pyeventsourcing/eventsourcing

Executive summary

pyeventsourcing/eventsourcing scores 60 out of 100, but it is rated At risk while a critical security finding is open; the score itself is unchanged.

The weakest lens counts most in the score, and here that is Production Readiness, which scores 44 and is rated Weak. Its DR & Backup dimension scores 0 out of 10, and until that reaches 4, Production Readiness can't be rated higher than Adequate. The first actions are to codify backups + geo-recovery in IaC and document RTO/RPO and the restore procedure — a persistence guard alone is not disaster recovery and to add a SAST step to CI running what this repository's stack ships: bandit, `semgrep --config=p/python`, or CodeQL's python pack — so a security regression fails the build instead of landing, and if Production Readiness rose to 70, the score would rise from 60 to about 70.

14 findings are critical: six in Static Analysis (SAST), five in IaC & Container Security and three in Dependency Vulnerabilities.

Watchdog couldn't measure 18 dimensions in this code, among them Code Coverage, Navigability and Data Protection, so they are left out of the score. The product code is 17,169 lines, which would take an estimated 0.3 person-years, around €45,000, to rebuild.

Code Health 92 ★ Exemplary Architecture 87 Adequate, capped by Project Cohesion Maturity 59 Adequate, capped by Architecture documentation Production Readiness 44 Weak, capped by Security & performance tooling and DR & Backup Security and Compliance 87 Strong Performance 90 ★ Exemplary

A lens is capped at Adequate while one of its dimensions scores below 4 out of 10, however well the rest of the lens does. That way a serious problem in one place always shows in the lens's rating.

How the score is built: what each lens counts for The lenses don't count equally. The weakest lens counts most, the next weakest a little less, and so on, so a weak area pulls the score down instead of being averaged away. In the bar below, each part's width shows how much that lens counts and its colour shows its rating. Improving the widest part moves the score most, and as that lens improves, it counts for less, because another lens becomes the weakest.

Production Readiness 44 · counts for 46%Maturity 59 · counts for 25%Architecture 87 · counts for 14%Security and Compliance 87 · counts for 8%Performance 90 · counts for 4%Code Health 92 · counts for 2%

If Production Readiness rose from 44 to 70, the lowest score rated Strong, the score would rise from 60 to about 70.

Code composition: what the lines of code are

Product code 49%Tests 51%

New since the last survey: 10 findings

These 10 critical or serious findings weren't in the previous survey, on 8 October 2026.

Code Duplication · Duplicated block (13 lines × 2) eventsourcing/dcb/postgres_tt.py
Boundary Type-Coupling · Cross-context type CanInitAggregate (eventsourcing → examples) examples/aggregate10/mutablemodel.py
Boundary Type-Coupling · Cross-context type CanInitAggregate (eventsourcing → examples) examples/aggregate11/domainmodel.py
Boundary Type-Coupling · Cross-context type CanInitAggregate (eventsourcing → examples) examples/aggregate8/mutablemodel.py
Boundary Type-Coupling · Cross-context type Aggregate (eventsourcing → examples) examples/cargoshipping/domainmodel.py
Boundary Type-Coupling · Cross-context type Aggregate (eventsourcing → examples) examples/contentmanagement/domainmodel.py
Boundary Type-Coupling · Cross-context type CanInitAggregate (eventsourcing → examples) examples/dcb_enrolment/domainmodel.py
Dependency Vulnerabilities · REDACTED
Dependency Vulnerabilities · REDACTED
Supply-chain Provenance & Signing · REDACTED

Watchdog compares every finding with the previous survey's. A finding that has only moved to another line in the same file counts as the same finding, so only new findings appear here. Advisory notes from the AI model are left out, because the model words them afresh in every survey.

Fixed since the last survey: 2 findings

These 2 critical or serious findings were in the previous survey, on 8 October 2026, and are gone from this one.

Code Duplication · Duplicated block (17 lines × 2) eventsourcing/dcb/postgres_tt.py
Supply-chain Provenance & Signing REDACTED

Rebuild cost: about €45,000 · Estimate

Cost to rebuild	€15,000 to €76,000, for 251 to 797 hours of work, about 0.3 person-years for one engineer
Difficulty of the problem	Standard, judged from the kind of software and how it is built. Code that solves a harder problem, such as payments or medical bookings, costs more per line to write.
Quality factor	×0.8 at a score of 60. Better code takes more work to write, so the factor is ×1.0 at a score of 70, lower below it and higher above it.
Size	Small: 17,169 lines of product code

How the estimate is made: Watchdog prices the hours a team would need to write this code again, at €60 to €95 an hour. Declarations and boilerplate are priced at a fast rate and logic at a slower one, and the logic is then multiplied by the difficulty of the problem and by the quality factor. The estimate can be about 30% off either way, and it moves most with the hourly rate and the difficulty. For this code, every line is priced as straight logic, which keeps the estimate on the low side.

Top priorities

The three actions that raise the score most for the work they take. The full ranked list is in the Roadmap.

Codify backups + geo-recovery in IaC and document RTO/RPO and the restore procedure — a persistence guard alone is not disaster recovery.

Raises the score by about 8 points · Medium effort · DR & Backup

Add a SAST step to CI running what this repository's stack ships: bandit, `semgrep --config=p/python`, or CodeQL's python pack — so a security regression fails the build instead of landing.

Raises the score by about 7 points · Medium effort · Security & performance tooling

Record your significant design decisions.

Write one short document per decision, giving its date, the situation, the decision and its consequences, and keep them together with your other design documents. A docs/adr folder with each file named by number and title is the easiest place to find them.

Raises the score by about 5 points · Medium effort · Architecture documentation

Diagnosis: what the measurements show together

Each conclusion below combines several dimensions into one point that no single dimension shows, and lists the measurements it rests on.

Where the investment is most exposed · Value at risk

This code would cost about €45,000 to build again, about 0.3 person-years of work. Its weakest lens is Production Readiness, at 44 (Weak). Production Readiness is about whether the product is ready to run in production and to change without breaking. Because the weakest lens counts most in the score, work on Production Readiness also moves the score most.

Based on: the rebuild estimate · the Production Readiness grade · how much each lens counts

What to do: Start with the Production Readiness actions in Top priorities.

If you do one thing first · First action

Codify backups + geo-recovery in IaC and document RTO/RPO and the restore procedure — a persistence guard alone is not disaster recovery. Of all the actions in this report, it raises the score most for the work it takes: about 8 points for medium effort. The next survey will show the change in the score.

Based on: the ranked actions in Top priorities, by score gain and effort

Architecture: which parts of the code depend on which

The code is divided into modules, groups of code that each handle one part of the product, and a module depends on another when it uses code from it. The table lists the modules both down the side and across the top, in an order where each module should only use modules listed above it. A number in a cell means the module on that row uses the module in that column, and it counts the pairs of building blocks (types) that connect them. The one thing to look for is a mark above the diagonal line. It means two or more modules use each other in a loop (a dependency cycle), so none of them can be changed, tested or released on its own.

111 modules, with 153 dependencies between them. Every module uses only modules listed above it, so there are no loops.

The table shows the 40 modules with the most connections; 71 more are left out to keep it readable.

Which modules use which. The module on each row uses the module in each column, and the number counts the pairs of types that connect them. A cell above the diagonal is part of a loop.
uses →	1 eventsourcing.dcb.api	2 eventsourcing.domain	3 eventsourcing.utils	4 examples.aggregate7.immutablemodel	5 examples.aggregate9.immutablemodel	6 examples.dcb_enrolment.interface	7 eventsourcing.dcb.application	8 eventsourcing.dcb.domain	9 eventsourcing.persistence	11 examples.aggregate8.mutablemodel	12 examples.cargoshipping.domainmodel	13 examples.contentmanagement.domainmodel	15 eventsourcing.application	16 eventsourcing.dcb.persistence	17 eventsourcing.postgres	18 eventsourcing.sqlite	19 examples.ftscontentmanagement.persistence	20 examples.searchabletimestamps.persistence	22 eventsourcing.dcb.msgpack	25 eventsourcing.projection	28 examples.cargoshipping.application	32 examples.ftscontentmanagement.postgres
1 eventsourcing.dcb.api
2 eventsourcing.domain
3 eventsourcing.utils
4 examples.aggregate7.immutablemodel
5 examples.aggregate9.immutablemodel
6 examples.dcb_enrolment.interface
7 eventsourcing.dcb.application			1
8 eventsourcing.dcb.domain		1
9 eventsourcing.persistence		7	1
10 examples.aggregate10.mutablemodel		4			3
11 examples.aggregate8.mutablemodel		4		3
12 examples.cargoshipping.domainmodel		4
13 examples.contentmanagement.domainmodel		6
14 examples.shopvertical.common				2
15 eventsourcing.application		1	1						5
16 eventsourcing.dcb.persistence	7								1
17 eventsourcing.postgres									11
18 eventsourcing.sqlite									13
19 examples.ftscontentmanagement.persistence									1
20 examples.searchabletimestamps.persistence									1
21 examples.shopstandard.domain				2						7
22 eventsourcing.dcb.msgpack	1							2						1
23 eventsourcing.dcb.popo	5													2
24 eventsourcing.dcb.postgres_tt	4													2	3
25 eventsourcing.projection			1				1		4				1
26 examples.aggregate7.orjsonpydantic									3				1
27 examples.aggregate9.msgpack									3				1
28 examples.cargoshipping.application									5		8		1
29 examples.contentmanagement.application												2	1
30 examples.dcb_enrolment.application						1							1
31 examples.dcb_enrolment_with_basic_objects.postgres_ts	4													1	3
32 examples.ftscontentmanagement.postgres															3		2
33 examples.ftscontentmanagement.sqlite																5	2
34 examples.searchabletimestamps.postgres									1						3			1
35 examples.searchabletimestamps.sqlite									1							4		1
36 eventsourcing.system									1				3							1
37 examples.dcb_enrolment_with_enduring_objects.application						1	1	3											6
38 examples.dcb_enrolment_with_vertical_slices.application						1	1	24											8
39 examples.ftsprojection.projection									4			2			1		1			1		1
40 examples.searchabletimestamps.application											1		1								1

Uses a module listed above itPart of a loopThe module itself

At a glance — Code Health · 92% · Exemplary ·

The Good

D1 · Python Cyclomatic Complexity 7.9 D3 · Python God Classes 8.4 D4 · Python Code Duplication 9.3 D17 · Python Explicit Debt 9.6 X1 · Repo Async correctness 10.0 X12 · Repo Unreachable branch 10.0 X13 · Repo Undrained process stream 10.0 X19 · Repo Unrestored process-global state 10.0 X21 · Repo Side-effecting pattern guard 10.0 X22 · Repo Contradicted release guard 10.0 X23 · Repo Unguarded diagnostic materialisation 10.0 X25 · Repo Inert configuration knob 10.0 X26 · Repo Unsynchronised callback handoff 10.0 X27 · Repo Collection changed while being enumerated 10.0 X28 · Repo Index access outside its own emptiness guard 10.0 X3 · Repo Exception handling 10.0 X30 · Repo Support guard that admits what it rejects 10.0

The Bad

D2 · Python Cognitive Complexity 6.3

At a glance — Architecture · 87% · Adequate · gated by D26 ·

The Good

D6 · Python Cohesion (LCOM4) 9.5 D23 · Python Boundary Type-Coupling 8.3 D35 · Python Change Coupling 9.8 AX10 · Repo Code composition 9.0 AX3 · Repo Project dependency cycles 10.0 AX4 · Repo Dependency direction 10.0 AX5 · Repo Architecture & structure 10.0

The Ugly

D22 · Python Internal API Consistency 4.0 D26 · Python Project Cohesion 0.0

At a glance — Maturity · 59% · Adequate · gated by M2 ·

The Good

D15 · Python Churn × Complexity Hotspots 10.0 D19 · Python Documentation Quality 8.9 D21 · Python Naming Consistency 10.0 D34 · Python Knowledge Freshness 10.0 M3 · Repo Folder & project structure 8.0 M4 · Repo Documentation accuracy 8.0

The Bad

M1 · Repo Documentation (README) 6.7

The Ugly

M2 · Repo Architecture documentation 2.0

At a glance — Readiness · 44% · Weak · gated by P3, P5 ·

The Good

D9 · Python Test Distribution 10.0 D11 · Python Test Reliability 10.0 D13 · Python Secret Scanning 10.0 D14 · Python License Compliance 10.0 P1 · Repo CI/CD gates 10.0 P10 · Repo Library API & versioning 10.0 P2 · Repo Observability 7.0 P6 · Repo Release Hygiene 10.0

The Bad

P4 · Repo Deployment & Rollback 5.0

The Ugly

P3 · Repo Security & performance tooling 1.0 P5 · Repo DR & Backup 0.0

At a glance — Security · 87% · Strong ·

The Good

D28 · Python Secrets (history) 10.0 D30 · Python Dependency Vulnerabilities 7.5 D31 · Python IaC & Container Security 8.2 D43 · Python Malicious Dependencies 10.0 D44 · Python Platform End-of-Life 10.0 X14 · Repo Bypassable address classification 10.0 X15 · Repo Unvalidated length from an untrusted reader 10.0 X17 · Repo Uncapped recursion over a caller-supplied document 10.0 X24 · Repo Document value interpolated into markup unescaped 10.0

The Bad

D29 · Python Static Analysis (SAST) 6.7

At a glance — Performance · 90% · Exemplary ·

The Good

PF1 · Repo Benchmark discipline 9.0

Security & Compliance — OWASP Top-10 mapping

Findings mapped to OWASP categories; the specific CVEs/secrets are in the Security dimension cards below and findings.md (redacted only on the public version of this report).

OWASP category	Findings	Severity
A05:2025 — Injection	7	High / Critical
A02:2025 — Security Misconfiguration	6	High / Critical
A03:2025 — Software Supply Chain Failures	3	High / Critical

Roadmap

First, codify disaster recovery by defining RTO/RPO and restore procedures in infrastructure as code, ensuring backups are properly credited. Second, integrate static security analysis into the CI pipeline to fail builds on regressions, while documenting key architectural decisions in a dedicated folder. Finally, improve deployment reliability by adding health checks and immutable image tags for easy rollbacks, and implement observability through tracing and a health endpoint.

Ranked by impact ÷ effort. "Helps" is the estimated gain on the 0–100 health score.

Do this	Helps	Effort	Dimension
Codify backups + geo-recovery in IaC and document RTO/RPO and the restore procedure — a persistence guard alone is not disaster recovery.	+7.6 pts	Medium	DR & Backup
Add a SAST step to CI running what this repository's stack ships: bandit, `semgrep --config=p/python`, or CodeQL's python pack — so a security regression fails the build instead of landing.	+6.7 pts	Medium	Security & performance tooling
Record your significant design decisions. Write one short document per decision, giving its date, the situation, the decision and its consequences, and keep them together with your other design documents. A docs/adr folder with each file named by number and title is the easiest place to find them.	+5.4 pts	Medium	Architecture documentation
Add a `healthcheck:` to the served compose service — probing the endpoint it already answers on where it has one — with `depends_on: condition: service_healthy` on whatever waits for it, and keep the deployed image tag immutable and recorded so rolling back is re-pointing at the previous tag rather than rebuilding.	+3.0 pts	Medium	Deployment & Rollback
Resolve the 3 Documentation finding(s) in Documentation Quality — start with release_notes.rst, aggregate5.rst, aggregate6.rst.	+1.4 pts	Low	Documentation Quality
Consider OpenTelemetry tracing/metrics (opentelemetry-sdk) and a health-check endpoint (a /health route) for operability.	+1.6 pts	Medium	Observability
Explain in the README how to run the tests. Add a section called Testing to the README in the repository's top folder, saying how to run the test suite.	+1.5 pts	Medium	Documentation (README)
Resolve the 1 Projects may be oversized for their cohesion finding(s) in Project Cohesion.	+0.5 pts	Low	Project Cohesion

File quality

Per-file score 0–10 — a quality signature. Of 52 files carrying findings, judged against the Production bar: 2% slop · 35% mixed · 63% near-clean.

File	Score	Band	Worst signal
REDACTED	1.4	Slop	Static Analysis (SAST): High: REDACTED
REDACTED	4.6	Mixed	IaC & Container Security: High IaC: REDACTED
REDACTED	5.1	Mixed	Dependency Vulnerabilities: Critical vulnerability: REDACTED
eventsourcing/domain.py	6.0	Mixed	Explicit Debt: TodoComment
eventsourcing/postgres.py	6.0	Mixed	Explicit Debt: TodoComment
eventsourcing/persistence.py	6.0	Mixed	Explicit Debt: TodoComment
eventsourcing/application.py	6.0	Mixed	Explicit Debt: TodoComment
eventsourcing/dcb/domain.py	6.0	Mixed	Explicit Debt: TodoComment
eventsourcing/dcb/postgres_tt.py	6.0	Mixed	Explicit Debt: TodoComment
eventsourcing/utils.py	6.7	Mixed	Explicit Debt: TodoComment
eventsourcing/dcb/popo.py	6.7	Mixed	Explicit Debt: TodoComment
eventsourcing/dcb/persistence.py	6.7	Mixed	Explicit Debt: TodoComment
tests/dcb_tests/test_domain.py	6.9	Mixed	Explicit Debt: TodoComment
examples/dcb_enrolment_with_vertical_slices/application.py	7.0	Mixed	Boundary Type-Coupling: Cross-context type Selector (eventsourcing → examples)
eventsourcing/system.py	7.0	Mixed	Cognitive Complexity: NewSingleThreadedRunner.receive_recording_event (cognitive 40)
REDACTED	7.2	Mixed	Static Analysis (SAST): High: REDACTED
tests/domain_tests/test_aggregate_decorators.py	7.3	Mixed	Explicit Debt: TodoComment
examples/aggregate5/domainmodel.py	7.8	Mixed	Code Duplication: Duplicated block (8 lines × 3)
REDACTED	7.9	Mixed	IaC & Container Security: Medium IaC: REDACTED
eventsourcing/projection.py	8.2	Near-clean	Explicit Debt: TodoComment

How the grades work

Every finding carries one of four grades. Three say how serious it is. The fourth says this survey could not settle it — and it is a grade, not a gap.

Critical — 14

A definite problem that already costs you something and drags the score down: a missing authorisation check, a dependency with a known exploit, a build that does not reproduce. Failure here tends to cause failures elsewhere.

Serious — 116

Likely wrong, but not failing yet. It degrades the codebase over a longer horizon and can cause failures elsewhere — not urgent this week, not something to carry for two years either.

Minor — 16

Recorded, with no effect on how the codebase functions. Present so the survey is complete, not because it needs doing.

Could not be resolved — 18

Something this survey could not settle from the outside, and which could be critical or serious. Either a control was required and no positive evidence of it exists in the repository — a backup job that nothing shows was ever restored from proves nothing about restores — or our own analysis could not run over that part of the tree. This is not a clean result. These are excluded from the score rather than awarded a pass, so the number on the cover neither rewards nor penalises them: if you act on this survey without resolving them, you carry that risk yourself. Each one is named under Limitations.

Methodology & how to trust this report

Watchdog is a deep, periodic assessment — run each sprint, monthly, or quarterly, taking the time to go wider and deeper than a quick check and surfacing in one coherent report what you'd otherwise piece together from a dozen separate tools. It scores deterministically: the same commit yields the same score, every run. 52 of 57 evaluated dimensions are computed purely by tools and static analysis (confidence 1.0); 5 documentation/naming judgement(s) are LLM-assisted and labelled advisory. Overall confidence is 0.9 — the weighted average across measured dimensions; it falls as more of the score leans on LLM-assisted judgement and rises when it's fully tool-backed.

Every figure here is one of three kinds, and we label which: ✓ Measured — a deterministic fact (LoC, complexity, coverage); ~ Modeled — an estimate from a stated model (cost, effort, value-at-risk), always a range with its assumptions, never a precise fact; ◐ Advisory — an LLM prose judgement. We never present a modelled estimate as if it were measured. Perfect or absent scores carry their provenance too (ADR-0011): ✓ Tool-verified means the property itself was measured across the surface; ○ Nothing flagged means the probes came back clean — a claim bounded by what a repository can show; ⊘ Not evidenced means a working control (a tested restore, an automated rollback) showed no positive evidence — absence of evidence is not evidence of a control, so it's excluded from the score rather than awarded a spurious 10; ◐ Sampled · advisory marks an LLM verdict over a bounded sample — advisory, never a deterministic measurement.

What we checked — 57 dimensions across the health lenses

D1D2D3D4D6D9D11D13D14D15D17D19D21D22D23D26D28D29D30D31D34D35D43D44AX10AX3AX4AX5M1M2M3M4P1P10P2P3P4P5P6PF1X1X12X13X14X15X17X19X21X22X23X24X25X26X27X28X3X30

Each chip is a dimension scored from real signals across architecture, testing, dependencies, security & compliance, documentation, git-history and code quality — in one coherent pass. A surface report typically covers a handful.

How to trust any code-health report — three questions

Can you open the finding? Real findings cite a repo-relative file and line you can open at the cited line — never an absolute scratch path. Here, 133 of 146 do; the remainder are repo-wide signals — a dimension-level measurement, not a single line. (Every path in this report is repo-relative by construction: paths are normalized at the producer and the report is rejected if any rooted path leaks through.)
Is there a tool behind the number? Every score below names the method that produced it — Roslyn, git, a scanner, or (for a handful of documentation/naming dimensions) an LLM labelled sampled · advisory — not a narrative.
Does re-running give the same result? Run it again on the same commit and the score — and this report, byte for byte — is identical. A report whose numbers move between runs is describing the run, not the code.

This report answers yes to all three. That's the bar to hold any assessment to.

Tools & methods

The actual versions used this run (captured at analysis time) — re-run on the same commit for the identical score.

Method	Backs	Version	Evaluator
Roslyn static analysis	Complexity, cohesion, coupling, dead code, API surface, layering	5.3.0	✓ deterministic
Native secret scanner	Hardcoded secrets / credentials	1.0.0	✓ deterministic
Watchdog duplication detector (in-process)	Code duplication	1.0.0	✓ deterministic
Coverage (coverlet / dotnet-coverage)	Line & branch coverage	10.0.400	✓ deterministic
NuGet / dotnet	Outdated, vulnerable & deprecated dependencies	10.0.400	✓ deterministic
git / LibGit2Sharp	Churn hotspots, knowledge concentration, history	2.43.0 · 0.31.0	✓ deterministic
gitleaks · semgrep · trivy · checkov	Secrets in history, SAST, CVEs, IaC & container, PII / GDPR	1.86.0 · 0.69.3 · 3.2.533	✓ deterministic
LLM (sampled · advisory)	Documentation quality, ADR conformance, naming — sampled over a bounded sample; advisory, never a deterministic measurement	Local LLM	◐ LLM · sampled · advisory

Every finding is locatable in findings.md. Run 01a16573-4e84-7575-8a36-cde73b2a4eba.

The exact command behind every deep-scan dimension — tool, version, invocation and retained raw output — is in Appendix B — Reproduction & audit trail.

Run transparency — what happened this run

What ran differently this time — a tool absent, degraded, or that fell back to an estimate. Named openly, not folded silently into the scores. A degraded run also records its exact cause in diagnostics.md.

D8 Code Coverage — not measured this run — Watchdog could not measure this here. That is a gap on our side — a collector, parser or image we have not built yet — and it is neither a defect in this repository nor evidence that the check would have passed. Coverage NOT READ here — but this repository measures it: a coverage step in CI (`coverage run`) shows that coverage is collected and tracked in your own CI. The built-in collector has no runner for this ecosystem (.py), so the analyzer could not read the number — a gap in the analyzer's language coverage, not an unmeasured repo. Not scored. To have the real number read, produce a coverage report in a standard format (`coverage run -m pytest` then `coverage xml`) and commit it — a hosted scan measures a clone of the repository, so a report that exists only in a working tree, a CI runner's or your own, never reaches it; the artefact is commonly gitignored, so `git add -f` that one file (or un-ignore its path) and commit it alongside the code it measures. You can widen what we reach: optional: produce a coverage report in a standard format (`coverage run -m pytest` then `coverage xml`) and commit it — a hosted scan measures a clone of the repository, so a report that exists only in a working tree, a CI runner's or your own, never reaches it; the artefact is commonly gitignored, so `git add -f` that one file (or un-ignore its path) and commit it alongside the code it measures — then the real number is read on the next scan.
D12 Dependency Hygiene — not measured this run — This is a true statement about the repository that carries nothing for its owner to act on, so it is reported here rather than as a defect in their code. This repository's 1 shipped Python distribution(s) across 1 manifest(s) WERE read; what went unanswered is the currency half, because it grades an EXACT pin against the newest release and every declaration here is a floor or a range — which installs the newest release it admits and so cannot be behind one. So pypi.org was never asked. This is a true statement about the repository, and the healthy one, NOT a gap on our side: no reader we could write would find a currency question here.
D16 Bus Factor — not measured this run — This is a true statement about the repository that carries nothing for its owner to act on, so it is reported here rather than as a defect in their code. Single-maintainer repository — bus factor is not applicable (29 contributor(s) across 5388 commit(s) sampled, automation and bot accounts excluded). One of them holds 98% of the history; the other 28 hold 0.1% each on average, below the 5% at which there is somebody to hand the work to. That is a single maintainer with drive-by contributors, not a team whose knowledge has concentrated — so the bus factor is not applicable and there is nothing here for the owner to act on.
D27 Navigability — not measured this run — Watchdog could not measure this here. That is a gap on our side — a collector, parser or image we have not built yet — and it is neither a defect in this repository nor evidence that the check would have passed. Navigability is taken over call sites whose callee resolved. For C# that population includes calls into referenced assemblies; for this language only calls declared inside the repository count, so the abstention threshold reads the repository's use of its standard library as a resolution failure. That is a limit of this analyzer, not a build problem in this repository.
AX1 Captive dependencies — not measured this run — Watchdog could not measure this here. That is a gap on our side — a collector, parser or image we have not built yet — and it is neither a defect in this repository nor evidence that the check would have passed. This check reads Microsoft.Extensions.DependencyInjection registrations in C# and Spring beans in Java/Kotlin only, and this repository defines its own container in eventsourcing/dispatch.py, whose lifetimes are not modelled yet, so it had nothing of this repository's product to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
AX6 Interface segregation — not measured this run — Watchdog could not measure this here. That is a gap on our side — a collector, parser or image we have not built yet — and it is neither a defect in this repository nor evidence that the check would have passed. This check is computed over the public interfaces this run's compilations declare, and none was loaded, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
AXR1 Runtime accessibility — not measured this run — Watchdog could not measure this here. That is a gap on our side — a collector, parser or image we have not built yet — and it is neither a defect in this repository nor evidence that the check would have passed. Render strategy: boot via DockerCompose (REDACTED). compose up failed (exit 18 — an image could not be pulled) — axon Pulling cassandra Pulling redis Pulling mysql Error Get "https://registry-1.docker.io/v2/": Forbidden axon Error Get "https://registry-1.docker.io/v2/": Forbidden postgres Error context canceled redis Error context canceled eventsourcing_requirements Warning context canceled cassandra Error context canceled Error response from daemon: Get "https://registry-1.docker.io/v2/": Forbidden; the earlier `compose pull` step reported: eventsourcing_requirements Warning context canceled redis Error context canceled cassandra Error context canceled mysql Error context canceled postgres Error context canceled WARNING: Some service image(s) must be built from source by running: docker compose build eventsourcing_requirements Error response from daemon: Get "https://registry-1.docker.io/v2/": Forbidden; the runtime sandbox reaches registries only through the in-fence pull-through mirror, so an image the mirror does not carry cannot be fetched — this is a limit of our sandbox, not of your stack; runtime evidence skipped.
C1 Data Protection — not measured this run — Watchdog could not measure this here. That is a gap on our side — a collector, parser or image we have not built yet — and it is neither a defect in this repository nor evidence that the check would have passed. These personal data controls are read from declarative annotations, request middleware, entity/column names and guard methods in a C# source model, and none was loaded on this run, so there was nothing to gather. That is a gap in this analyzer's language reach — not a finding that the repository lacks personal data controls.
C3 Audit Trail — not measured this run — Watchdog could not measure this here. That is a gap on our side — a collector, parser or image we have not built yet — and it is neither a defect in this repository nor evidence that the check would have passed. 'sqlite3' is imported (eventsourcing/sqlite.py:3), but no entity, schema, table or model declaration this check reads was found beside it, so whether personal data is stored could not be decided.
C4 Data Retention — not measured this run — Watchdog could not measure this here. That is a gap on our side — a collector, parser or image we have not built yet — and it is neither a defect in this repository nor evidence that the check would have passed. 'sqlite3' is imported (eventsourcing/sqlite.py:3), but no entity, schema, table or model declaration this check reads was found beside it, so whether personal data is stored could not be decided.
C5 Data-Subject Rights — not measured this run — Watchdog could not measure this here. That is a gap on our side — a collector, parser or image we have not built yet — and it is neither a defect in this repository nor evidence that the check would have passed. 'sqlite3' is imported (eventsourcing/sqlite.py:3), but no entity, schema, table or model declaration this check reads was found beside it, so whether personal data is stored could not be decided.
GD1 Unfinished & placeholder code — not measured this run — Watchdog could not measure this here. That is a gap on our side — a collector, parser or image we have not built yet — and it is neither a defect in this repository nor evidence that the check would have passed. This check reads C# syntax, F#, JavaScript/TypeScript, Dart, Ruby and Scala source only, and no C#, F#, JavaScript/TypeScript, Dart, Ruby or Scala was found, and this repository's Python is not read yet, so it had nothing of this repository's product to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
IC1 Incompleteness & stubs — not measured this run — Watchdog could not measure this here. That is a gap on our side — a collector, parser or image we have not built yet — and it is neither a defect in this repository nor evidence that the check would have passed. This check reads C# syntax, JavaScript/TypeScript, Java, Dart, Ruby and Scala source only, and no C#, JavaScript/TypeScript, Java, Dart, Ruby or Scala was found, and this repository's Python is not read yet, so it had nothing of this repository's product to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
P8 Schema migrations — not measured this run — Watchdog could not measure this here. That is a gap on our side — a collector, parser or image we have not built yet — and it is neither a defect in this repository nor evidence that the check would have passed. The schema may be created by a runner, a deploy script or a config file outside what this check reads, so an absence here is our blind spot rather than a missing migration strategy. The card abstains instead of scoring. You can widen what we reach: if the schema is created and evolved by a tool this check does not name, naming it lets us teach the detector to read it.
S1 Web-Security Posture — not measured this run — Watchdog could not measure this here. That is a gap on our side — a collector, parser or image we have not built yet — and it is neither a defect in this repository nor evidence that the check would have passed. These web-security controls are read from declarative annotations, request middleware, entity/column names and guard methods in a C# source model, and none was loaded on this run, so there was nothing to gather. That is a gap in this analyzer's language reach — not a finding that the repository lacks web-security controls.
X16 Unfloored truncation loop — not measured this run — Watchdog could not measure this here. That is a gap on our side — a collector, parser or image we have not built yet — and it is neither a defect in this repository nor evidence that the check would have passed. This check reads C# syntax, and JavaScript/TypeScript, Java, PHP, Dart, Ruby, Scala and Kotlin source only, and no C# was loaded and no JavaScript/TypeScript, Java, PHP, Dart, Ruby, Scala or Kotlin was found in this repository, so it had nothing of this repository's product to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
X18 Disposal-pattern correctness — not measured this run — Watchdog could not measure this here. That is a gap on our side — a collector, parser or image we have not built yet — and it is neither a defect in this repository nor evidence that the check would have passed. This check reads C# syntax, and JavaScript/TypeScript, Java, Kotlin, Dart, Ruby, Scala and PHP source only, and no C# was loaded and no JavaScript/TypeScript, Java, Kotlin, Dart, Ruby, Scala or PHP was found in this repository, so it had nothing of this repository's product to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
X29 Per-element action decided by a fixed element — not measured this run — Watchdog could not measure this here. That is a gap on our side — a collector, parser or image we have not built yet — and it is neither a defect in this repository nor evidence that the check would have passed. This check reads C# syntax, and JavaScript/TypeScript, Java, Rust, Dart, Ruby, Scala and Kotlin source only, and no C# was loaded and no JavaScript/TypeScript, Java, Rust, Dart, Ruby, Scala or Kotlin was found in this repository, so it had nothing of this repository's product to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
X4 Structured logging — not measured this run — Watchdog could not measure this here. That is a gap on our side — a collector, parser or image we have not built yet — and it is neither a defect in this repository nor evidence that the check would have passed. This check reads C# syntax, and JavaScript/TypeScript, Java, Kotlin, Python, PHP, Dart, Ruby, Scala and Rust source only, and no C# was loaded, and this repository's JavaScript/TypeScript, Python and PHP make no call through a named logger, so it had nothing of this repository's product to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
X5 Nullable reference types — not measured this run — Watchdog could not measure this here. That is a gap on our side — a collector, parser or image we have not built yet — and it is neither a defect in this repository nor evidence that the check would have passed. This check reads C# syntax and MSBuild project configuration, TypeScript source and its tsconfig files, Java source and its package and module declarations, PHP source and its PHPStan and Psalm configuration, Dart source and its pubspec language version, Ruby source and its Sorbet and Steep configuration, Scala source and its build's explicit-nulls, WartRemover and Scalafix settings, and Kotlin source only, and no C# was loaded, no TypeScript was found, and this repository's Python is not read yet, so it had nothing of this repository's product to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.

Repo exclusion declarations (.gitattributes linguist-generated/vendored, .editorconfig generated_code): none declared — every source file was scored.

Limitations & what we did not check

Watchdog assesses the repository exactly as committed, and only the repository. By design it does not reach outside the source tree: the live cloud account, the running CI/CD pipeline, the host's branch-protection and approval rules, the production configuration, or a restore actually exercised against a backup are all out of scope. That boundary is a feature, not a gap — a repo-relative, deterministic scan re-runs identically on any commit and every finding opens at a real file and line, where a live audit can neither be reproduced nor traced. The visible consequence is that controls which leave no in-repo evidence are reported as "not evidenced" and excluded from the score rather than awarded a number a static scan cannot justify.

Per-dimension blind spots

For each dimension that was measured, what a static, repo-only scan structurally cannot see — the honest edge of the measurement, not a failure of it.

D1 Cyclomatic Complexity: Cyclomatic complexity counts branches statically — it cannot tell an essential decision tree from accidental tangle, nor see complexity that lives in data or configuration (large switch-case token tables, DSL lexers/parsers, data-as-code rule tables) rather than control flow: a tokenizer's many single-character cases read as high complexity though each branch is trivial.
D2 Cognitive Complexity: Cognitive-complexity heuristics approximate how hard code is to follow; genuine domain difficulty and well-named intent that eases reading are not captured.
D3 God Classes: "God class" is sized by members and responsibilities visible in the type — a deliberately broad facade over a coherent subsystem can read the same as an accidental grab-bag. For front-end JS the file-length check is cohesion-aware (a single-responsibility module — one class/IIFE — earns a 3× threshold), but cohesion is approximated from top-level declarations, not true dependency structure.
D4 Code Duplication: Duplication is token-similarity — an in-process token-stream comparison over sliding windows, with type-aware normalization — so it finds copy-paste, not semantic duplication expressed differently. Committed machine-written code (scaffolded migrations, designer/codegen output, protobuf/OpenAPI stubs, model snapshots) is EXCLUDED — its repetition is the tool's, not the team's — so the score reflects hand-written duplication only.
D6 Cohesion (LCOM4): LCOM4 cohesion is syntactic — it infers connectivity from which methods touch which fields/methods by name, not from real runtime behaviour or intent.
D9 Test Distribution: The test-pyramid shape is inferred from project/folder naming and references, with a single test host bucketed per-file by its path tier and content signals — a suite that names tiers unconventionally and gives no per-file signal can still be mis-bucketed.
D11 Test Reliability: Flakiness is inferred from history/markers — Watchdog runs the suite once (for coverage), not the repeated runs under varied conditions that reveal nondeterminism, so a flaky test never recorded as failing is invisible here.
D13 Secret Scanning: Secret detection is signature- and entropy-based on the current tree — a secret that does not match a known pattern, or one already rotated, will not be flagged (a clean scan is "nothing matched", not "no secrets exist").
D14 License Compliance: License compatibility is checked against declared package metadata and a policy — mislabelled or missing license metadata, and obligations that depend on how you distribute, are not resolved here.
D15 Churn × Complexity Hotspots: Churn hotspots come from git history — a freshly imported or squashed repository has no churn signal, and recent rewrites can mask a historically risky file.
D17 Explicit Debt: Acknowledged-debt signals (TODO/FIXME, suppressions, dead code) are textual — undocumented debt that nobody marked, and debt that lives in design rather than annotations, is invisible. Committed machine-written code (scaffolded migrations, designer/codegen output, generated stubs) is excluded — it is never the team's dead code to delete.
D19 Documentation Quality: Documentation quality is judged by an LLM over a bounded sample of docs — it reads what is written, not whether the docs match the running system, and it is advisory, not a measurement. Its critique rows are drawn from a closed category vocabulary and each row means the same thing in every run, so two scans can be compared row by row; the SET that fires is still a sample, and does not repeat exactly. Measured on one frozen input, six scans at one engine SHA: 2-5 critique rows per scan, 8 distinct rows across the six, 3 of those 8 seen in only one scan. So a D19 row is evidence about the documentation, but a COUNT of D19 rows is not a quantity — never read a change in it as an improvement or a regression.
D21 Naming Consistency: Naming quality is an LLM judgement over a bounded sample — it assesses clarity/consistency of the names it sees, not domain-correctness, and is advisory.
D22 Internal API Consistency: API-surface coherence is an LLM judgement over a sample of the public surface — consistency of intent across the whole API is approximated, not exhaustively verified.
D23 Boundary Type-Coupling: Boundary leakage is detected from type references across detected contexts — leaks that flow through primitives, serialization or shared infrastructure may not surface as a typed reference.
D26 Project Cohesion: Project focus is sized from members/namespaces per project — a project that is broad by deliberate design reads the same as one that has sprawled.
D28 Secrets (history): Secret-history scanning sweeps the git log for known patterns — a secret that predates the available history, or never matched a signature, is not found (clean means "nothing matched in the history we can see").
D29 Static Analysis (SAST): SAST findings are pattern-based (semgrep) — it finds classes of bug it has rules for; logic flaws, auth/authorization gaps and issues needing runtime context are out of reach (and clean means "no rule matched").
D30 Dependency Vulnerabilities: CVE matching depends on accurate package/version metadata and on the advisory databases — a vulnerability with no published advisory, or in code not declared as a dependency, is not seen. Coverage needs a RESOLVED graph: an unpinned requirements.txt, or a pom without a resolved build, yields partial coverage rather than a clean verdict. An ecosystem the analyzer cannot scan is reported as unmeasured, never as clean.
D31 IaC & Container Security: IaC scanning checks Dockerfiles/Terraform/Kubernetes against best-practice rules — it cannot see the live cloud account, runtime configuration, or drift between the committed config and what is actually deployed.
D34 Knowledge Freshness: Freshness is decayed commit RECENCY, not comprehension — code read often but rarely committed reads as orphaned, and stable code that genuinely needs no changes is penalised the same as forgotten code; bot/squash commits distort it like the bus factor.
D35 Change Coupling: Change coupling is co-change in COMMITS — files split across separate commits, or coupled only through a shared config/build step, read as uncoupled, and a sweeping commit (rename/format) is excluded so it doesn't couple everything. It shows that files change together, not WHY: a high coupling can be a healthy cohesive pair as readily as a hidden leak.
D43 Malicious Dependencies: Only packages some vulnerability database has already NAMED as malicious are seen — a compromise published in the last hours, or never reported at all, is invisible here, and this dimension reading 10 is not evidence that a dependency is trustworthy. There is no typosquat or dependency-confusion analysis: a package nobody has reported is simply absent from the feeds. Coverage is the dependency scan's: an ecosystem that could not be scanned is disclosed as unmeasured, never as clean.
D44 Platform End-of-Life: The support table is FROZEN, so it goes out of date by losing RECALL: a release that ended support after the table was written is missed until the table is refreshed, and this dimension reading 10 is not evidence that a platform is current. Only platforms the repository DECLARES in a place this pass reads are seen — a runtime named only in a Dockerfile (D31's subject), in a CI workflow (D29's), or in a file this pass does not parse (go.mod, a Gemfile ruby directive) is invisible here, which is why a repository declaring none of them abstains rather than scoring. Only frameworks with a PUBLISHED support policy are tracked: React, Flask and Express publish none, so their age cannot be judged and their absence from a report is not a statement that they are supported.
AX10 Code composition: Role is inferred from namespace/folder convention, not semantics — a domain concept living in a folder named "Services" reads as application, and the split is lines-of-code, not business value. The business-logic-share score is a SOFT, FLOORED signal: it contributes to the Architecture lens but is floored at the Critical gate, so an infrastructure-heavy design (a gateway, an ETL, a driver) is legitimately low without being nuked to zero.
M4 Documentation accuracy: Onboarding quality is an LLM read of the docs/setup present — it cannot run the onboarding or measure how long a real new joiner takes; the verdict is sampled and advisory.
P4 Deployment & Rollback: Approval/branch-protection rules live in repository settings the scan cannot see — only their in-repo evidence (config files, workflows) is checked, so a control enforced purely in the host's settings reads as "not evidenced".
P5 DR & Backup: Backup/restore and disaster-recovery readiness is judged from in-repo evidence — a config that exists is not a tested restore, so the absence of positive evidence is reported as "not evidenced", never scored as present.
P6 Release Hygiene: Rollback/observability controls are inferred from repo artefacts (pipelines, dashboards-as-code) — controls configured in external tooling, with no in-repo trace, cannot be credited.

The LLM boundary

LLM-set scores this run (5): D19, D21, D22, D26, M4 (model: Local LLM). For these, a model reads a bounded sample and sets the numeric score; each names its own sample and method on its card. They are sampled and advisory by design: they vary at the margins between runs and are never a deterministic measurement. Every other score in this report is tool-computed at confidence 1.0.

Dimensions

D1 · Cyclomatic Complexity7.9 / 10Strong✓ Tool-verified

What it measures: How tangled the control flow is — methods with many branches are hard to test and change.

Method: Cyclomatic complexity per method (1 + decision points), computed exhaustively across production source; test projects separated by convention. Deterministic.

Maturity: Documented → Verified → Prevented · effective 7.9 / 10 · rule-coverage 100% · ceiling Prevented

4 method(s) exceeded the cyclomatic complexity threshold of 15; the worst was BaseAggregate.__init_subclass__ at 83.

BaseAggregate.__init_subclass__ (cyclomatic 83)eventsourcing/domain.py:1296

domain._spec_coerce_args_to_kwargs (cyclomatic 25)eventsourcing/domain.py:937

BasePostgresFactory.__init__ (cyclomatic 25)eventsourcing/postgres.py:1138

CommandMethodDecorator.__init__ (cyclomatic 17)eventsourcing/domain.py:484

What to do

Bring the 1 body over 30 down to 30 or less in Cyclomatic Complexity — start with BaseAggregate.__init_subclass__ (cyclomatic 83). — Refactoring it lifts Cyclomatic Complexity from 7.9 to about 9.0/10.
Enforce Cyclomatic Complexity in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Prevented — provenance only; does not change the score.

Detailed fixes: d1_recommendation.md · top locations in Appendix A, every location in findings.md.

Do you agree with this assessment?

D2 · Cognitive Complexity6.3 / 10Adequate✓ Tool-verified

What it measures: How hard the code is for a person to follow, beyond raw branching.

Method: Cognitive complexity per method (Sonar-style nesting-penalized score), computed exhaustively over production code, excluding test projects. Deterministic.

Maturity: Documented → Verified → Prevented · effective 6.3 / 10 · rule-coverage 100% · ceiling Prevented

14 method(s) exceeded the cognitive complexity threshold of 15; the worst was BaseAggregate.__init_subclass__ at 173.

BaseAggregate.__init_subclass__ (cognitive 173)eventsourcing/domain.py:1296

NewSingleThreadedRunner.receive_recording_event (cognitive 40)eventsourcing/system.py:533

domain._spec_coerce_args_to_kwargs (cognitive 37)eventsourcing/domain.py:937

BasePostgresFactory.__init__ (cognitive 31)eventsourcing/postgres.py:1138

utils.resolve_topic (cognitive 30)eventsourcing/utils.py:53

+ 9 more group(s) — more in Appendix A; the complete list is findings.md.

What to do

Bring the 1 body over 60 down to 60 or less in Cognitive Complexity — start with BaseAggregate.__init_subclass__ (cognitive 173). — Refactoring it lifts Cognitive Complexity from 6.3 to about 7.4/10.
Enforce Cognitive Complexity in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Prevented — provenance only; does not change the score.

Detailed fixes: d2_recommendation.md · top locations in Appendix A, every location in findings.md.

Do you agree with this assessment?

D3 · God Classes8.4 / 10Strong✓ Tool-verified

What it measures: Over-large classes that try to do too much ("god classes").

Method: God-class detection by line and method-count thresholds per logical type (partial classes unified), filtered for generated code and registration/contract false positives. Deterministic.

Maturity: Documented → Verified → Prevented · effective 8.4 / 10 · rule-coverage 100% · ceiling Prevented

6 over-large unit(s) detected — types, modules or files that carry too much.

FileTooLong: eventsourcing/domain.py · ×6eventsourcing/domain.py

What to do

Resolve the 6 FileTooLong finding(s) in God Classes — start with domain.py, postgres.py, persistence.py. — One of this dimension's main actionable groups (6 warning-level).
Enforce God Classes in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Prevented — provenance only; does not change the score.

Detailed fixes: d3_recommendation.md · top locations in Appendix A, every location in findings.md.

Do you agree with this assessment?

D4 · Code Duplication9.3 / 10Stronggated by 26 serious findings✓ Tool-verified

What it measures: Copy-pasted code that should be shared instead.

Method: Code duplication via token-stream sliding windows with type-aware normalization (locals masked, type names preserved), density-scored per KLoC of production code. Deterministic.

Maturity: Documented → Verified → Prevented · effective 9.3 / 10 · rule-coverage 100% · ceiling Verified

26 duplicated block group(s) detected. 12 of the 26 are in trees this repository does not ship — vendored, example/demo, fixture and benchmark code — and are ranked below the shipped groups rather than excluded from them: the duplication there is real and is still counted in this dimension's score. The dimensions that publish a production-file census leave those trees out of theirs, so this count is deliberately drawn over the wider population.

Duplicated block (20 lines × 2) · ×2eventsourcing/dcb/domain.py:34

Duplicated block (13 lines × 2) · ×2eventsourcing/dcb/postgres_tt.py:669

Duplicated block (12 lines × 2) · ×2eventsourcing/postgres.py:1294

Duplicated block (11 lines × 2) · ×2eventsourcing/domain.py:1735

Duplicated block (10 lines × 2) · ×2eventsourcing/dcb/postgres_tt.py:689

+ 13 more group(s) — more in Appendix A; the complete list is findings.md.

What to do

Resolve the 2 Duplicated block (20 lines × 2) finding(s) in Code Duplication — start with domain.py, system.py. — One of this dimension's main actionable groups (2 warning-level).
Resolve the 2 Duplicated block (13 lines × 2) finding(s) in Code Duplication — start with postgres_tt.py, postgres.py. — One of this dimension's main actionable groups (2 warning-level).
Resolve the 2 Duplicated block (12 lines × 2) finding(s) in Code Duplication — start with postgres.py, system.py. — One of this dimension's main actionable groups (2 warning-level).
Enforce Code Duplication in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Verified — provenance only; does not change the score.

Detailed fixes: d4_recommendation.md · top locations in Appendix A, every location in findings.md.

Do you agree with this assessment?

D6 · Cohesion (LCOM4)9.5 / 10Stronggated by 4 serious findings✓ Tool-verified

What it measures: Whether a class's methods are focused on a single responsibility.

Method: LCOM4 cohesion per production class with at least two methods: connected components of methods sharing state or calls, computed syntactically. Deterministic, not a proxy.

Coverage: Exhaustive · type-level: LCOM4 cohesion computed over every production class — the population is all types, not a name convention.

Maturity: Documented → Verified → Prevented · effective 9.5 / 10 · rule-coverage 100% · ceiling Verified

4 of 98 classes have LCOM4 above 3.

Low cohesion: Application (LCOM4 4) · ×4eventsourcing/application.py:602

What to do

Resolve the 4 Low cohesion finding(s) in Cohesion (LCOM4) — start with application.py (2), postgres.py, sqlite.py. — One of this dimension's main actionable groups (4 warning-level).
Enforce Cohesion (LCOM4) in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Verified — provenance only; does not change the score.

Detailed fixes: d6_recommendation.md · top locations in Appendix A, every location in findings.md.

Do you agree with this assessment?

D9 · Test Distribution10.0 / 10Exemplary✓ Tool-verified

What it measures: Whether the test suite has a healthy mix of unit / integration / end-to-end tests.

Method: Test projects classified (Unit/Integration/BDD/E2E) from compiled metadata; test methods counted exhaustively across projects with placement-agnostic disk fallback. Deterministic.

Maturity: Documented → Verified → Prevented · effective 10.0 / 10 · rule-coverage 100% · ceiling Documented

610 test methods: 610 unit, 0 integration, 0 BDD, 0 e2e. The Python suite contributes 610 test function(s) across 92 file(s) declaring at least one — every `def test…` in a file pytest or unittest would collect, which is those frameworks' own definition of a case; a parametrize table counts once, so this is a floor. Its tier split is read from file names and paths only.

✓ On the Gold path — maintain.

Detailed fixes: d9_recommendation.md.

Do you agree with this assessment?

D11 · Test Reliability10.0 / 10Exemplary✓ Tool-verified

What it measures: Whether the tests pass reliably, with no flakiness.

Method: Suite re-run N times within tiered wall-clock budgets (unit to e2e); tests failing non-deterministically across runs flagged; guarded tests retried when #if guards detected.

Maturity: Documented → Verified → Prevented · effective 10.0 / 10 · rule-coverage 100% · ceiling Verified

0 flaky across 1 measured tier(s). Python (repository root, 100 test files): measured (0 flaky).

✓ On the Gold path — maintain.

Detailed fixes: d11_recommendation.md.

Do you agree with this assessment?

D13 · Secret Scanning10.0 / 10Exemplary○ Nothing flagged

What it measures: Whether any secrets (keys, tokens, passwords) have leaked into the code.

Method: In-process native secret scanner (entropy plus signature patterns) across all tracked files; no external tool. A clean result is a measured 10, not no-data zero. Deterministic.

Maturity: Documented → Verified → Prevented · effective 10.0 / 10 · rule-coverage 100% · ceiling Prevented

Secret scan ran and found no leaked secrets.

✓ On the Gold path — maintain.

Detailed fixes: d13_recommendation.md.

Do you agree with this assessment?

D14 · License Compliance10.0 / 10Exemplary○ Nothing flagged

What it measures: Whether the licenses of third-party packages are compatible with your policy.

Method: Third-party package licenses resolved from declared package metadata and checked against the configured policy (allow/deny/copyleft). Deterministic; clean = no incompatible license found at metadata depth.

Maturity: Documented → Verified → Prevented · effective 10.0 / 10 · rule-coverage 100% · ceiling Verified

0 of 1 shipped Python distribution(s) use a banned license. Licences were resolved from PyPI over the distributions a consumer installs — this repository's 1 declared runtime requirement(s) closed transitively over each distribution's published `requires_dist` (0 reached that way). Requirements it states ONLY under an extra, a PEP 735 dependency group, a Poetry dev group or a dev-named requirements file are excluded: pip does not install any of them for a consumer. ★ This repository commits no dependency lockfile that this pass reads, so each licence is the one PyPI publishes for the distribution's CURRENT release rather than for a pinned version. This repository publishes itself under BSD-3-Clause, which is its own choice and is not judged here.

✓ On the Gold path — maintain.

Detailed fixes: d14_recommendation.md.

Do you agree with this assessment?

D15 · Churn × Complexity Hotspots10.0 / 10Exemplary✓ Tool-verified

What it measures: Files that change often and are also complex — the riskiest hotspots.

Method: Per production file churn times cyclomatic complexity over a rolling window, computed from git and Roslyn/JS/Razor analysis. Exhaustive, deterministic per commit date.

Maturity: Documented → Verified → Prevented · effective 10.0 / 10 · rule-coverage 100% · ceiling Documented

No churn × complexity hotspots in the window.

✓ On the Gold path — maintain.

Detailed fixes: d15_recommendation.md.

Do you agree with this assessment?

D17 · Explicit Debt9.6 / 10Stronggated by 36 serious findings✓ Tool-verified

What it measures: Acknowledged debt left in the code — TODOs, dead code, suppressed warnings.

Method: Roslyn syntactic debt markers (suppressions/TODO/FIXME/HACK/empty-catch/commented-code/Obsolete) plus SymbolFinder dead-code analysis; weighted-debt-per-KLoC density deducted 2.0x per unit. Deterministic, exhaustive.

Maturity: Documented → Verified → Prevented · effective 9.6 / 10 · rule-coverage 100% · ceiling Prevented

36 deducted task-comment markers across 17169 LoC (0.2/KLoC) → score 9.6. Task comments only: this repository's language is read without a compiler, so D17's suppression, dead-code and commented-out-code arms did not run and this score counts fewer marker kinds than a .NET repository's would.

TodoComment · ×36eventsourcing/utils.py:224

What to do

Resolve the 36 TodoComment finding(s) in Explicit Debt — start with domain.py (14), application.py (4), persistence.py (3). — One of this dimension's main actionable groups (36 warning-level).
Enforce Explicit Debt in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Prevented — provenance only; does not change the score.

Detailed fixes: d17_recommendation.md · top locations in Appendix A, every location in findings.md.

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D19 · Documentation QualityStrong◐ Sampled · advisory

What it measures: Whether the project's documentation is clear, complete, and useful.

Method: Judged by language model at low temperature (0.0-0.1) on a deterministic doc sample (READMEs plus first 25 architecture docs), with two-pass stability filtering. Advisory, sampled.

Maturity: Documented → Verified → Prevented · effective Strong / 10 · rule-coverage 100% · ceiling Documented

The repository's root README is a comprehensive overview of the project (event sourcing in Python) with links to docs and releases. The architecture/Docs markdown files are well-organized: one file gives an overview of each module (application, dcb), another lists all topics by outline, and the main topic docs cover installation, synopsis, domain models, examples, interface, modules, persistence, and DCB in depth with clear prose and code blocks. The README is itself a single document that serves as the project's root; its scope is covered by the overview plus the install/usage sections it contains. The repository's documentation is strong: it contains one README file (projection.rst) and four architecture/design docs covering projections, release notes, support, and a tutorial. The projection.rst document is well written with an overview of the module's purpose, a CQRS rationale, and a detailed description of how materialised views are constructed from domain events, plus a concrete ApplicationSubscription example and a clipped outline (Construct an application object; Record an event; ...). Release notes gives full major-version semantics and changelogs for each release. Support covers GitHub stars/sponsor/donations, community channels, training workshops, professional support, and links to the issue tracker. The tutorial is thin but points to part1 through part5. All four architecture docs are present (release_notes.rst, support.rst, system.rst, tutorial.rst) and describe their scope; the README for the projection module is focused on its directory's purpose and usage. This repository's documentation is strong: it contains two README files (Aggregate 5 and Aggregate 6) that each describe their own immutable aggregate base class with code examples for the base classes and a domain model. The architecture/design docs are separate markdown files at a high level; the visible content of the two example Readmes is sufficient to judge them, but the summary does not yet show whether the repository's root README (the one that describes the project as a whole) exists or what it says. Given only the two example Readmes and no architecture docs, I rate this set of documents at 7.

Documentation: contradicts the code · ×3docs/topics/release_notes.rst

What to do

Resolve the 3 Documentation finding(s) in Documentation Quality — start with release_notes.rst, aggregate5.rst, aggregate6.rst. — One of this dimension's main actionable groups (3 recommendation-level).

Detailed fixes: d19_recommendation.md · top locations in Appendix A, every location in findings.md.

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D21 · Naming ConsistencyExemplary◐ Sampled · advisory

What it measures: Whether names — types, methods, variables — are clear and consistent.

Method: Judged by language model at low temperature (0.0-0.1) on a deterministic random symbol sample (fixed size, not exhaustive), with disclosed confidence band. Advisory, sampled.

Maturity: Documented → Verified → Prevented · effective Exemplary / 10 · rule-coverage 100% · ceiling Verified

0 naming inconsistencies across 0 sampled symbols.

✓ On the Gold path — maintain.

Detailed fixes: d21_recommendation.md.

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D22 · Internal API ConsistencyWeak◐ Sampled · advisory

What it measures: Whether the internal API surface is consistent and coherent.

Method: Judged by language model at low temperature over a sample of the public API surface (IsPackable or .Contracts types). Sampled, advisory; confidence discounted by model uncertainty.

Maturity: Documented → Verified → Prevented · effective Weak / 10 · rule-coverage 100% · ceiling Verified

5 API inconsistencies across a 400-member sample of 206 exposed types.

Redundant interface implementation: LRUCache duplicates the exact signature of the abstract Cache interface. While this is technically an implementation, exposing both as top-level public types with identical method signatures suggests a lack of clear abstraction hierarchy or unnecessary duplication in the public surface. · ×2

Duplicate type definition: Two distinct types named AESCipher exist in different modules (cipher vs cryptography) with identical signatures. This creates ambiguity for users importing by name.

Duplicate property access: Two properties (notification_log and log) expose the exact same type (LocalNotificationLog) and likely the same underlying instance. This is confusing for API consumers who must guess which name to use.

Inconsistent naming and duplication: The abstract Cipher interface and the two AESCipher implementations all expose encrypt/decrypt. Combined with the duplicate AESCipher types, this creates a fragmented API for encryption.

What to do

Resolve the 2 Redundant interface implementation finding(s) in Internal API Consistency. — One of this dimension's main actionable groups (2 warning-level).
Resolve the 1 Duplicate type definition finding(s) in Internal API Consistency. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 Duplicate property access finding(s) in Internal API Consistency. — One of this dimension's main actionable groups (1 warning-level).

Detailed fixes: d22_recommendation.md · top locations in Appendix A, every location in findings.md.

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D23 · Boundary Type-Coupling8.3 / 10Strong✓ Tool-verified

What it measures: Whether domain types (IDs, enums, value objects) leak across bounded-context boundaries.

Method: Cross-context domain-type leakage via Roslyn structural classification (strongly-typed IDs / value objects) over every public surface. Exhaustive, deterministic, type-level aggregate-boundary check.

Coverage: Bounded contexts derived from NAMESPACE prefix (or graph-inferred where available); cross-boundary domain-type leakage then checked exhaustively over every public member of every type.

Maturity: Documented → Verified → Prevented · effective 8.3 / 10 · rule-coverage 100% · ceiling Verified

16 domain type(s) cross context boundaries across 2 contexts.

Cross-context type Selector (eventsourcing → examples) · ×10examples/dcb_enrolment_with_vertical_slices/application.py:81

Cross-context type CanInitAggregate (eventsourcing → examples) · ×4examples/aggregate10/mutablemodel.py:79

Cross-context type Aggregate (eventsourcing → examples) · ×2examples/cargoshipping/domainmodel.py:201

What to do

Resolve the 10 Cross-context type Selector (eventsourcing → examples) finding(s) in Boundary Type-Coupling — start with application.py (10). — One of this dimension's main actionable groups (10 warning-level).
Resolve the 4 Cross-context type CanInitAggregate (eventsourcing → examples) finding(s) in Boundary Type-Coupling — start with mutablemodel.py (2), domainmodel.py (2). — One of this dimension's main actionable groups (4 warning-level).
Resolve the 2 Cross-context type Aggregate (eventsourcing → examples) finding(s) in Boundary Type-Coupling — start with domainmodel.py (2). — One of this dimension's main actionable groups (2 warning-level).
Enforce Boundary Type-Coupling in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Verified — provenance only; does not change the score.

Detailed fixes: d23_recommendation.md · top locations in Appendix A, every location in findings.md.

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D26 · Project Cohesion0.0 / 10Critical✓ Tool-verified

What it measures: Whether each project is a focused, coherent unit rather than an oversized grab-bag.

Method: Project size overshoot penalties (LoC / public-type count / namespace count, 2-of-3 flag) weighted by log magnitude. Exhaustive across projects, deterministic, LLM-independent.

Maturity: Documented → Verified → Prevented · effective 0.0 / 10 · rule-coverage 100% · ceiling Documented

1 of 1 build units (Python) flagged as possibly oversized/incoherent.

Projects may be oversized for their cohesion

What to do

Resolve the 1 Projects may be oversized for their cohesion finding(s) in Project Cohesion. — One of this dimension's main actionable groups (1 recommendation-level).

Detailed fixes: d26_recommendation.md · top locations in Appendix A, every location in findings.md.

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D28 · Secrets (history)10.0 / 10Exemplary○ Nothing flagged

What it measures: Whether any secrets were ever committed — scanned across the full git history, not just now.

Method: Secret scan via TWO gitleaks detect passes in an isolated checkout — the full git history, then a second --no-git pass over the working tree as it stands — merged and de-duplicated by (rule, file, line); each match flagged High. Both invocations are recorded in the audit trail. Exhaustive; when the tool is absent, or when its output cannot be parsed into the expected shape, the dimension is WITHHELD as an explicit measurement gap on our side — unscored and excluded from the lens, never a hedged middling score.

Maturity: Documented → Verified → Prevented · effective 10.0 / 10 · rule-coverage 100% · ceiling Documented

gitleaks scanned the full history AND the current working tree and found no secrets.

✓ On the Gold path — maintain.

Detailed fixes: d28_recommendation.md.

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D29 · Static Analysis (SAST)6.7 / 10Adequate✓ Tool-verified

What it measures: Real static-analysis (SAST) findings — likely security bugs in the code, any language.

Method: Polyglot static analysis via semgrep across the repo using the pinned, image-baked p/security-audit + p/owasp-top-ten rulesets (no scan-time registry fetch); severity rules (ERROR/WARNING/INFO) map to a full-band severity-weighted score. Exhaustive, deterministic; degrades on parse failure.

Coverage: semgrep pattern rules over all files — exhaustive for the rule set, blind to classes of bug without a rule (clean = no rule matched).

Maturity: Documented → Verified → Prevented · effective 6.7 / 10 · rule-coverage 100% · ceiling Documented

7 finding(s): 0 critical, 6 high, 1 medium, 0 low. 4 unpinned-GitHub-Actions row(s) are reported here but scored by D36 (supply-chain provenance), which measures that posture as `pinned_actions` — one pinning decision is charged once, not once per lens.

REDACTED

What to do

Resolve the 1 REDACTED finding(s) in Static Analysis (SAST) — start with REDACTED. — One of this dimension's main actionable groups (1 issue-level).
Resolve the 1 REDACTED finding(s) in Static Analysis (SAST) — start with REDACTED. — One of this dimension's main actionable groups (1 issue-level).
No action in Static Analysis (SAST) — all 4 REDACTED finding(s) are reported here at file:line but scored by D36 (supply-chain provenance), so none is charged to this dimension. — One of this dimension's main actionable groups (4 issue-level, 0 of them charged here).

Detailed fixes: d29_recommendation.md · top locations in Appendix A, every location in findings.md.

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D30 · Dependency Vulnerabilities7.5 / 10Adequategated by 3 critical findings✓ Tool-verified

What it measures: Whether any dependency has a known published vulnerability (CVE), direct or transitive, in ANY ecosystem the repository declares — Dart pub, Elixir and Erlang via Hex, Go modules, Java and Kotlin via Maven/Gradle, JavaScript/npm, .NET/NuGet, PHP/Composer, Python/PyPI, RubyGems, Rust/Cargo and Swift.

Method: Dependency-CVE scan across every ecosystem the repository declares, scored ONCE. Three sources are unioned and deduplicated by advisory identity (rule id + alias closure, CVE<->GHSA) scoped to package+version, keeping the worst severity: `osv-scanner --recursive` over osv.dev for Dart pub, Elixir/Hex (and Erlang, whose `rebar.lock` syft first converts to a CycloneDX SBOM the scanner reads, with rows attributed back to the lock), Go, Java and Kotlin via Maven/Gradle (and Scala, whose sbt build's pinned direct declarations are written into a CycloneDX SBOM the scanner reads, with rows attributed back to the build file), npm, PHP/Composer, Python/PyPI, RubyGems, Rust/Cargo and Swift; `trivy fs --scanners vuln` for npm lockfiles; and `dotnet list package --vulnerable --include-transitive` for NuGet (with per-advisory collapse of the project x target-framework fan-out), plus a DECLARED-dependency arm that resolves a published gem's gemspec against rubygems.org where no Gemfile.lock is committed. `SeverityScore(c,h,m,l, normalizer 8.0)`. NotApplicable only when NO ecosystem is readable; if any applicable ecosystem could not be scanned the findings are REPORTED and the score is withheld. Supersedes the npm and OSV arms, retired 2026-09-05.

Maturity: Documented → Verified → Prevented · effective 7.5 / 10 · rule-coverage 100% · ceiling Documented

3 finding(s): 1 critical, 2 high, 0 medium, 0 low.

REDACTED

What to do

Resolve the 2 High CVE finding(s) in Dependency Vulnerabilities — start with REDACTED (2). — One of this dimension's main actionable groups (2 issue-level).
Resolve the 1 Critical vulnerability finding(s) in Dependency Vulnerabilities — start with REDACTED. — One of this dimension's main actionable groups (1 issue-level).

Detailed fixes: d30_recommendation.md · top locations in Appendix A, every location in findings.md.

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D31 · IaC & Container Security8.2 / 10Adequategated by 5 critical findings✓ Tool-verified

What it measures: Whether Dockerfiles / Terraform / Kubernetes config follow security best practices.

Method: IaC/container misconfiguration scan via trivy config (Dockerfile/Terraform/K8s/Helm/CloudFormation); severity rules to 0-10 moderate normalizer. NotApplicable without manifests. Exhaustive, deterministic.

Maturity: Documented → Verified → Prevented · effective 8.2 / 10 · rule-coverage 100% · ceiling Documented

6 finding(s): 0 critical, 5 high, 1 medium, 0 low.

REDACTED

What to do

Resolve the 5 High IaC finding(s) in IaC & Container Security — start with REDACTED (5). — One of this dimension's main actionable groups (5 issue-level).
Resolve the 1 Medium IaC finding(s) in IaC & Container Security — start with REDACTED. — One of this dimension's main actionable groups (1 warning-level).

Detailed fixes: d31_recommendation.md · top locations in Appendix A, every location in findings.md.

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D34 · Knowledge Freshness10.0 / 10Exemplary✓ Tool-verified

What it measures: Whether anyone still has living knowledge of each file, or it has been orphaned — last understood long ago by someone now gone quiet. The sibling of the bus factor: D16 asks who owns it, D34 asks whether anyone still knows it.

Method: File orphaning as total living-knowledge decay below one focused-commit's worth within a year, computed per-file from the D16 decay model. Exhaustive, deterministic over fixed history.

Maturity: Documented → Verified → Prevented · effective 10.0 / 10 · rule-coverage 100% · ceiling Documented

Every significant source file has living knowledge — recently and meaningfully worked. Counted over 21 of the 28 production source files in this repository: the rest are under the ~2,400-byte size floor this dimension measures over.

✓ On the Gold path — maintain.

Detailed fixes: d34_recommendation.md.

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D35 · Change Coupling9.8 / 10Stronggated by 1 serious finding✓ Tool-verified

What it measures: Whether files that change together actually belong together — pairs that repeatedly co-change in git history despite having no explicit code dependency, surfacing the hidden/logical coupling (and boundaries in the wrong place) a static scan can't see.

Method: Pairwise co-occurrence over the per-commit file sets in git history (production source only — tests and generated dropped): Degree-of-Coupling = shared ÷ min individual revisions, reported above noise floors (each file ≥10 revisions, ≥5 shared commits, ≥50% strength); sweeping commits excluded. Deterministic over fixed history.

Coverage: Population: PRODUCTION source files only — test and generated files are dropped before pairing, so a class co-changing with its own test (trivially ~100%) can't drown the real production↔production coupling. Pairs ranked by Degree-of-Coupling. A non-source file is never a coupling PARTICIPANT either: documentation, schemas, config and data files are dropped with the rest, so a code↔docs pair — a command and the reference page that restates it — is not reported however strongly the two co-change; nor is coupling that runs THROUGH a build step or config file.

Maturity: Documented → Verified → Prevented · effective 9.8 / 10 · rule-coverage 100% · ceiling Documented

Strongest change-coupling: prepare-distribution.py↔test-released-distribution.py 71%; prepare-distribution.py↔release-distribution.py 70%; release-distribution.py↔test-released-distribution.py 50%

Change coupling clique: prepare-distribution.py, release-distribution.py, test-released-distribution.pydev/prepare-distribution.py

What to do

Resolve the 1 Change coupling clique finding(s) in Change Coupling — start with prepare-distribution.py. — One of this dimension's main actionable groups (1 warning-level).

Detailed fixes: d35_recommendation.md · top locations in Appendix A, every location in findings.md.

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D43 · Malicious Dependencies10.0 / 10Exemplary✓ Tool-verified

What it measures: Whether any dependency the repository declares is published as MALICIOUS rather than merely vulnerable — a package that is an attacker's work, in any ecosystem osv-scanner reads. Scored apart from D30 because the answer is binary: there is no safe version to upgrade to, and the fix is to remove the package and rotate every credential it could have read.

Method: The same dependency scan D30 reads, partitioned on the scanner's own classification rather than rescanned: a row is MALICIOUS when its id is in the `MAL-` space (the ossf/malicious-packages feed) OR its `database_specific.cwe_ids` carries `CWE-506` ("Embedded Malicious Code"). Both channels are structural; the summary text is deliberately NOT read, because a malicious-package record whose summary says only "Critical severity vulnerability" is a real shape ([GHSA redacted]) and a text matcher misses it. Scored BINARY: any surviving row is 0, whatever its severity and however many CVEs sit beside it — a hostile dependency is not a quantity. Applicability and degradation are D30's: NotApplicable only when no ecosystem is readable, and an unscannable ecosystem degrades rather than reading clean. SCORED, not informational.

Maturity: Documented → Verified → Prevented · effective 10.0 / 10 · rule-coverage 100% · ceiling Documented

No dependency in any ecosystem this repository declares is published as malicious.

✓ On the Gold path — maintain.

Detailed fixes: d43_recommendation.md.

Do you agree with this assessment?

D44 · Platform End-of-Life10.0 / 10Exemplary✓ Tool-verified

What it measures: Whether anyone still ships security patches for the platform this repository RUNS ON — the runtime it pins and the framework majors its own constraints hold it to. Separate from D12 because the question differs: a current Django on an end-of-life Python is perfectly up to date and completely unsupported, and the fix is a migration rather than a version bump. What the repository says it merely SUPPORTS is never charged.

Method: End-of-life PLATFORM read from the repository's own declarations and graded against a FROZEN, dated table of vendor support dates — no network, no feed, no API, so this dimension answers identically inside a closed scan fence. Two subjects: a RUNTIME the project pins (a single or all-end-of-life TargetFramework, a .nvmrc or .python-version, a requires-python CAP) and a FRAMEWORK major a dependency constraint cannot move off (a caret, tilde or exact version; `vue@^2.7.16` pins Vue 2). A FLOOR is deliberately never charged — `requires-python = ">=3.8"` states what a package SUPPORTS, not what it runs on — and a multi-target project is charged only when EVERY target is out of support. Runtime 4.0/product capped 8.0, framework 1.5 capped 4.5. The table is safe to freeze because a statement about support that ended in the past cannot become false: it loses recall as it ages, never precision, and a test asserts every entry predates the freeze date. Disjoint from D31 (a container image's OS layer) and D29 (the toolchain a CI workflow installs). Abstains when the repository declares no platform this pass reads — never scores it clean.

Maturity: Documented → Verified → Prevented · effective 10.0 / 10 · rule-coverage 100% · ceiling Documented

0 end-of-life runtime(s) and 0 end-of-life framework(s), read from 1 platform declaration(s) and 1 dependency declaration(s). This dimension reads what the repository says about ITSELF — a pinned target framework, a version file, a capped requires-python, a Rust toolchain pin, a framework major a constraint cannot move off. A FLOOR is deliberately never charged: `requires-python = ">=3.8"` states what the package SUPPORTS, not what it runs on, and a well-maintained library declares exactly that while running its own CI on a current release. The end-of-life facts are FROZEN and dated, so this dimension needs no network and answers identically inside a closed scan fence; as the table ages it loses recall and never precision, because a statement about support that ended in the past cannot become false. The OS layer of a container image is D31's question and the toolchain a CI workflow installs is D29's; this row is neither.

✓ On the Gold path — maintain.

Detailed fixes: d44_recommendation.md.

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Frontend & cross-cutting dimensions

R = React/JS · M = Maturity · P = Readiness.

AX10 · Code composition9.0 / 10Exemplary✓ Tool-verified

Other · Architecture — How the codebase splits by code ROLE — domain, application, infrastructure, test, generated. The significance map behind the knowledge/coupling weighting, and a DDD signal in its own right: a thin domain core under fat infrastructure is the anemic-domain smell, quantified. How each file's role is decided, because the split is only as good as that: a generated name or a build-output tree makes it Generated, a test project makes it Test, and otherwise the file's NAMESPACE and PATH words are matched against fixed vocabularies in a fixed ORDER — domain, then infrastructure, then application — so a file whose words hit two layers is counted under the earlier one. A production file matching none of them counts as application, so that share reads 'application or unclassified' rather than a measured application layer. Roles come from naming convention, never from what the code does. On this repository the split was taken from the source tree on disk rather than from a loaded .NET workspace, so a file's role is decided by its PATH segments alone — no declared namespace was available to add to the evidence — and generated output is excluded from the census entirely rather than counted as a generated share.

Method: Roslyn line-count by code ROLE: every source file classified Domain/Application/Infrastructure/Test/Generated by namespace + path convention (the shared CodeRoleClassifier), then significant lines summed per role. Deterministic; the advisory score is the business-logic (domain+application) share of production code.

Coverage: Population: ALL source files, each bucketed into ONE of five roles (Domain/Application/Infrastructure/Test/Generated) by namespace + path convention — a file whose layer isn't named in the convention falls to Application (the neutral default), and the split is line-count, not semantic depth or business value.

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AX3 · Project dependency cycles10.0 / 10Exemplary✓ Tool-verified

Other · Architecture — Whether the project-reference graph is acyclic (cycles block independent build/deploy and signal eroding boundaries).

Method: Project reference cycles via elementary-DFS over real .csproj references, using the engine shared with D5/D7; cyclic versus acyclic. Exhaustive, deterministic.

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AX4 · Dependency direction10.0 / 10Exemplary✓ Tool-verified

Other · Architecture — Whether dependencies point inward (Domain ← Application ← Infrastructure/Web) — the clean-architecture dependency rule, checked across the project graph.

Method: Layer violations by name-segment inference (Domain/Core to Application to Infrastructure/Web) over the project-reference graph. Exhaustive over all projects, deterministic.

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AX5 · Architecture & structure10.0 / 10Exemplary✓ Tool-verified

Other · Architecture — Whether the codebase has a recognisable, scale-appropriate structure (a named architectural style, or modular enough for its size) rather than being an ad-hoc ball of mud.

Method: Roslyn plus csproj analysis: architecture style detection (DDD, clean, vertical-slice, CQRS) and structure fitness for repo size. Deterministic.

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M1 · Documentation (README)6.7 / 10Adequate✓ Tool-verified

Maturity · Maturity — Whether the repo and its projects have a README, and whether it's substantive and current.

Method: Filesystem scan: README presence, word count, and headings for depth; git history for staleness. Exhaustive across root and project dirs, deterministic.

What to do

Explain in the README how to run the tests. Add a section called Testing to the README in the repository's top folder, saying how to run the test suite.
Add an 'Architecture' / 'How it works' section to the root README — the high-level shape.

Do you agree with this assessment?

M2 · Architecture documentation2.0 / 10Critical✓ Tool-verified

Maturity · Maturity — Whether key decisions (ADRs) and the high-level shape (C4/diagrams) are written down.

Method: Filesystem scan: ADR folder/naming conventions or content, plus Mermaid/PlantUML/C4/architecture.md discovery. Exhaustive, deterministic.

No Architecture Decision Records found — no conventional ADR directory, no numbered `NNNN-title` documents in any markup this check reads, and nothing ADR-shaped by content. Design rationale recorded elsewhere (a design-notes tree, a mailing list, pull-request discussion) is not visible to this check and is not re-findable per decision, so a future maintainer cannot ask why one choice was made and get an answer.

What to do

Record your significant design decisions. Write one short document per decision, giving its date, the situation, the decision and its consequences, and keep them together with your other design documents. A docs/adr folder with each file named by number and title is the easiest place to find them.

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M3 · Folder & project structure8.0 / 10Strong✓ Tool-verified

Maturity · Maturity — Whether the repo is organised deliberately — src/test separation and consistent project naming.

Method: Filesystem scan: src/test folder separation and namespace-prefix consistency (majority RootNamespace agreement). Exhaustive across projects, deterministic.

Production code isn't grouped under a src/ folder — it's spread across several top-level directories, so there's no one place that says 'this is the product'.

What to do

Group production code under src/ (or split deliberately, e.g. backend/ + frontend/) so production and tooling code aren't mixed at the root.

Do you agree with this assessment?

M4 · Documentation accuracy8.0 / 10Strong◐ Sampled · advisory

Maturity · Maturity — Whether the README actually describes the code that exists (LLM-judged, advisory).

Method: Judged by language model at low temperature: README accuracy versus actual projects, within a disclosed tolerance. Advisory, not a measured number.

docs/topics/persistence.rst links to `transcoder=transcoder`, but `docs/topics/transcoder=transcoder` does not exist. Checked without a model against the repository: its files and folders, the scripts and dependencies of every package.json, the projects, namespaces, package references and target frameworks of the .NET build, the SDK and Node pins, and the identifiers of every file that is not a document; the documents' own text never counts. A footprint generated at build time, read only by a platform, or living outside this repository is not seen, and this row is then wrong. — docs/topics/persistence.rst:521

What to do

Reconcile the README with reality: docs/topics/persistence.rst links to `transcoder=transcoder`, but `docs/topics/transcoder=transcoder` does not exist.

Do you agree with this assessment?

P1 · CI/CD gates10.0 / 10Exemplary○ Nothing flagged

Readiness · Readiness — Whether an automated pipeline builds and tests every change.

Method: Filesystem scan: CI workflow files (.github/workflows, .gitlab-ci.yml, etc.) for build and test stages. Exhaustive, deterministic.

Do you agree with this assessment?

P10 · Library API & versioning10.0 / 10Exemplary○ Nothing flagged

Readiness · Readiness — For a library: a deliberate (small) public API surface and explicit semantic versioning so consumers can depend on it safely.

Method: Roslyn scan: public API surface area and semantic-versioning markers (SemVer attributes, changelog entries) for libraries; off .NET, a library is the ecosystem's publication act (an npm package that is not private and names an entry point, a PyPI distribution with a build system, a Rust library crate, a Maven/Gradle module that publishes, a Go module with no package main, a gemspec, a Composer library, a SwiftPM library product, a pub.dev or Hex package), its surface is the share of types the language model records as public (Rust, Swift, Java, Kotlin, Go, Dart; not measured where the model records no type visibility or, as in TypeScript, only module-level export), and its version is read from the manifest, a semver CHANGELOG, release tooling or semver git tags. Exhaustive, deterministic.

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P2 · Observability7.0 / 10Strong✓ Tool-verified

Readiness · Readiness — Whether the code is diagnosable in production — structured logging, tracing/metrics, health checks.

Method: Filesystem/Roslyn scan: structured-logging frameworks (Serilog, NLog), OpenTelemetry, and health-check endpoint patterns. Exhaustive, deterministic.

What to do

Consider OpenTelemetry tracing/metrics (opentelemetry-sdk) and a health-check endpoint (a /health route) for operability.

Do you agree with this assessment?

P3 · Security & performance tooling1.0 / 10Critical✓ Tool-verified

Readiness · Readiness — Whether SAST, secret/dependency scanning and performance benchmarking are wired in (presence, not runtime).

Method: Filesystem scan: SAST configuration, dependency-update automation, secret scanning, and a benchmark harness or benchmark step — in this repository's own ecosystem. Exhaustive, deterministic.

No static application security testing detected. For this repository's stack, add bandit, `semgrep --config=p/python`, or CodeQL's python pack as a CI step. What was searched, so you can tell an absence from a miss: the 3820 CI workflow file(s) in this repository, and the scanner and linter configuration checked in beside them. A scan that runs outside CI, one configured in your forge's web UI rather than in a committed file, or a tool whose name is none of those this check carries, is not seen — if that is your case the row is wrong, and saying so is more useful than adding a second scanner.

What to do

Add a SAST step to CI running what this repository's stack ships: bandit, `semgrep --config=p/python`, or CodeQL's python pack — so a security regression fails the build instead of landing.
Enable Dependabot/Renovate or a dependency-review gate.
Add gitleaks/trufflehog in CI to block PRs that introduce committed secrets.

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P4 · Deployment & Rollback5.0 / 10Adequate✓ Tool-verified

Readiness · Readiness — Whether releases are automated and safely reversible (probes, rolling updates, approval gates) — from manifests/pipeline files, not the live environment.

Method: Filesystem scan: deployment manifests/IaC (K8s YAML, Helm, Terraform) for rolling updates, probes, approval gates, migration hooks. Exhaustive, deterministic.

Deployment is orchestrated by compose, but no service declares a `healthcheck:` and nothing pins a previous image to fall back to — the runtime can tell that the container is up, not that it is serving, so a bad release is harder to detect and reverse.

What to do

Add a `healthcheck:` to the served compose service — probing the endpoint it already answers on where it has one — with `depends_on: condition: service_healthy` on whatever waits for it, and keep the deployed image tag immutable and recorded so rolling back is re-pointing at the previous tag rather than rebuilding.
Add an approval/environment gate (required reviewers / protection rules) before production promotion.

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P5 · DR & Backup0.0 / 10Critical✓ Tool-verified

Readiness · Readiness — Whether disaster recovery is planned and codified — backups, geo-recovery, RTO/RPO, persistence guarantees — from IaC + container manifests + docs, never the live cloud.

Method: Filesystem scan: disaster recovery, backup, geo-recovery, RTO/RPO, persistence guarantees from IaC, manifests, and docs. Exhaustive, deterministic, never a live environment.

A persistence guard (data volume / purge-protection) was found, but no backup, geo-recovery or RTO/RPO controls were evidenced — a volume that survives a container recreate is not a tested restore from catastrophic loss.

What to do

Codify backups + geo-recovery in IaC and document RTO/RPO and the restore procedure — a persistence guard alone is not disaster recovery.

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P6 · Release Hygiene10.0 / 10Exemplary✓ Tool-verified

Readiness · Readiness — Whether releases are traceable — a maintained changelog and explicit version stamping.

Method: Filesystem scan: changelog file presence and version tags in csproj or git tags. Exhaustive, deterministic.

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PF1 · Benchmark discipline9.0 / 10Exemplary✓ Tool-verified

Readiness · Performance — Whether the code protects its performance with benchmarks — a benchmark suite, allocation/memory measurement, and (ideally) a CI gate. Presence is credited as a bonus, never a deduction.

Method: Repo + source scan: BenchmarkDotNet referenced (csproj/source), [Benchmark]/[MemoryDiagnoser] attribute counts, and a benchmark step in CI; off .NET, the same ladder over Go testing.B, Rust criterion/#[bench]/divan, JMH/kotlinx-benchmark, pytest-benchmark/asv/pyperf, tinybench/mitata/vitest bench/benchmark.js and Swift package-benchmark — scored as a bonus ladder (absence is neutral, never a deduction). Deterministic, presence detection.

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X1 · Async correctness10.0 / 10Exemplary○ Nothing flagged

Other · Code Health — Whether the code avoids sync-over-async (deadlock-prone blocking on tasks) and async void.

Method: Roslyn syntax scan: async methods scanned for .Wait()/.GetAwaiter().GetResult() and async-void outside event handlers. Deterministic, hard fact per invocation.

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X12 · Unreachable branch10.0 / 10Exemplary○ Nothing flagged

Other · Code Health — Whether any branch is dead by construction — a switch arm whose label can never equal a case-normalised subject, or an `else if` whose predicate the arm above has already swallowed.

Method: Roslyn syntax + semantics: switch labels compared against the subject's own case normaliser, and if/else-if chains checked for a literal an earlier arm's containment test already swallows. Deterministic, provable per finding. Advisory.

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X13 · Undrained process stream10.0 / 10Exemplary○ Nothing flagged

Other · Code Health — Whether a child process that has BOTH standard streams redirected drains both — reading one to the end while the other is never read deadlocks once the child fills the unread pipe.

Method: Roslyn syntax + semantics: ProcessStartInfo launches with both streams redirected, checked for a drain of each stream across the enclosing type. On a repository with no .NET source it reads JavaScript/TypeScript off the engine’s own token stream (test, vendored and minified paths not) with the same rule: a `spawn` imported from `child_process` whose stdout and stderr are both pipes (no options, no `stdio`, or `stdio` of `'pipe'`), bound to a local that never leaves its scope, where exactly one of the two streams is read, the other never, and the child’s `close`/`exit` (or the read stream’s end) is awaited; a shell redirect in the call’s arguments or a `kill` of the child suppresses it. The same rule reads Python’s `subprocess.Popen`, Dart’s `Process.start`, Ruby’s `Open3.popen3`, and Scala’s JDK process starts (`new ProcessBuilder(…).start()` with no `redirectErrorStream`/`redirectError`/`redirectOutput`/`inheritIO`, `Runtime.getRuntime.exec`) where one of `getInputStream`/`getErrorStream` is read and the other never while `waitFor()` is called or the read stream is read to its end. Deterministic, provable per finding. Advisory.

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X14 · Bypassable address classification10.0 / 10Exemplary○ Nothing flagged

Other · Security — Whether a hand-rolled public/private IP check can be walked past — a method that unwraps IPv4-mapped IPv6 but returns the opposite verdict for the same host written as IPv4-compatible, 6to4 or NAT64.

Method: Roslyn syntax + semantics: methods that unwrap IPv4-mapped IPv6 and hand-roll IPv4 range carve-outs, checked for whether the IPv6 branch also accounts for the IPv4-compatible, 6to4 and NAT64 embeddings. Deterministic, provable per finding. Advisory.

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X15 · Unvalidated length from an untrusted reader10.0 / 10Exemplary○ Nothing flagged

Other · Security — Whether a length read out of the stream being parsed is bounded before it is allocated or read — an unchecked count taken from the input lets the input choose the allocation.

Method: Roslyn syntax + semantics: integer lengths read from a BinaryReader and spent on a bulk read or an array allocation, checked for any comparison or bounding call on the value anywhere in the method. Deterministic, provable per finding. Advisory.

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X17 · Uncapped recursion over a caller-supplied document10.0 / 10Exemplary○ Nothing flagged

Other · Security — Whether a walk that recurses through a JSON/XML tree handed in by its caller bounds how deep it will go — an uncapped walk lets the document's nesting choose the stack depth, and the resulting StackOverflowException cannot be caught.

Method: Roslyn syntax + semantics: methods that take a JSON/XML document node and call themselves with a child of it, reachable from an externally-callable member of the same type that accepts a document, checked for any depth parameter, descent counter or threaded arithmetic anywhere in the walk. On a repository with no .NET source it reads TypeScript off the engine’s own token stream (test, vendored, generated and minified paths and `.d.ts` not) with the same rule: a function or method with a parameter typed as a document value — `unknown`, `any`, `object`, `Record<string, unknown|any>`, a JSON alias (`JsonValue`, `JSONObject`, …) or a DOM node global the file does not rebind — that calls itself (bare, or through `this` for a method, or hands itself to a call over the value as in `value.map(walk)`) with something it took out of that value and never through an ancestor accessor such as `closest()` or `parentElement`, that is exported or reached from an exported function (a public method of the same exported class) taking such a value, and that names no depth, level, nesting, recursion, remaining or budget anywhere and threads no `+`/`-` arithmetic through a self-call. Plain JavaScript is not read: with no annotation nothing tells a parsed document from a tree the code built itself. Deterministic, provable per finding. Advisory.

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X19 · Unrestored process-global state10.0 / 10Exemplary○ Nothing flagged

Other · Code Health — Whether a method that temporarily changes state belonging to the whole process — the working directory, an environment variable — puts it back on EVERY path: a restore reached only when nothing throws leaks the change to the rest of the process.

Method: Roslyn syntax + semantics: method bodies that write the process working directory or an environment variable and write it back in the same body, checked for whether that restore sits in a `finally`/`catch` or only on the straight-line path. On a repository with no .NET source the same rule reads production JavaScript/TypeScript off the engine’s own token stream (test, vendored and minified paths not): `process.chdir`, `process.env.NAME =`/`["NAME"] =` and `delete process.env.NAME`, and Deno’s `Deno.chdir`/`Deno.env.set`/`Deno.env.delete`, paired per function body (a nested function or arrow is its own body, and module top-level code is none), where the last write puts back a local the body captured from the same global or deletes a variable the first write set, with at least one statement between them; a write in a `catch`/`finally` of that body silences it. Deterministic, provable per finding. Advisory.

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X21 · Side-effecting pattern guard10.0 / 10Exemplary○ Nothing flagged

Other · Code Health — Whether a `when` guard is free of side effects — a guard that increments a counter or assigns while deciding whether its arm matches applies that change during PATTERN MATCHING, on an arm that may not be selected, and skips it entirely when a short-circuit to its left answers first.

Method: Roslyn syntax: `when` guards on case labels and switch-expression arms, read for a mutation (`++`/`--`/assignment) sitting in a position the guard's own `&&`/`||`/`??`/`?:`/`?.` can skip. Deterministic, provable per finding. Advisory.

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X22 · Contradicted release guard10.0 / 10Exemplary○ Nothing flagged

Other · Code Health — Whether a method that TAKES a lock or semaphore and gives it back from a flag-guarded `finally` returns the value that flag implies — reporting success while the guard hands the primitive back admits a second caller the exclusion was there to keep out, and reporting failure while the guard keeps it leaves nothing to ever give it back.

Method: Roslyn syntax: `try` statements whose `finally` releases a synchronisation primitive under a bare local-bool guard, where the method also TOOK that same primitive before the `try`, checked for a `return` of a bool literal whose value disagrees with the flag state the method's own straight-line assignments put it in. Deterministic, provable per finding. Advisory.

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X23 · Unguarded diagnostic materialisation10.0 / 10Exemplary○ Nothing flagged

Other · Code Health — Whether the work a diagnostic log line costs is paid only when that line is wanted — C# evaluates a call's arguments BEFORE the call, so a trace/debug message joined or projected out of a collection is built in full on every pass, and then discarded by a sink the shipped configuration leaves switched off.

Method: Roslyn syntax: log calls at a diagnostic level (a `Log`-prefixed method naming Trace/Debug/Verbose, or a bare `Debug`/`Trace`/`Verbose` on a receiver named for a logger), whose argument list is read for a call whose cost scales with a sequence — a LINQ operator, a materialisation, `string.Join`, a serializer — with no enclosing level check or conditional-compilation region. On a repository with no .NET source it reads JavaScript/TypeScript off the engine’s own token stream (test, vendored and minified paths not) with the same rule: a `debug`/`trace`/`verbose` call on a receiver named for a logger, or a `log`-prefixed method naming the level, whose argument calls an array operator (`map`/`filter`/`reduce`/`sort`/…), `Array.from`, `Object.keys/values/entries`, `JSON.stringify`/`util.inspect` over anything but a literal, or an array `join` — outside any arrow or function passed as an argument, which the logger calls only when the level is on — with no enclosing `if`, `&&` or `?:` whose condition names a level, a level string, or the `NODE_ENV`/`__DEV__`/`DEV` build switch. Deterministic, provable per finding. Advisory.

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X24 · Document value interpolated into markup unescaped10.0 / 10Exemplary○ Nothing flagged

Other · Security — Whether text read out of the document being converted is escaped before it is written into generated markup — a value the document's author chose, interpolated into an attribute the surrounding literal delimits, can close that attribute and open another.

Method: Roslyn semantic model over the whole compilation: a string-typed `Value`/`InnerText`/`InnerXml`/`Text` member declared inside `DocumentFormat.OpenXml` or `System.Xml` is a taint SOURCE, propagated through assignments, returns, arguments, tuple elements and string composition to its transitive closure, then read at interpolated-string holes that sit in a markup position the surrounding literal itself delimits. Escaper/encoder calls and enclosing validator conditions cut the flow. Flow- and container-insensitive by construction. A second arm needs no provenance at all and reports a type that CONTRADICTS ITSELF — the same expression escaped at one delimited markup hole and interpolated raw at another hole in the same markup position of the same type, which the type's own escaping proves is a defect without knowing where the value came from. On a repository with no .NET source it reads JavaScript/TypeScript off the token stream with the same rule: a DOM read of raw document text (`getAttribute`, `textContent`, `innerText`, `nodeValue`) is the source, propagated through local bindings and string composition, and judged at template-literal and concatenation holes in the same two delimited markup positions; escapers and validating conditions cut it, and documentation-site, test, vendored and minified scripts are not read. Deterministic, provable per finding. Advisory.

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X25 · Inert configuration knob10.0 / 10Exemplary○ Nothing flagged

Other · Code Health — Whether a value the caller is invited to supply is the value the type actually uses — a constructor parameter stored in a private field that nothing ever reads while the default it was given is spelled out a second time at the site that should have read it, a keyed lookup that falls back to a different setting than the one its key names while the same type falls back to the matching one for that same key, or a culture-sensitive parse given no format provider by a type that feeds its own settable culture to the same kind of parse elsewhere, or a number an entry point writes to standard output under the host's culture while the same entry point formats with the invariant culture elsewhere. Either way, every caller who supplies a value silently gets something else.

Method: Roslyn syntax: private instance fields of a non-partial type assigned in a constructor from one of its own parameters with a `??` fallback, checked for whether anything in the type body reads the field and whether that same fallback expression is spelled out again outside the constructor; and `??` fallbacks onto a member access from a lookup call carrying exactly one string literal, grouped by that key across the type and checked for a fallback member whose folded name disagrees with the key while a sibling site for the same key agrees with it. On a repository with no .NET source the first two arms read JavaScript/TypeScript off the engine’s own token stream (tests included, bundles and vendored paths not): a `#x`, `private` or `private` parameter-property instance field filled in the constructor from a parameter (or one member of one) through `??`/`||` or a parameter default, never read anywhere in the file by name, whose constructed default is spelled again in the class body; and `lookup("key") ?? s.member` grouped by key per class, or per module outside every class. The culture arm has no JavaScript counterpart: its parses take no locale. Deterministic, provable per finding. Advisory.

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X26 · Unsynchronised callback handoff10.0 / 10Exemplary○ Nothing flagged

Other · Code Health — Whether a value handed from a callback to the body that waits on it crosses on something built to be crossed — a `Queue<T>`/`List<T>`/`Dictionary<K,V>` written inside an event handler and read back outside it is mutated by two flows at once, and the semaphore or completion source beside it orders how MANY items exist while leaving the collection's own head, tail and backing array unprotected.

Method: Roslyn syntax: method, accessor, local-function and lambda bodies that declare BOTH a non-thread-safe generic collection (`Queue`/`Stack`/`List`/`Dictionary`/`HashSet`/`Sorted*`/`LinkedList`) and a synchronisation primitive (`SemaphoreSlim`/`TaskCompletionSource`/`ManualResetEvent(Slim)`/`AutoResetEvent`/`CountdownEvent`) as locals, then read for a `+=`-registered lambda that raises that primitive while the body outside every lambda waits on it — and, in that scope, a mutating call on the collection inside the lambda paired with a mention of it outside. Any `lock` in the scope abstains it. On a repository with no .NET source the same handoff is read in Java off the engine’s own token stream (test source sets, vendored and demonstration paths not): an `ArrayList`/`LinkedList`/`ArrayDeque`/`PriorityQueue`/`Hash*`/`LinkedHash*`/`Tree*` local and a `CountDownLatch`/`Semaphore`/`CompletableFuture` local, a lambda or anonymous class that raises the primitive and mutates the collection, and a wait outside it; any `synchronized` or `lock()` abstains the body. Because each of those primitives orders what the callback wrote before raising it, only a touch that provably overlaps the callback is convicted: one after the registration and before the next wait, or one in a loop registered-before, waiting on every pass and not declaring the collection. Deterministic, provable per finding. Advisory.

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X27 · Collection changed while being enumerated10.0 / 10Exemplary○ Nothing flagged

Other · Code Health — Whether a `for` loop leaves the `dict`, `set` or `deque` it is walking alone — CPython's iterators over those check that the collection has not changed size since the loop began, so a body that removes from (or empties) the very collection the loop is walking makes the next step raise `RuntimeError: dictionary changed size during iteration` and the remaining items are never seen.

Method: Roslyn syntax + semantics: `foreach` statements whose body calls a structural mutator (`Add`/`Remove`/`Clear`/`Insert`/…) on the very expression the loop is enumerating. Two arms. ARM A — the source is a concrete fragile BCL collection, or a live `Keys`/`Values` view over one, and the mutator resolves to that same collection's own member; concurrent and immutable collections and arrays are outside the population by construction, since their enumerators survive a structural change. ARM B — the source is an argument-less accessor CALL on a receiver whose body is in source: the accessor must return a stored field VERBATIM and a sibling member must structurally change that same field, both read off the implementations rather than from the members' names. A mutation the loop provably exits immediately after (`break`/`return`/`throw`/`goto`), or one written inside a nested loop or a lambda, is counted and never reported. Deterministic, provable per finding. Advisory.

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X28 · Index access outside its own emptiness guard10.0 / 10Exemplary○ Nothing flagged

Other · Code Health — Whether a condition that tests a value for emptiness indexes that same value only where the test holds — an `||` written one parenthesis too far to the left leaves an index access outside the guard beside it, so the empty case the guard exists to anticipate reaches the index and throws.

Method: Roslyn syntax only, no semantic model: the OUTERMOST `&&`/`||` of every boolean condition, read for a symbol the condition tests for emptiness (`string.IsNullOrEmpty`/`IsNullOrWhiteSpace`, a `Length`/`Count` comparison against a literal, `Any()`, a `Length`/`Count` pattern, or a comparison against `""`) and ALSO indexes. Each `symbol[...]` access is placed by a boolean-reachability walk from the access up to the outermost connective: an access is COVERED when some enclosing step has it in the right operand and the left operand, under the truth value that step forces, proves the symbol non-empty — a recursion over `&&`/`||` whose true- and false-directions are asymmetric. A finding needs BOTH an uncovered access and a covered one on the same symbol in the same condition, which is the agreeing twin that separates a misplaced parenthesis from an unrelated length test. Bare index accesses with no emptiness test in the condition are neither counted nor reported; a non-identifier receiver and a lambda nested inside the condition are outside the population. Deterministic, provable per finding. Advisory.

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X3 · Exception handling10.0 / 10Exemplary○ Nothing flagged

Other · Code Health — Whether exceptions are handled rather than silently swallowed or rethrown with lost stack traces.

Method: Roslyn syntax scan: every catch clause counted; empty catches and bare rethrows flagged. Population is all catch clauses, not estimated. Deterministic, hard fact.

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X30 · Support guard that admits what it rejects10.0 / 10Exemplary○ Nothing flagged

Other · Code Health — Whether a guard written as a NEGATED `||` says what its author meant — `!(a || b || x != k)` is `!a && !b && x == k` by De Morgan, so a bail-out that mixes capabilities the code needs with a fault it refuses turns inside out: it fires only where the capabilities are ABSENT, and lets every value the fault term names walk straight into the body that cannot handle it.

Method: Roslyn syntax only, no semantic model: every logical-not whose operand is a parenthesised `||` chain of two or more disjuncts, flattened (a left-nested `a || b || c` read once would see `(a || b)` as one disjunct). A site enters the population on that shape alone. A finding additionally needs the disjuncts to DISAGREE in polarity: at least one bare boolean read — an identifier or member access, never an invocation, which is a predicate rather than a capability flag — and at least one `x != <constant>`, the only form that negates into an exact-value pin (`== null` negates into a looser requirement and is outside the fault set). Consistently-polarised disjunctions, all-fault or all-capability, are counted and never reported; a negated `&&` is outside the population entirely. No same-receiver gate: it was measured to cost a real defect and remove no false positive. Deterministic, provable per finding. Advisory.

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Reference — by lens

The score is the rank-weighted fold of these lenses (worst-heaviest), each including its meta-dimensions; a lens with a Critical contributor is capped at Fair (its band reads "gated by …") and is never the strongest area however high its average.

Lens	Score	Rating	Impact
Code Health	92%	Exemplary	Strongest area.
Architecture	87%	Adequate — gated by D26	Capped at Fair by a Critical contributor — resolve it before relying on this lens.
Maturity	59%	Adequate — gated by M2	Capped at Fair by a Critical contributor — resolve it before relying on this lens.
Readiness	44%	Weak — gated by P3, P5	Capped at Fair by a Critical contributor — resolve it before relying on this lens.
Security	87%	Strong	Solid.
Performance	90%	Exemplary	Solid.

Unscored — 2 check(s) recorded observations but carry no score

These checks ran and found something, but they do not carry a score — either by design (an advisory check reports evidence rather than grading it) or because they could not be scored here. They are excluded from the score for that reason, not because there was nothing to see.

D36 Supply-chain Provenance & Signing — 1 observation(s) recorded · The CI pipeline builds and tests but publishes no released artifact — no package publish, container push, GitHub release or deployment step. Supply-chain provenance, signing and SBOM attest RELEASED artifacts, so there is nothing to attest here. Add them to the release pipeline when this repo starts shipping artifacts (a published package, a container image, a deployed service or a tagged release). Build integrity and workflow-token hygiene are reported below: they describe what the CI runs and the token it runs with, neither of which is affected by whether the pipeline ships an artifact.
X10 Duplicated predicate — 5 observation(s) recorded · Advisory — this card reports evidence and never carries a score.

Not evidenced — 3 control(s) we could not find positive evidence for

These checks grade a working control, and the repository shows no evidence of one. That is deliberately not scored as a zero: a repository cannot show an ops runbook, a database TTL or an infrastructure-side audit log, so absence of evidence here is not evidence the control is missing. It is also not a statement that the check is irrelevant to this codebase — the thing it grades applies; we just could not see it. Excluded from the score either way.

C3 Audit Trail — Not assessed: this repository stores data through 'sqlite3' (eventsourcing/sqlite.py:3) but declares no persisted model this check reads (Django, SQLAlchemy, SQLModel, Peewee, Tortoise and MongoEngine model fields, Alembic and Django migration columns, CREATE TABLE and ALTER TABLE … ADD columns in SQL files). Personal data may be written through raw SQL or a hosted backend, so whether its changes need an audit trail could not be established, and the trail's absence is not scored.
C4 Data Retention — Not assessed: this repository stores data through 'sqlite3' (eventsourcing/sqlite.py:3) but declares no persisted model this check reads (Django, SQLAlchemy, SQLModel, Peewee, Tortoise and mongoengine model fields, Alembic and Django migration columns, SQL schemas). Personal data may be written through raw SQL or a hosted backend, so whether a retention limit applies here could not be established, and its absence is not scored.
C5 Data-Subject Rights — Not assessed: this repository stores data through 'sqlite3' (eventsourcing/sqlite.py:3) but declares no persisted model this check reads (Django, SQLAlchemy, SQLModel, Peewee, Tortoise and mongoengine model fields, Alembic and Django migration columns, CREATE TABLE and ALTER TABLE … ADD columns in SQL files). Personal data may be written through raw SQL or a hosted backend, so whether data-subject rights apply here could not be established, and their absence is not scored.

Not included — 58 check(s) not relevant to this codebase

These checks had nothing to measure here (no tests, no git history, the codebase is small, or the architecture style doesn't apply), so they're omitted above rather than scored low.

AC1 Text alternatives — No web markup found — accessibility is not applicable to this repository.
AC2 Forms & labels — No web markup found — accessibility is not applicable to this repository.
AC3 Page structure — No web markup found — accessibility is not applicable to this repository.
AC4 Keyboard semantics — No web markup found — accessibility is not applicable to this repository.
AC5 ARIA correctness — No web markup found — accessibility is not applicable to this repository.
AC6 Visual & motion safety — No web markup found — accessibility is not applicable to this repository.
AC7 A11y enforcement — No web markup found — accessibility is not applicable to this repository.
AX1 Captive dependencies — not analysed — these correctness checks read a source model that was not loaded for this repository, because the repository is written in a language this check does not yet model, or because its projects failed to load. This is a gap in the analyzer, not a finding about this repository
AX2 Stateful singletons — No container singleton was found, so there is no shared instance for concurrent requests to race on. No function in this Python code is served by a threaded web framework (a Flask, Bottle or FastAPI route, a Django or Pyramid view), so no module is shared between request threads.
AX6 Interface segregation — not assessed — interface segregation is computed over a type surface that was not loaded for this repository, because the repository is written in a language this check does not yet model, or because its projects failed to load. This is a gap in the analyzer, not a finding about this repository
AX7 Slice cohesion — not applicable — not a vertical-slice architecture
AX8 Test isolation — no test/production split to check
AX9 CQS / query purity — no CQRS query handlers detected — query purity is not applicable to this codebase
AXB2 Runtime readiness — Advisory — this card reports evidence and never carries a score, so there is nothing missing here.
AXR1 Runtime accessibility — compose up failed (exit 18 — an image could not be pulled) — axon Pulling cassandra Pulling redis Pulling mysql Error Get "https://registry-1.docker.io/v2/": Forbidden axon Error Get "https://registry-1.docker.io/v2/": Forbidden postgres Error context canceled redis Error context canceled eventsourcing_requirements Warning context canceled cassandra Error context canceled Error response from daemon: Get "https://registry-1.docker.io/v2/": Forbidden; the earlier `compose pull` step reported: eventsourcing_requirements Warning context canceled redis Error context canceled cassandra Error context canceled mysql Error context canceled postgres Error context canceled WARNING: Some service image(s) must be built from source by running: docker compose build eventsourcing_requirements Error response from daemon: Get "https://registry-1.docker.io/v2/": Forbidden; the runtime sandbox reaches registries only through the in-fence pull-through mirror, so an image the mirror does not carry cannot be fetched — this is a limit of our sandbox, not of your stack; runtime evidence skipped This is a statement about this run, not a statement about your application: nothing here says the surface is inaccessible, only that it was never rendered.
C1 Data Protection — Not assessed: these personal data controls are read from a source model (declarative annotations, request middleware, entity/column names, guard methods) that was not loaded for this repository — because the repository is written in a language this check does not yet model, or because its projects failed to load. Absence of an idiom this check recognises is NOT evidence that this repository lacks personal data controls: it may implement them entirely in its own ecosystem. This is a gap in the analyzer's language coverage, not a finding about this repository.
C2 Access Controls — No access-control surface detected in the analyzed source — this repository registers no route and starts no server another machine can reach (no Flask/FastAPI/Starlette route, Django urlpatterns or class-based view, Tornado handler). Access control is therefore N/A here — a library or command-line tool is authorized by the application that serves it, not by itself. If this codebase grows request handlers, the dimension reactivates and a default-deny posture is expected then.
D10 Test Quality — ~17889 lines of test source are present (.py) but no test cases reached the test census for this repository — no test root we could resolve declared them, or the files we read declare no cases in a test framework we recognise — so skipped/assertion-free tests couldn't be counted. Not scored — this is a gap in the analyzer, not a finding about this repository.
D12 Dependency Hygiene — Dependency currency not established — no declaration carries an exact pin to grade
D16 Bus Factor — single-maintainer repository — bus factor is not applicable
D18 Solution Shape — D18 scores the shape of a .NET solution; this repository has no .NET solution or project files, so the dimension does not apply.
D20 ADR Quality — N/A — ADRs are expected on deployable products with a user-facing host, not consumed libraries; no ADR log is required here.
D24 Comment Value — No inline comments to assess — comment value is not applicable here.
D25 ADR Conformance — no ADRs to check
D27 Navigability — D27 counts a call into the standard library or a dependency as unresolved for this repository's language (.py), so too few call sites counted as resolved to assess navigability. Not scored: this is a gap in the analyzer, not a verdict about this repository.
D32 Data Compliance (PII/GDPR) — No personal data was found crossing a boundary the PII/GDPR ruleset checks — nothing written to a log or console sink, placed in a URL or query string, or persisted to browser storage. That is a clean result for the LEAK surface only: this ruleset detects personal data escaping, it does not inventory the personal data a repository holds, so it is not evidence that this repository has no personal-data surface. The personal-data map (Appendix C) and the C1-C5 compliance cards are what speak to that.
D37 Vulnerability-disclosure Policy — No vulnerability-disclosure policy file found (SECURITY.md/.markdown/.rst/.txt at root or under .github/.forgejo/.gitea/docs, .well-known/security.txt). A coordinated-disclosure policy may live off-repo, so this is not evidenced rather than failed.
D39 IL Efficiency — D39 measures the IL emitted by a .NET build; this repository has no .NET solution or project files, so the dimension does not apply.
D40 Network Egress Confinement — No Kubernetes/orchestration workloads found in the repository manifests; network egress policy is a cluster-native control that may live at the platform/firewall layer, so there is nothing to assess here.
D41 Kernel & Syscall Confinement — No Kubernetes/orchestration workloads found in the repository manifests; seccomp/AppArmor/SELinux confinement is a workload-level control, so there is nothing to assess here.
D42 Runtime Threat Enforcement — No Kubernetes/orchestration workloads found in the repository manifests; runtime threat-detection and admission-control policy are cluster-level controls, so there is nothing to assess here.
D5 Coupling — Not applicable — this Python build ships 1 production module(s), so there is no coupling BETWEEN modules to measure. (Its test and non-production modules are not part of the shipped graph.)
D7 Architectural Integrity — no checkable ADRs, and no project-reference graph for the cycle pass to read — so this dimension makes no claim about dependency cycles in either direction (where this repository's language has an import-cycle lens, cycles are reported there). Architectural integrity not assessed
D8 Code Coverage — Coverage not included — suite not readable by the collector
DM1 Domain Modelling — applicable but not scored (4 signals for this style, 3 needed — the count is met but a required primary signal is absent): 32 aggregate root(s) (AggregateRoot/IAggregateRoot); 24 value object(s); 54 domain event(s); a Domain/Aggregates/ValueObjects layer; a top-level examples/ tree: a library or framework whose examples are its consumers — these types are building blocks, not a domain
ED1 Event-Driven — not scored — this repository shows none of the 3 signals this lens looks for
ED5 Idempotency — no mutating command handlers or message consumers detected — idempotency check not applicable
ES1 Event Sourcing — not scored — this repository shows none of the 3 signals this lens looks for
GD1 Unfinished & placeholder code — no source files were read — this check reads C#, F#, JavaScript/TypeScript, Dart, Ruby and Scala, and none was read for this repository's product. That is a limit of the analyzer, not a finding about your code.
IC1 Incompleteness & stubs — not analysed — these correctness checks read a source model that was not loaded for this repository, because the repository is written in a language this check does not yet model, or because its projects failed to load. This is a gap in the analyzer, not a finding about this repository
P12 CI test-gate honesty — Reported, not scored — this card publishes what the CI gate does with the test inventory rather than grading it. The findings above are its output.
P7 Outbound HTTP resilience — not applicable — no HTTP server, API framework or worker entry point was found in the Python source, so there is no service whose uptime a failing dependency could take down
P8 Schema migrations — Django is declared, but the schema-migration mechanism could not be identified. Our limit, not a verdict on this repository.
P9 Domain vs controller coverage — no coverage report found on disk — produce a coverage report in a standard format (`coverage run -m pytest` then `coverage xml`) and commit it — a hosted scan measures a clone of the repository, so a report that exists only in a working tree, a CI runner's or your own, never reaches it; the artefact is commonly gitignored, so `git add -f` that one file (or un-ignore its path) and commit it alongside the code it measures, or wire coverage collection into CI, to enable this cross-layer check
PF2 Allocation hygiene — Not applicable: Python runs on a garbage-collected runtime that gives a program no allocation-control idiom to choose on a hot path — no pools, stack allocation or value types — so allocation awareness is not something this code can be rated on.
PF3 Async & latency hygiene — Not applicable: this repository declares no async functions, so there is no asynchronous code for a blocking call to stall.
S1 Web-Security Posture — Not assessed: these web-security controls are read from a source model (declarative annotations, request middleware, entity/column names, guard methods) that was not loaded for this repository — because the repository is written in a language this check does not yet model, or because its projects failed to load. Absence of an idiom this check recognises is NOT evidence that this repository lacks web-security controls: it may implement them entirely in its own ecosystem. This is a gap in the analyzer's language coverage, not a finding about this repository.
X16 Unfloored truncation loop — not analysed — these correctness checks read a source model that was not loaded for this repository, because the repository is written in a language this check does not yet model, or because its projects failed to load. This is a gap in the analyzer, not a finding about this repository
X18 Disposal-pattern correctness — not analysed — these correctness checks read a source model that was not loaded for this repository, because the repository is written in a language this check does not yet model, or because its projects failed to load. This is a gap in the analyzer, not a finding about this repository
X2 Cancellation propagation — no C# was loaded; this repository's Python was read, and no request in it can be cancelled by a caller — a Python request takes no token: asyncio cancels the task and trio or anyio the scope that made it, from outside the call, and requests, httpx, aiohttp and gRPC take a timeout, not a cancellation
X20 Mistyped argument guard — This check asks whether an argument guard reports an EMPTY value as a NULL one, which needs a language that throws a null-specific argument exception — .NET's ArgumentNullException, the JVM's NullPointerException, Dart's ArgumentError.notNull. This repository contains none of those languages: the ones it is written in have a single exception for a bad argument, so there is no pair of exceptions to confuse and nothing here for it to assess. Not a gap in the analyzer and not a finding about your code.
X29 Per-element action decided by a fixed element — not analysed — these correctness checks read a source model that was not loaded for this repository, because the repository is written in a language this check does not yet model, or because its projects failed to load. This is a gap in the analyzer, not a finding about this repository
X32 Type resolved by simple name across every loaded assembly — This check is about how a .NET program searches the assemblies loaded into its process for a type, and this repository contains no .NET source, so there is nothing here for it to assess. Not a gap in the analyzer and not a finding about your code.
X4 Structured logging — not analysed — these correctness checks read a source model that was not loaded for this repository, because the repository is written in a language this check does not yet model, or because its projects failed to load. This is a gap in the analyzer, not a finding about this repository
X5 Nullable reference types — not analysed — these correctness checks read a source model that was not loaded for this repository, because the repository is written in a language this check does not yet model, or because its projects failed to load. This is a gap in the analyzer, not a finding about this repository
X6 Hand-rolled structured-format parsing — Advisory — this card reports evidence and never carries a score, so there is nothing missing here.
X7 Silent fallback defaults — Advisory — this card reports evidence and never carries a score, so there is nothing missing here.
X9 Subsumed condition operand — Advisory — this card reports evidence and never carries a score, so there is nothing missing here.

Appendix A — Findings (grouped)

The findings behind the scores, grouped by severity, then by dimension and kind. The high-severity issues are enumerated in full below; items per group are capped at 25 with any overflow stated explicitly per group, never silently truncated. The complete machine-readable list of every finding (all severities) is the companion findings.md in this report's bundle.

Critical — 14 finding(s)

D31 · IaC & Container Security · High IaC · ×5

REDACTED
REDACTED
REDACTED
REDACTED
REDACTED

D29 · Static Analysis (SAST) · REDACTED

REDACTED
REDACTED
REDACTED
REDACTED

D30 · Dependency Vulnerabilities · High CVE · ×2

REDACTED
REDACTED

D29 · Static Analysis (SAST) · REDACTED · ×1

REDACTED

D29 · Static Analysis (SAST) · REDACTED · ×1

REDACTED

D30 · Dependency Vulnerabilities · Critical vulnerability · ×1

REDACTED

Serious — 116 finding(s)

D17 · Explicit Debt · TodoComment · ×36

TodoComment eventsourcing/utils.py:224 — # TODO: Inline this now. — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `# REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment eventsourcing/projection.py:430 — # TODO: Improve typing of application classes and type annotation for self.app — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `# REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment eventsourcing/postgres.py:1147 — # TODO: Indicate both keys here, also for other environment variables. — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `# REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment eventsourcing/persistence.py:453 — # TODO: Write a test where a custom class does override __init_subclass__ — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `# REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment eventsourcing/domain.py:280 — # TODO: Move this to a HasTimestamp? Why is it here?? — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `# REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment eventsourcing/domain.py:535 — # TODO: Disallow unusual property setters in more detail. — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `# REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment eventsourcing/domain.py:784 — # TODO: Review this, because other subclasses of BaseAggregate might too.... — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `# REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment eventsourcing/domain.py:885 — # TODO: Support VAR_POSITIONAL? — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `# REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment eventsourcing/domain.py:889 — # TODO: Support VAR_KEYWORD? — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `# REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment eventsourcing/domain.py:896 — # TODO: Support POSITIONAL_ONLY? — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `# REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment eventsourcing/domain.py:1392 — # TODO: Review decorator processing below to see if subclassing can be improved. — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `# REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment eventsourcing/domain.py:1410 — # # TODO: Maybe also prohibit triggering such things? — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `# REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment eventsourcing/domain.py:1659 — # TODO: Check if this subclassing means we can avoid some of — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `# REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment eventsourcing/domain.py:1811 — # TODO: Improve on this 'Any'. — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `# REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment eventsourcing/application.py:282 — # TODO: Should this be 'fastforward or self.fastforward_skipping'? — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `# REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment eventsourcing/application.py:924 — # TODO: Rename to 'event_class' in v10. — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `# REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment eventsourcing/application.py:928 — # TODO: Rename to 'event_class' in v10. — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `# REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment eventsourcing/dcb/postgres_tt.py:399 — # TODO: Actually return an iterator from _read()! — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `# REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment eventsourcing/dcb/popo.py:66 — # TODO: Change the previous few lines to actually be an iterator. — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `# REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment eventsourcing/dcb/persistence.py:204 — # TODO: Cover this with a test... — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `# REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment eventsourcing/dcb/domain.py:48 — # TODO: Write a test that does this... — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `# REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment eventsourcing/dcb/domain.py:82 — # TODO: Write a test that does this... — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `# REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment eventsourcing/dcb/domain.py:200 — # TODO: Maybe support event name strings, maybe not.... — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `# REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment eventsourcing/dcb/domain.py:232 — # TODO: For convenience, make this error out in the same way — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `# REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment eventsourcing/tests/persistence.py:1595 — # TODO: Int keys? — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `# REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
+ 11 more in this group — see findings.md.

D23 · Boundary Type-Coupling · Cross-context type Selector (eventsourcing → examples) · ×10

Cross-context type Selector (eventsourcing → examples) examples/dcb_enrolment_with_vertical_slices/application.py:81 — Selector (context eventsourcing) is exposed in examples's public surface via RegisterStudent.consistency_boundary — couples the contexts.
Cross-context type Selector (eventsourcing → examples) examples/dcb_enrolment_with_vertical_slices/application.py:100 — Selector (context eventsourcing) is exposed in examples's public surface via UpdateStudentName.consistency_boundary — couples the contexts.
Cross-context type Selector (eventsourcing → examples) examples/dcb_enrolment_with_vertical_slices/application.py:123 — Selector (context eventsourcing) is exposed in examples's public surface via UpdateMaxCourses.consistency_boundary — couples the contexts.
Cross-context type Selector (eventsourcing → examples) examples/dcb_enrolment_with_vertical_slices/application.py:149 — Selector (context eventsourcing) is exposed in examples's public surface via RegisterCourse.consistency_boundary — couples the contexts.
Cross-context type Selector (eventsourcing → examples) examples/dcb_enrolment_with_vertical_slices/application.py:168 — Selector (context eventsourcing) is exposed in examples's public surface via UpdateCourseName.consistency_boundary — couples the contexts.
Cross-context type Selector (eventsourcing → examples) examples/dcb_enrolment_with_vertical_slices/application.py:191 — Selector (context eventsourcing) is exposed in examples's public surface via UpdatePlaces.consistency_boundary — couples the contexts.
Cross-context type Selector (eventsourcing → examples) examples/dcb_enrolment_with_vertical_slices/application.py:355 — Selector (context eventsourcing) is exposed in examples's public surface via StudentsIDs.consistency_boundary — couples the contexts.
Cross-context type Selector (eventsourcing → examples) examples/dcb_enrolment_with_vertical_slices/application.py:397 — Selector (context eventsourcing) is exposed in examples's public surface via CourseIDs.consistency_boundary — couples the contexts.
Cross-context type Selector (eventsourcing → examples) examples/dcb_enrolment_with_vertical_slices/application.py:442 — Selector (context eventsourcing) is exposed in examples's public surface via Student.consistency_boundary — couples the contexts.
Cross-context type Selector (eventsourcing → examples) examples/dcb_enrolment_with_vertical_slices/application.py:476 — Selector (context eventsourcing) is exposed in examples's public surface via Course.consistency_boundary — couples the contexts.

D3 · God Classes · FileTooLong · ×6

FileTooLong: eventsourcing/domain.py eventsourcing/domain.py — FileTooLong — 1140 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 640 over it, 2.28× the bar. To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
FileTooLong: eventsourcing/postgres.py eventsourcing/postgres.py — FileTooLong — 1130 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 630 over it, 2.26× the bar. To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
FileTooLong: eventsourcing/persistence.py eventsourcing/persistence.py — FileTooLong — 948 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 448 over it, 1.90× the bar. To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
FileTooLong: eventsourcing/system.py eventsourcing/system.py — FileTooLong — 816 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 316 over it, 1.63× the bar. To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
FileTooLong: eventsourcing/application.py eventsourcing/application.py — FileTooLong — 647 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 147 over it, 1.29× the bar. To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
FileTooLong: eventsourcing/sqlite.py eventsourcing/sqlite.py — FileTooLong — 644 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 144 over it, 1.29× the bar. To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.

D23 · Boundary Type-Coupling · Cross-context type CanInitAggregate (eventsourcing → examples) · ×4

Cross-context type CanInitAggregate (eventsourcing → examples) examples/aggregate10/mutablemodel.py:79 — CanInitAggregate (context eventsourcing) is exposed in examples's public surface via Created.CanInitAggregate — couples the contexts.
Cross-context type CanInitAggregate (eventsourcing → examples) examples/aggregate11/domainmodel.py:48 — CanInitAggregate (context eventsourcing) is exposed in examples's public surface via Created.CanInitAggregate — couples the contexts.
Cross-context type CanInitAggregate (eventsourcing → examples) examples/aggregate8/mutablemodel.py:59 — CanInitAggregate (context eventsourcing) is exposed in examples's public surface via Created.CanInitAggregate — couples the contexts.
Cross-context type CanInitAggregate (eventsourcing → examples) examples/dcb_enrolment/domainmodel.py:36 — CanInitAggregate (context eventsourcing) is exposed in examples's public surface via MsgspecStringIDCreatedEvent.CanInitAggregate — couples the contexts.

D6 · Cohesion (LCOM4) · Low cohesion · ×4

Low cohesion: Application (LCOM4 4) eventsourcing/application.py:602 — Application's methods fall into 4 groups that share no field and call none of each other, against a bar of more than 3 for this run (LCOM4, configurable — your repository's bar is the one quoted here). Each group is a set of methods reachable from one another through shared fields or direct calls, so 4 groups means the type has that many internally-connected clusters with nothing tying them together. Types whose shape makes a high count expected — and which would otherwise dominate this list — are excluded before this row is raised, so this is a genuine split candidate rather than a metric reading. It is still a shape, not a defect: confirm the groups match responsibilities you can name before splitting.
Low cohesion: DCBApplication (LCOM4 4) eventsourcing/dcb/application.py:30 — DCBApplication's methods fall into 4 groups that share no field and call none of each other, against a bar of more than 3 for this run (LCOM4, configurable — your repository's bar is the one quoted here). Each group is a set of methods reachable from one another through shared fields or direct calls, so 4 groups means the type has that many internally-connected clusters with nothing tying them together. Types whose shape makes a high count expected — and which would otherwise dominate this list — are excluded before this row is raised, so this is a genuine split candidate rather than a metric reading. It is still a shape, not a defect: confirm the groups match responsibilities you can name before splitting.
Low cohesion: PostgresFtsRecorder (LCOM4 4) examples/ftscontentmanagement/postgres.py:25 — PostgresFtsRecorder's methods fall into 4 groups that share no field and call none of each other, against a bar of more than 3 for this run (LCOM4, configurable — your repository's bar is the one quoted here). Each group is a set of methods reachable from one another through shared fields or direct calls, so 4 groups means the type has that many internally-connected clusters with nothing tying them together. Types whose shape makes a high count expected — and which would otherwise dominate this list — are excluded before this row is raised, so this is a genuine split candidate rather than a metric reading. It is still a shape, not a defect: confirm the groups match responsibilities you can name before splitting.
Low cohesion: SQLiteFtsRecorder (LCOM4 4) examples/ftscontentmanagement/sqlite.py:21 — SQLiteFtsRecorder's methods fall into 4 groups that share no field and call none of each other, against a bar of more than 3 for this run (LCOM4, configurable — your repository's bar is the one quoted here). Each group is a set of methods reachable from one another through shared fields or direct calls, so 4 groups means the type has that many internally-connected clusters with nothing tying them together. Types whose shape makes a high count expected — and which would otherwise dominate this list — are excluded before this row is raised, so this is a genuine split candidate rather than a metric reading. It is still a shape, not a defect: confirm the groups match responsibilities you can name before splitting.

D22 · Internal API Consistency · Redundant interface implementation · ×2

Redundant interface implementation: LRUCache duplicates the exact signature of the abstract Cache interface. While this is technically an implementation, exposing both as top-level public types with identical method signatures suggests a lack of clear abstraction hierarchy or unnecessary duplication in the public surface. — Ensure LRUCache is clearly documented as the concrete implementation of Cache, or remove the explicit public exposure of the base Cache class if it serves no polymorphic purpose for the user. (signatures: eventsourcing.application.Cache.get(self, key: S, evict: bool): T | eventsourcing.application.LRUCache.get(self, key: S, evict: bool): T)
Redundant interface implementation: Similar to Cache, ZlibCompressor duplicates the Compressor interface signature. If Compressor is an abstract base, it should not be a public concrete type if it has no other purpose, or ZlibCompressor should be the only public entry point. — Consolidate into a single Compressor protocol/interface and ensure only concrete implementations (like ZlibCompressor) are exposed, or remove the abstract Compressor from the public API if it's internal. (signatures: eventsourcing.persistence.Compressor.compress(self, data: bytes): bytes | eventsourcing.compressor.ZlibCompressor.compress(self, data: bytes): bytes)

D23 · Boundary Type-Coupling · Cross-context type Aggregate (eventsourcing → examples) · ×2

Cross-context type Aggregate (eventsourcing → examples) examples/cargoshipping/domainmodel.py:201 — Aggregate (context eventsourcing) is exposed in examples's public surface via Event.apply — couples the contexts.
Cross-context type Aggregate (eventsourcing → examples) examples/contentmanagement/domainmodel.py:34 — Aggregate (context eventsourcing) is exposed in examples's public surface via Event.apply — couples the contexts.

D4 · Code Duplication · Duplicated block (20 lines × 2) · ×2

Duplicated block (20 lines × 2) eventsourcing/dcb/domain.py:34 — eventsourcing/dcb/domain.py:34-53 | eventsourcing/dcb/domain.py:68-87 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited.
Duplicated block (20 lines × 2) eventsourcing/system.py:632 — eventsourcing/system.py:632-651 | eventsourcing/system.py:801-820 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited.

D4 · Code Duplication · Duplicated block (13 lines × 2) · ×2

Duplicated block (13 lines × 2) eventsourcing/dcb/postgres_tt.py:669 — eventsourcing/dcb/postgres_tt.py:669-681 | eventsourcing/postgres.py:843-855 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice. Read the line range as the matched WINDOW rather than a finished unit: at `eventsourcing/dcb/postgres_tt.py:669` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (13 lines × 2) eventsourcing/postgres.py:1003 — eventsourcing/postgres.py:1003-1015 | eventsourcing/sqlite.py:595-607 — the copies sit in sibling files of one directory, so a shared home is within easy reach: extract the block into a single shared function the call sites can all reach — a file they already depend on, or a new one alongside them — and call it from both call sites, so a change lands once. ★ These copies have DRIFTED, and that is worth reading before extracting anything: just after the matched lines, `eventsourcing/postgres.py:1017` calls `retry` and `eventsourcing/sqlite.py:609` does not — after which the two agree again for 4 more lines. One of those two behaviours is the intended one and the other is what a copy-paste left behind, so decide which BEFORE unifying them: extracting the shared part will silently settle it, and if the copy that skips the call is the wrong one, that bug is already live.

D4 · Code Duplication · Duplicated block (12 lines × 2) · ×2

Duplicated block (12 lines × 2) eventsourcing/postgres.py:1294 — eventsourcing/postgres.py:1294-1305 | eventsourcing/sqlite.py:724-735 — the copies sit in sibling files of one directory, so a shared home is within easy reach: extract the block into a single shared function the call sites can all reach — a file they already depend on, or a new one alongside them — and call it from both call sites, so a change lands once. Read the line range as the matched WINDOW rather than a finished unit: at `eventsourcing/postgres.py:1294` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. ★ These copies have DRIFTED, and that is worth reading before extracting anything: just before the matched lines, `eventsourcing/postgres.py:1290` calls `get` and `eventsourcing/sqlite.py:720` does not — after which the two agree again for 2 more lines. One of those two behaviours is the intended one and the other is what a copy-paste left behind, so decide which BEFORE unifying them: extracting the shared part will silently settle it, and if the copy that skips the call is the wrong one, that bug is already live.
Duplicated block (12 lines × 2) eventsourcing/system.py:395 — eventsourcing/system.py:395-406 | eventsourcing/system.py:493-504 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited.

D4 · Code Duplication · Duplicated block (11 lines × 2) · ×2

Duplicated block (11 lines × 2) eventsourcing/domain.py:1735 — eventsourcing/domain.py:1735-1746 | eventsourcing/domain.py:1755-1765 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited.
Duplicated block (11 lines × 2) eventsourcing/cipher.py:48 — eventsourcing/cipher.py:48-58 | eventsourcing/cryptography.py:46-56 — the copies sit in sibling files of one directory, so a shared home is within easy reach: extract the block into a single shared function the call sites can all reach — a file they already depend on, or a new one alongside them — and call it from both call sites, so a change lands once. Read the line range as the matched WINDOW rather than a finished unit: at `eventsourcing/cipher.py:48` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.

D4 · Code Duplication · Duplicated block (10 lines × 2) · ×2

Duplicated block (10 lines × 2) eventsourcing/dcb/postgres_tt.py:689 — eventsourcing/dcb/postgres_tt.py:689-698 | examples/dcb_enrolment_with_basic_objects/postgres_ts.py:468-477 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice. The `return` at the foot of the matched lines is the enclosing body's own terminal exit, not an early one: it moves with them unchanged, and each site calls the extracted unit from the position that `return` occupied — no decision has to be handed back and re-acted on.
Duplicated block (10 lines × 2) examples/aggregate6a/domainmodel.py:83 — examples/aggregate6a/domainmodel.py:83-92 | examples/aggregate7a/domainmodel.py:103-112 — `examples/aggregate6a/domainmodel.py` and `examples/aggregate7a/domainmodel.py` are one unit implemented once per sibling directory, so they are most likely parallel implementations of one contract rather than a copy of each other — this scan matched 4 separate duplicated blocks between them, totalling at least 34 lines. If both are selected at run time, neither can be retired in favour of the other, and the lines that DIFFER between them are the reason both exist. The move that pays here is to hoist the identical part into a shared location the whole family can reach and give what differs a parameter or a seam, so a change lands once instead of once per sibling; extracting one helper per block leaves every sibling to drift on its own. The `return` at the foot of the matched lines is the enclosing body's own terminal exit, not an early one: it moves with them unchanged, and each site calls the extracted unit from the position that `return` occupied — no decision has to be handed back and re-acted on.

D4 · Code Duplication · Duplicated block (7 lines × 2) · ×2

Duplicated block (7 lines × 2) eventsourcing/domain.py:423 — eventsourcing/domain.py:423-429 | examples/aggregate11/domainmodel.py:27-33 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice.
Duplicated block (7 lines × 2) examples/aggregate7/immutablemodel.py:40 — examples/aggregate7/immutablemodel.py:40-46 | examples/aggregate7a/domainmodel.py:56-62 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice. The matched lines also transfer control out of the body holding them, which cannot survive a move into a called unit unchanged: have the extracted unit return that decision and let each site act on it.

D4 · Code Duplication · Duplicated block (8 lines × 2) · ×2

Duplicated block (8 lines × 2) eventsourcing/postgres.py:1047 — eventsourcing/postgres.py:1047-1054 | eventsourcing/sqlite.py:637-644 — the copies sit in sibling files of one directory, so a shared home is within easy reach: extract the block into a single shared function the call sites can all reach — a file they already depend on, or a new one alongside them — and call it from both call sites, so a change lands once. Note first that the copies are not typed on the same thing: the declarations holding them bind `c` to `Cursor[DictRow]` in one and `SQLiteCursor` in another, and the duplicated lines use it. The extracted unit therefore needs a parameter type that fits BOTH — their common supertype where they have one, or a new abstraction over them where they do not — and settling that is the step that comes BEFORE the extraction above. Where the two types are deliberately unrelated, the duplication is the price of that separation and the honest resolution is to record the decision rather than to extract.
Duplicated block (8 lines × 2) examples/aggregate7/domainmodel.py:82 — examples/aggregate7/domainmodel.py:82-89 | examples/aggregate7a/domainmodel.py:159-166 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice. The matched lines also transfer control out of the body holding them, which cannot survive a move into a called unit unchanged: have the extracted unit return that decision and let each site act on it.

D4 · Code Duplication · Duplicated block (8 lines × 5) · ×2

Duplicated block (8 lines × 5) examples/aggregate6/baseclasses.py:51 — examples/aggregate6/baseclasses.py:51-58 | examples/aggregate6a/domainmodel.py:53-60 | examples/aggregate7/immutablemodel.py:57-64 | examples/aggregate7a/domainmodel.py:72-79 | examples/aggregate9/immutablemodel.py:57-64 — `examples/aggregate6a/domainmodel.py` and `examples/aggregate7a/domainmodel.py` are one unit implemented once per sibling directory, so they are most likely parallel implementations of one contract rather than a copy of each other — this scan matched 4 separate duplicated blocks between them, totalling at least 34 lines. If both are selected at run time, neither can be retired in favour of the other, and the lines that DIFFER between them are the reason both exist. The move that pays here is to hoist the identical part into a shared location the whole family can reach and give what differs a parameter or a seam, so a change lands once instead of once per sibling; extracting one helper per block leaves every sibling to drift on its own.
Duplicated block (8 lines × 5) examples/aggregate6/domainmodel.py:69 — examples/aggregate6/domainmodel.py:69-76 | examples/aggregate6a/domainmodel.py:127-134 | examples/aggregate7/domainmodel.py:70-77 | examples/aggregate7a/domainmodel.py:147-154 | examples/aggregate9/domainmodel.py:72-79 — `examples/aggregate6a/domainmodel.py` and `examples/aggregate7a/domainmodel.py` are one unit implemented once per sibling directory, so they are most likely parallel implementations of one contract rather than a copy of each other — this scan matched 4 separate duplicated blocks between them, totalling at least 34 lines. If both are selected at run time, neither can be retired in favour of the other, and the lines that DIFFER between them are the reason both exist. The move that pays here is to hoist the identical part into a shared location the whole family can reach and give what differs a parameter or a seam, so a change lands once instead of once per sibling; extracting one helper per block leaves every sibling to drift on its own. The matched lines also transfer control out of the body holding them, which cannot survive a move into a called unit unchanged: have the extracted unit return that decision and let each site act on it.

D1 · Cyclomatic Complexity · BaseAggregate.__init_subclass__ (cyclomatic 83) · ×1

BaseAggregate.__init_subclass__ (cyclomatic 83) eventsourcing/domain.py:1296 — BaseAggregate.__init_subclass__ has cyclomatic complexity 83 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · domain._spec_coerce_args_to_kwargs (cyclomatic 25) · ×1

domain._spec_coerce_args_to_kwargs (cyclomatic 25) eventsourcing/domain.py:937 — domain._spec_coerce_args_to_kwargs has cyclomatic complexity 25 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · BasePostgresFactory.__init__ (cyclomatic 25) · ×1

BasePostgresFactory.__init__ (cyclomatic 25) eventsourcing/postgres.py:1138 — BasePostgresFactory.__init__ has cyclomatic complexity 25 (threshold 15). To reduce it, separate the branches: extract each independent case into its own named function so the top-level body reads as a short sequence of named decisions.

D1 · Cyclomatic Complexity · CommandMethodDecorator.__init__ (cyclomatic 17) · ×1

CommandMethodDecorator.__init__ (cyclomatic 17) eventsourcing/domain.py:484 — CommandMethodDecorator.__init__ has cyclomatic complexity 17 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D2 · Cognitive Complexity · BaseAggregate.__init_subclass__ (cognitive 173) · ×1

BaseAggregate.__init_subclass__ (cognitive 173) eventsourcing/domain.py:1296 — BaseAggregate.__init_subclass__ has cognitive complexity 173 (threshold 15). Drivers by points: if/else 50 (126 pts), loops 11 (24 pts), boolean chains 13, error handling 5 (10 pts) (nesting depth added 94). To reduce it, flatten the nesting: this score is depth rather than breadth — most of its points come from checks stacked inside one another, so the work sits several levels in. Invert each enclosing check into an early exit (a return, or the language's equivalent) so the happy path stays at one level, and where a level cannot be exited early, lift the block it encloses into its own named function. This file is where this pass's cognitive complexity CONCENTRATES: eventsourcing/domain.py holds 4 of the 14 methods over the threshold — including the worst — and 190 of the 284 points over it (67%), 5.3× the next-largest file (eventsourcing/system.py at 36). No single row can show this, because each is measured only against the threshold: reducing this one file moves this dimension further than any other file in the repository.

D2 · Cognitive Complexity · NewSingleThreadedRunner.receive_recording_event (cognitive 40) · ×1

NewSingleThreadedRunner.receive_recording_event (cognitive 40) eventsourcing/system.py:533 — NewSingleThreadedRunner.receive_recording_event has cognitive complexity 40 (threshold 15). Drivers by points: loops 5 (19 pts), if/else 5 (18 pts), boolean chains 3 (nesting depth added 27). To reduce it, break up the iteration: give each loop body a named function, and split a multi-phase loop into one function per phase so no single body carries the whole pipeline.

D2 · Cognitive Complexity · domain._spec_coerce_args_to_kwargs (cognitive 37) · ×1

domain._spec_coerce_args_to_kwargs (cognitive 37) eventsourcing/domain.py:937 — domain._spec_coerce_args_to_kwargs has cognitive complexity 37 (threshold 15). Drivers by points: if/else 15 (25 pts), ternaries 3 (6 pts), loops 4, boolean chains 2 (nesting depth added 13). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body. This file is where this pass's cognitive complexity CONCENTRATES: eventsourcing/domain.py holds 4 of the 14 methods over the threshold — including the worst — and 190 of the 284 points over it (67%), 5.3× the next-largest file (eventsourcing/system.py at 36). No single row can show this, because each is measured only against the threshold: reducing this one file moves this dimension further than any other file in the repository.

D2 · Cognitive Complexity · BasePostgresFactory.__init__ (cognitive 31) · ×1

BasePostgresFactory.__init__ (cognitive 31) eventsourcing/postgres.py:1138 — BasePostgresFactory.__init__ has cognitive complexity 31 (threshold 15). Drivers by points: if/else 12 (13 pts), error handling 7 (12 pts), boolean chains 6 (nesting depth added 6). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · utils.resolve_topic (cognitive 30) · ×1

utils.resolve_topic (cognitive 30) eventsourcing/utils.py:53 — utils.resolve_topic has cognitive complexity 30 (threshold 15). Drivers by points: error handling 6 (19 pts), loops 3 (9 pts), if/else 1 (2 pts) (nesting depth added 20). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · ConnectionPool.get_connection (cognitive 24) · ×1

ConnectionPool.get_connection (cognitive 24) eventsourcing/persistence.py:1209 — ConnectionPool.get_connection has cognitive complexity 24 (threshold 15). Drivers by points: if/else 9 (22 pts), boolean chains 1, ternaries 1 (nesting depth added 13). To reduce it, flatten the nesting: this score is depth rather than breadth — most of its points come from checks stacked inside one another, so the work sits several levels in. Invert each enclosing check into an early exit (a return, or the language's equivalent) so the happy path stays at one level, and where a level cannot be exited early, lift the block it encloses into its own named function.

D2 · Cognitive Complexity · BaseInfrastructureFactory.construct (cognitive 23) · ×1

BaseInfrastructureFactory.construct (cognitive 23) eventsourcing/persistence.py:830 — BaseInfrastructureFactory.construct has cognitive complexity 23 (threshold 15). Drivers by points: if/else 9 (18 pts), boolean chains 2, loops 1 (2 pts), error handling 1 (nesting depth added 10). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · System.__init__ (cognitive 23) · ×1

System.__init__ (cognitive 23) eventsourcing/system.py:230 — System.__init__ has cognitive complexity 23 (threshold 15). Drivers by points: if/else 6 (14 pts), loops 7 (8 pts), boolean chains 1 (nesting depth added 9). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · CommandMethodDecorator.__init__ (cognitive 22) · ×1

CommandMethodDecorator.__init__ (cognitive 22) eventsourcing/domain.py:484 — CommandMethodDecorator.__init__ has cognitive complexity 22 (threshold 15). Drivers by points: if/else 11 (18 pts), boolean chains 4 (nesting depth added 7). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body. This file is where this pass's cognitive complexity CONCENTRATES: eventsourcing/domain.py holds 4 of the 14 methods over the threshold — including the worst — and 190 of the 284 points over it (67%), 5.3× the next-largest file (eventsourcing/system.py at 36). No single row can show this, because each is measured only against the threshold: reducing this one file moves this dimension further than any other file in the repository.

D2 · Cognitive Complexity · Application._take_snapshots (cognitive 20) · ×1

Application._take_snapshots (cognitive 20) eventsourcing/application.py:792 — Application._take_snapshots has cognitive complexity 20 (threshold 15). Drivers by points: if/else 3 (9 pts), error handling 2 (7 pts), boolean chains 2, loops 1 (2 pts) (nesting depth added 12). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · Repository.get (cognitive 18) · ×1

Repository.get (cognitive 18) eventsourcing/application.py:251 — Repository.get has cognitive complexity 18 (threshold 15). Drivers by points: if/else 6 (13 pts), boolean chains 3, error handling 1 (2 pts) (nesting depth added 8). To reduce it, flatten the nesting: this score is depth rather than breadth — most of its points come from checks stacked inside one another, so the work sits several levels in. Invert each enclosing check into an early exit (a return, or the language's equivalent) so the happy path stays at one level, and where a level cannot be exited early, lift the block it encloses into its own named function.

D2 · Cognitive Complexity · HasOriginatorIDVersion.find_originator_id_type (cognitive 18) · ×1

HasOriginatorIDVersion.find_originator_id_type (cognitive 18) eventsourcing/domain.py:256 — HasOriginatorIDVersion.find_originator_id_type has cognitive complexity 18 (threshold 15). Drivers by points: if/else 5 (16 pts), loops 1 (2 pts) (nesting depth added 12). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body. This file is where this pass's cognitive complexity CONCENTRATES: eventsourcing/domain.py holds 4 of the 14 methods over the threshold — including the worst — and 190 of the 284 points over it (67%), 5.3× the next-largest file (eventsourcing/system.py at 36). No single row can show this, because each is measured only against the threshold: reducing this one file moves this dimension further than any other file in the repository.

D2 · Cognitive Complexity · ConvertingThread.run (cognitive 18) · ×1

ConvertingThread.run (cognitive 18) eventsourcing/system.py:1041 — ConvertingThread.run has cognitive complexity 18 (threshold 15). Drivers by points: if/else 5 (11 pts), loops 2 (4 pts), boolean chains 2, error handling 1 (nesting depth added 8). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · InMemoryDCBRecorder.read (cognitive 17) · ×1

InMemoryDCBRecorder.read (cognitive 17) eventsourcing/dcb/popo.py:34 — InMemoryDCBRecorder.read has cognitive complexity 17 (threshold 15). Drivers by points: boolean chains 7, if/else 4 (5 pts), ternaries 2 (4 pts), loops 1 (nesting depth added 3). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D22 · Internal API Consistency · Duplicate type definition · ×1

Duplicate type definition: Two distinct types named AESCipher exist in different modules (cipher vs cryptography) with identical signatures. This creates ambiguity for users importing by name. — Remove one of the modules (likely the older 'cipher' or 'cryptography' one) and consolidate into a single public API entry point. (signatures: eventsourcing.cipher.AESCipher | eventsourcing.cryptography.AESCipher)

D22 · Internal API Consistency · Duplicate property access · ×1

Duplicate property access: Two properties (notification_log and log) expose the exact same type (LocalNotificationLog) and likely the same underlying instance. This is confusing for API consumers who must guess which name to use. — Deprecate one of the properties (likely 'log' if 'notification_log' is more descriptive, or vice versa) and keep only one public accessor. (signatures: eventsourcing.application.Application.notification_log: LocalNotificationLog | eventsourcing.application.Application.log: LocalNotificationLog)

D22 · Internal API Consistency · Inconsistent naming and duplication · ×1

Inconsistent naming and duplication: The abstract Cipher interface and the two AESCipher implementations all expose encrypt/decrypt. Combined with the duplicate AESCipher types, this creates a fragmented API for encryption. — Unify the encryption API. Choose one module (e.g., cryptography) and expose a single Cipher interface and one AESCipher implementation. (signatures: eventsourcing.persistence.Cipher.encrypt(self, plaintext: bytes): bytes | eventsourcing.cipher.AESCipher.encrypt(self, plaintext: bytes): bytes | eventsourcing.cryptography.AESCipher.encrypt(self, plaintext: bytes): bytes)

D29 · Static Analysis (SAST) · REDACTED · ×1

REDACTED

D31 · IaC & Container Security · Medium IaC · ×1

REDACTED

D35 · Change Coupling · Change coupling clique · ×1

Change coupling clique: prepare-distribution.py, release-distribution.py, test-released-distribution.py dev/prepare-distribution.py — 3 files — `dev/prepare-distribution.py`, `dev/release-distribution.py`, `dev/test-released-distribution.py` — all change together with no explicit dependency: a fully-connected co-change clique, not 3 separate couplings. They share one concern (thin parallel siblings over a common abstraction), so extract the shared part into ONE unit and the whole clique's coupling clears at once — you do not need to break each pair individually.

D36 · Supply-chain Provenance & Signing REDACTED · ×1

REDACTED

D4 · Code Duplication · Duplicated block (22–25 lines × 2) · ×1

Duplicated block (22–25 lines × 2) eventsourcing/system.py:409 — eventsourcing/system.py:409-430 | eventsourcing/system.py:507-531 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited.

D4 · Code Duplication · Duplicated block (6 lines × 2) · ×1

Duplicated block (6 lines × 2) eventsourcing/application.py:139 — eventsourcing/application.py:139-144 | eventsourcing/application.py:165-170 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited.

D4 · Code Duplication · Duplicated block (9 lines × 2) · ×1

Duplicated block (9 lines × 2) eventsourcing/dcb/persistence.py:180 — eventsourcing/dcb/persistence.py:180-188 | eventsourcing/persistence.py:1550-1558 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice.

D4 · Code Duplication · Duplicated block (37 lines × 2) · ×1

Duplicated block (37 lines × 2) examples/dcb_enrolment_with_basic_objects/application.py:128 — examples/dcb_enrolment_with_basic_objects/application.py:128-164 | examples/dcb_enrolment_with_basic_objects/application.py:168-204 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. The `return` at the foot of the matched lines is the enclosing body's own terminal exit, not an early one: it moves with them unchanged, and each site calls the extracted unit from the position that `return` occupied — no decision has to be handed back and re-acted on.

D4 · Code Duplication · Duplicated block (14–15 lines × 2) · ×1

Duplicated block (14–15 lines × 2) examples/shopvertical/slices/add_item_to_cart/cmd.py:25 — examples/shopvertical/slices/add_item_to_cart/cmd.py:25-38 | examples/shopvertical/slices/remove_item_from_cart/cmd.py:24-38 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice.

D4 · Code Duplication · Duplicated block (8 lines × 3) · ×1

Duplicated block (8 lines × 3) examples/aggregate5/domainmodel.py:75 — examples/aggregate5/domainmodel.py:75-82 | examples/aggregate6/domainmodel.py:81-88 | examples/aggregate6a/domainmodel.py:139-146 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere all 3 call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made 3 times. The matched lines also transfer control out of the body holding them, which cannot survive a move into a called unit unchanged: have the extracted unit return that decision and let each site act on it. Note first that the copies are not typed on the same thing: the declarations holding them bind `event` to `Dog.Snapshot` in one and `Snapshot` in another, and the duplicated lines use it. The extracted unit therefore needs a parameter type that fits BOTH — their common supertype where they have one, or a new abstraction over them where they do not — and settling that is the step that comes BEFORE the extraction above. Where the two types are deliberately unrelated, the duplication is the price of that separation and the honest resolution is to record the decision rather than to extract.

D4 · Code Duplication · Duplicated block (12 lines × 3) · ×1

Duplicated block (12 lines × 3) examples/aggregate1/application.py:14 — examples/aggregate1/application.py:14-25 | examples/aggregate11/application.py:14-25 | examples/aggregate2/application.py:14-25 — `examples/aggregate1/application.py` and `examples/aggregate2/application.py` are one unit implemented once per sibling directory, so they are most likely parallel implementations of one contract rather than a copy of each other — this scan matched 1 separate duplicated blocks between them, totalling at least 12 lines. If both are selected at run time, neither can be retired in favour of the other, and the lines that DIFFER between them are the reason both exist. The move that pays here is to hoist the identical part into a shared location the whole family can reach and give what differs a parameter or a seam, so a change lands once instead of once per sibling; extracting one helper per block leaves every sibling to drift on its own. Note first that the copies are not typed on the same thing: `Dog` names `examples.aggregate1.domainmodel` in one and `examples.aggregate2.domainmodel` in another — different types that share a simple name, which is why the text matched. A single extracted unit cannot be given a parameter type that fits both, so unifying those types (or introducing a shared abstraction over them) is the step that has to come BEFORE the extraction above; if they are deliberately separate, the duplication is the price of that separation and the honest resolution is to record the decision rather than to extract.

D4 · Code Duplication · Duplicated block (17 lines × 2) · ×1

Duplicated block (17 lines × 2) examples/aggregate10/application.py:16 — examples/aggregate10/application.py:16-32 | examples/aggregate8/application.py:16-32 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice.

D4 · Code Duplication · Duplicated block (16 lines × 2) · ×1

Duplicated block (16 lines × 2) examples/aggregate7/application.py:18 — examples/aggregate7/application.py:18-33 | examples/aggregate9/application.py:18-34 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice.

D4 · Code Duplication · Duplicated block (8 lines × 6) · ×1

Duplicated block (8 lines × 6) examples/aggregate5/domainmodel.py:50 — examples/aggregate5/domainmodel.py:50-57 | examples/aggregate6/domainmodel.py:57-64 | examples/aggregate6a/domainmodel.py:115-122 | examples/aggregate7/domainmodel.py:58-65 | examples/aggregate7a/domainmodel.py:135-142 | examples/aggregate9/domainmodel.py:60-67 — `examples/aggregate6a/domainmodel.py` and `examples/aggregate7a/domainmodel.py` are one unit implemented once per sibling directory, so they are most likely parallel implementations of one contract rather than a copy of each other — this scan matched 4 separate duplicated blocks between them, totalling at least 34 lines. If both are selected at run time, neither can be retired in favour of the other, and the lines that DIFFER between them are the reason both exist. The move that pays here is to hoist the identical part into a shared location the whole family can reach and give what differs a parameter or a seam, so a change lands once instead of once per sibling; extracting one helper per block leaves every sibling to drift on its own. The matched lines also transfer control out of the body holding them, which cannot survive a move into a called unit unchanged: have the extracted unit return that decision and let each site act on it. Note first that the copies are not typed on the same thing: the declarations holding them bind `event` to `Dog.Registered` in one and `DogRegistered` in another, and the duplicated lines use it. The extracted unit therefore needs a parameter type that fits BOTH — their common supertype where they have one, or a new abstraction over them where they do not — and settling that is the step that comes BEFORE the extraction above. Where the two types are deliberately unrelated, the duplication is the price of that separation and the honest resolution is to record the decision rather than to extract.

P5 · DR & Backup · No DR/backup evidence · ×1

No DR/backup evidence — A persistence guard (data volume / purge-protection) was found, but no backup, geo-recovery or RTO/RPO controls were evidenced — a volume that survives a container recreate is not a tested restore from catastrophic loss.

Minor — 15 finding(s)

X10 · Duplicated predicate · Duplicated predicate · ×5

Duplicated predicate eventsourcing/dcb/postgres_tt.py:670 — `not self._has_been_stopped and not self._thread_error` appears character-identically in 2 files — eventsourcing/dcb/postgres_tt.py, eventsourcing/postgres.py. It is one line, so the duplication detector's token window never sees it; the copies drift when only one is corrected. Give the condition a name and one home.
Duplicated predicate eventsourcing/postgres.py:1048 — `not self.datastore.single_row_tracking and not self.has_checked_for_multi_row_tracking_table and self._max_tracking_id(self.table_migration_…` appears character-identically in 2 files — eventsourcing/postgres.py, eventsourcing/sqlite.py. It is one line, so the duplication detector's token window never sees it; the copies drift when only one is corrected. Give the condition a name and one home.
Duplicated predicate eventsourcing/postgres.py:953 — `not self.datastore.single_row_tracking and self.tracking_migration_current is not None` appears character-identically in 2 files — eventsourcing/postgres.py, eventsourcing/sqlite.py. It is one line, so the duplication detector's token window never sees it; the copies drift when only one is corrected. Give the condition a name and one home.
Duplicated predicate eventsourcing/postgres.py:962 — `self.datastore.single_row_tracking and self.tracking_table_exists and not self.tracking_migration_previous` appears character-identically in 2 files — eventsourcing/postgres.py, eventsourcing/sqlite.py. It is one line, so the duplication detector's token window never sees it; the copies drift when only one is corrected. Give the condition a name and one home.
Duplicated predicate eventsourcing/postgres.py:1009 — `self.tracking_table_exists and not self.tracking_migration_previous` appears character-identically in 2 files — eventsourcing/postgres.py, eventsourcing/sqlite.py. It is one line, so the duplication detector's token window never sees it; the copies drift when only one is corrected. Give the condition a name and one home.

D19 · Documentation Quality · Documentation · ×3

Documentation: contradicts the code docs/topics/release_notes.rst — The release notes document Version 9.5.6 (released 13 Oct 2026) but the latest version cited is 9.x, which was released in March 2021 and has not been updated. Update each major-version entry to reflect the current release date.
Documentation: no project overview docs/topics/examples/aggregate5.rst — The document begins with an aggregate title but does not state what the project is or what it does beyond describing the base classes and their role as frozen dataclasses. Add a one-paragraph overview stating that this repository shows how to define immutable aggregates (base classes, domain model) in two contrasting styles.
Documentation: no project overview docs/topics/examples/aggregate6.rst — The document begins with an aggregate title but does not state what the project is or what it does beyond describing the base classes and their role as frozen dataclasses. Add a one-paragraph overview stating that this repository shows how to define immutable aggregates (base classes, domain model) in two contrasting styles.

D26 · Project Cohesion · Projects may be oversized for their cohesion · ×1

Projects may be oversized for their cohesion — 1 of 1 project(s) overshoot their size bounds, lowering Project Cohesion to 0.0/10. The most over is `(repository root)` (17169 LoC, 459 module-visible types across 36 directories). Review these for cohesion — draw the boundary inside the module first (group each responsibility into its own package or directory and keep the cross-boundary members non-public), since splitting a published package moves types between packages and breaks consumers.

D36 · Supply-chain Provenance & Signing · REDACTED · ×1

REDACTED

M2 · Architecture documentation · No ADRs · ×1

No ADRs — No Architecture Decision Records found — no conventional ADR directory, no numbered `NNNN-title` documents in any markup this check reads, and nothing ADR-shaped by content. Design rationale recorded elsewhere (a design-notes tree, a mailing list, pull-request discussion) is not visible to this check and is not re-findable per decision, so a future maintainer cannot ask why one choice was made and get an answer.

M3 · Folder & project structure · No src/ separation · ×1

No src/ separation — Production code isn't grouped under a src/ folder — it's spread across several top-level directories, so there's no one place that says 'this is the product'.

M4 · Documentation accuracy · README/code drift · ×1

README/code drift docs/topics/persistence.rst:521 — docs/topics/persistence.rst links to `transcoder=transcoder`, but `docs/topics/transcoder=transcoder` does not exist. Checked without a model against the repository: its files and folders, the scripts and dependencies of every package.json, the projects, namespaces, package references and target frameworks of the .NET build, the SDK and Node pins, and the identifiers of every file that is not a document; the documents' own text never counts. A footprint generated at build time, read only by a platform, or living outside this repository is not seen, and this row is then wrong.

P3 · Security & performance tooling · No SAST · ×1

No SAST — No static application security testing detected. For this repository's stack, add bandit, `semgrep --config=p/python`, or CodeQL's python pack as a CI step. What was searched, so you can tell an absence from a miss: the 3820 CI workflow file(s) in this repository, and the scanner and linter configuration checked in beside them. A scan that runs outside CI, one configured in your forge's web UI rather than in a committed file, or a tool whose name is none of those this check carries, is not seen — if that is your case the row is wrong, and saying so is more useful than adding a second scanner.

P4 · Deployment & Rollback · No rollback/health safety · ×1

No rollback/health safety — Deployment is orchestrated by compose, but no service declares a `healthcheck:` and nothing pins a previous image to fall back to — the runtime can tell that the container is up, not that it is serving, so a bad release is harder to detect and reverse.

Minor — 1 finding(s)

D12 · Dependency Hygiene · Dependency hygiene PARTLY measured · ×1

Dependency hygiene PARTLY measured — Python dependencies read, no exact pin to grade for currency — This repository's Python dependencies were read: 1 shipped distribution(s) across 1 manifest(s) (19 development or optional declaration(s) excluded, because a consumer does not install them). Whether any of them is behind its current release is the dependency-CURRENCY question, and no declaration here carries an EXACT pin to ask it about — every one is a floor or a range, which installs the newest release it admits and therefore cannot be behind one. That is a healthy declaration style, NOT a defect and NOT a gap in this analyzer; there is simply no currency question to answer. This is NOT a finding that these dependencies are current or healthy. Lockfiles are deliberately not read (REDACTED, uv.lock, Pipfile.lock, pdm.lock): the four disagree about dev/optional membership, and misreading one would charge a test-only package a consumer never receives. Known CVEs in the same dependency graph are a separate question, reported under D30.

Appendix B — Reproduction & audit trail

Every external tool invocation behind a deep-scan dimension — the tool, its captured version, the exact command, how many findings it yielded, and a link to the retained raw output. To reproduce any finding: check out the same commit and run the command shown (repo-relative — never an absolute scratch path). The complete raw scanner output is retained verbatim under artifacts/raw/ (indexed in artifacts/raw/index.json); per-invocation exit codes and wall-clock durations are in sidecar.json — kept out of this table so the rendered report stays byte-identical across runs of the same commit.

Dimension	Tool	Version	Command	Findings	Raw output
D28 · Secrets (history)	gitleaks	—	gitleaks detect --no-banner --config /opt/gitleaks-rules/watchdog-gitleaks.toml --report-format json --report-path /tmp/watchdog-gitleaks-d51a9bbc603b4bc8a85e7d06cdd0e0a1/history.json --exit-code 0 --source .	0	artifacts/raw/gitleaks-history.json
D28 · Secrets (history)	gitleaks	—	gitleaks detect --no-git --no-banner --config /opt/gitleaks-rules/watchdog-gitleaks.toml --report-format json --report-path /tmp/watchdog-gitleaks-d51a9bbc603b4bc8a85e7d06cdd0e0a1/tree.json --exit-code 0 --source .	0	artifacts/raw/gitleaks-tree.json
D29 · Static Analysis (SAST)	semgrep	—	semgrep --config /opt/semgrep-rules/security-audit.yml --config /opt/semgrep-rules/owasp-top-ten.yml --config /opt/semgrep-rules/watchdog-sast.yml --json --quiet --timeout 10 --timeout-threshold 3 --metrics off .	7	artifacts/raw/semgrep.json
D30 · Dependency Vulnerabilities	osv-scanner	—	osv-scanner --format json --recursive --experimental-disable-plugins transitivedependency/requirements --experimental-disable-plugins dotnet/csproj --experimental-disable-plugins dotnet/nugetcpm .	3	artifacts/raw/osv-scanner.json
D31 · IaC & Container Security	trivy	—	trivy config --format json --quiet .	6	artifacts/raw/trivy-config.json
D32 · Data Compliance (PII/GDPR)	semgrep	—	semgrep: not applicable — No personal data was found crossing a boundary the PII/GDPR ruleset checks — nothing written to a log or console sink, placed in a URL or query string, or persisted to browser storage. That is a clean result for the LEAK surface only: this ruleset detects personal data escaping, it does not inventory the personal data a repository holds, so it is not evidence that this repository has no personal-data surface. The personal-data map (Appendix C) and the C1-C5 compliance cards are what speak to that.	0	—
D37 · Vulnerability-disclosure Policy	disclosure	—	disclosure: not applicable — No vulnerability-disclosure policy file found (SECURITY.md/.markdown/.rst/.txt at root or under .github/.forgejo/.gitea/docs, .well-known/security.txt). A coordinated-disclosure policy may live off-repo, so this is not evidenced rather than failed.	0	—
D40 · Network Egress Confinement	runtime-hardening	—	runtime-hardening: not applicable — No Kubernetes/orchestration workloads found in the repository manifests; network egress policy is a cluster-native control that may live at the platform/firewall layer, so there is nothing to assess here.	0	—
D41 · Kernel & Syscall Confinement	runtime-hardening	—	runtime-hardening: not applicable — No Kubernetes/orchestration workloads found in the repository manifests; seccomp/AppArmor/SELinux confinement is a workload-level control, so there is nothing to assess here.	0	—
D42 · Runtime Threat Enforcement	runtime-hardening	—	runtime-hardening: not applicable — No Kubernetes/orchestration workloads found in the repository manifests; runtime threat-detection and admission-control policy are cluster-level controls, so there is nothing to assess here.	0	—
D43 · Malicious Dependencies	osv-scanner	—	osv-scanner --format json --recursive --experimental-disable-plugins transitivedependency/requirements --experimental-disable-plugins dotnet/csproj --experimental-disable-plugins dotnet/nugetcpm .	0	artifacts/raw/osv-scanner.json

Run 01a16573-4e84-7575-8a36-cde73b2a4eba · every finding is also locatable in findings.md, and the complete scoring record (with exit codes + durations) in sidecar.json.

Findings by how serious they are

This survey was produced by

Executive summary

Top priorities

Diagnosis: what the measurements show together

Architecture: which parts of the code depend on which

At a glance — Code Health · 92% · Exemplary ·

At a glance — Architecture · 87% · Adequate · gated by D26 ·

At a glance — Maturity · 59% · Adequate · gated by M2 ·

At a glance — Readiness · 44% · Weak · gated by P3, P5 ·

At a glance — Security · 87% · Strong ·

At a glance — Performance · 90% · Exemplary ·

Security & Compliance — OWASP Top-10 mapping

Roadmap

File quality

How the grades work

Methodology & how to trust this report

Tools & methods

Run transparency — what happened this run

Limitations & what we did not check

Per-dimension blind spots

The LLM boundary

Dimensions

Frontend & cross-cutting dimensions

Reference — by lens

Appendix A — Findings (grouped)

Appendix B — Reproduction & audit trail

Downloadable artifacts