Public report of vshulcz/injex, published 22 October 2026. It has the same score, grades and number of findings as the full report. The details of security findings (where they are in the code, which known vulnerabilities and which passwords or keys were found) are left out, so nobody can use them against the project.
Public
Executive report Measured under the Code Assurance Index, an open standard for code quality, using its published scoring rules (rubric version 2026.10.5). Watchdog signed this survey and filed it in the standard's public register, where anyone can look it up by its survey ID. Check this survey → Signed and filed in the standard's public register, 22 October 2026, 12:03 UTC · Survey ID cd_ae586a04bfb849d7bdb726f45b3eeb09

vshulcz/injex

Measured 22 October 2026, 12:00 UTC, at code version ba01497

CAI score 70out of 100 At risk No change since the last survey

The score is built from these lenses. Each lens grades one area of the code, such as how easy it is to change or how well it is protected. The weakest lens counts most, so one weak area pulls the score down instead of being averaged away.

A small codebase: 3,987 lines of product code in 1 project, tests not counted · Estimated rebuild effort: about 0.1 person-years · Weakest lens: Production Readiness, 61

Findings by how serious they are

10 critical 30 serious 8 minor

17 dimensions are left out of the score. For each one, Watchdog either couldn't measure it in this code, or found no evidence of the safeguard it looks for, such as a tested backup restore. They count neither for nor against the score, and Limitations lists each one with its reason.

This survey was produced by

Watchdog
Producer
Canine Development
Analyzer
Watchdog engine 1.0.0
Measured
22 October 2026, 12:00 UTC

A measurement, not a certificate. The Code Assurance Index records a number together with the evidence it was worked out from, so anyone can recalculate it, but it doesn't certify or guarantee the code. The standard was written by Canine Development, which also builds Watchdog. It is open to any tool that implements it, and today Watchdog is the only one that does.

A critical security finding is open, such as a library with a known critical vulnerability or a password or key found in the code. The score itself is unchanged, but its band shows At risk until the finding is fixed. See the Security and Compliance lens.

The score is deterministic, which means the same code always gets the same score. Watchdog works it out with tools that follow published rules, and an AI model never decides it, so anyone who applies the same rules to the same code gets the same number. How it is done is explained under Methodology ▸

52of 56 dimensions measured by tools. The other 4 are advisory notes from an AI model, which explain the code but don't count towards the score.
36of 48 findings point to an exact file and line, so you can open each one in the code. The other 12 concern the repository as a whole, such as missing documentation.
56dimensions across 6 lenses, read from 3,987 lines of product code in 1 project.
Chapters

Executive summary

vshulcz/injex scores 70 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 61 and is rated Adequate. Its Observability 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 resolve the 1 No ADRs found finding(s) in ADR Quality and to log through `logging.getLogger(__name__)` (or structlog) with a JSON formatter at meaningful points in the modules you run, and if Production Readiness rose to 70, the score would rise from 70 to about 74.

Ten findings are critical: six in Dependency Vulnerabilities and four in Static Analysis (SAST).

Watchdog couldn't measure 16 dimensions in this code, among them Code Coverage, Test Reliability and Dependency Hygiene, so they are left out of the score. The product code is 3,987 lines, which would take an estimated 0.1 person-years, around €9,800, to rebuild.

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 61 · counts for 46%Maturity 70 · counts for 25%Code Health 80 · counts for 14%Security and Compliance 81 · counts for 8%Architecture 100 · counts for 4%Performance 100 · counts for 2%

If Production Readiness rose from 61 to 70, the lowest score rated Strong, the score would rise from 70 to about 74.

Code composition: what the lines of code are
Product code 54%Tests 46%
New since the last survey: 2 findings

These 2 critical or serious findings weren't in the previous survey, on 8 October 2026.

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.

Rebuild cost: about €9,800 · Estimate
Cost to rebuild€3,200 to €16,000, for 54 to 171 hours of work, about 0.1 person-years for one engineer
Difficulty of the problemStandard, 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×1.0 at a score of 70. 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.
SizeSmall: 3,987 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.

1
Resolve the 1 No ADRs found finding(s) in ADR Quality.
Raises the score by about 4 points · Low effort · ADR Quality
2
Log through `logging.getLogger(__name__)` (or structlog) with a JSON formatter at meaningful points in the modules you run.
Raises the score by about 7 points · Medium effort · Observability
3
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 3 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 €9,800 to build again, about 0.1 person-years of work. Its weakest lens is Production Readiness, at 61 (Adequate). 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
Resolve the 1 No ADRs found finding(s) in ADR Quality. Of all the actions in this report, it raises the score most for the work it takes: about 4 points for low effort, because it clears the 1 ADR Quality findings. 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.

31 modules, with 20 dependencies between them. Every module uses only modules listed above it, so there are no loops.

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 benchmarks.resolve_async2 benchmarks.resolve_graph3 benchmarks.resolve_scoped4 examples.clean_architecture5 examples.cli_app6 examples.cli_injection7 examples.config_injection8 examples.cyclic9 examples.factory10 examples.fastapi_app11 examples.fastapi_async12 examples.fastapi_ext13 examples.integration14 examples.resources15 examples.scan16 examples.scoped17 examples.testing18 injex.errors19 injex.ext.cli20 injex.ext.django21 injex.graph22 injex.planning23 injex.registry24 benchmarks25 injex.container26 examples.fastapi_lifespan27 injex28 injex.ext29 injex.ext.litestar30 injex.ext.starlette31 examples
1 benchmarks.resolve_async
2 benchmarks.resolve_graph
3 benchmarks.resolve_scoped
4 examples.clean_architecture
5 examples.cli_app
6 examples.cli_injection
7 examples.config_injection
8 examples.cyclic
9 examples.factory
10 examples.fastapi_app
11 examples.fastapi_async
12 examples.fastapi_ext
13 examples.integration
14 examples.resources
15 examples.scan
16 examples.scoped
17 examples.testing
18 injex.errors
19 injex.ext.cli
20 injex.ext.django
21 injex.graph
22 injex.planning
23 injex.registry
24 benchmarks111
25 injex.container32
26 examples.fastapi_lifespan1
27 injex12
28 injex.ext7
29 injex.ext.litestar1
30 injex.ext.starlette1
31 examples122211164
Uses a module listed above itPart of a loopThe module itself
1 benchmarks.resolve_async2 benchmarks.resolve_graph3 benchmarks.resolve_scoped4 examples.clean_architecture5 examples.cli_app6 examples.cli_injection7 examples.config_injection8 examples.cyclic9 examples.factory10 examples.fastapi_app11 examples.fastapi_async12 examples.fastapi_ext13 examples.integration14 examples.resources15 examples.scan16 examples.scoped17 examples.testing18 injex.errors19 injex.ext.cli20 injex.ext.django21 injex.graph22 injex.planning23 injex.registry24 benchmarks25 injex.container26 examples.fastapi_lifespan27 injex28 injex.ext29 injex.ext.litestar30 injex.ext.starlette31 examplesbenchmarks.resolve_async1benchmarks.resolve_graph2benchmarks.resolve_scoped3examples.clean_architecture4examples.cli_app5examples.cli_injection6examples.config_injection7examples.cyclic8examples.factory9examples.fastapi_app10examples.fastapi_async11examples.fastapi_ext12examples.integration13examples.resources14examples.scan15examples.scoped16examples.testing17injex.errors18injex.ext.cli19injex.ext.django20injex.graph21injex.planning22injex.registry23benchmarks24injex.container25examples.fastapi_lifespan26injex27injex.ext28injex.ext.litestar29injex.ext.starlette30examples3111132112711122211164

At a glance — Code Health · 80% · Strong ·

At a glance — Architecture · 100% · Exemplary ·

At a glance — Maturity · 70% · Strong ·

At a glance — Readiness · 61% · Adequate · gated by P2 ·

At a glance — Security · 81% · Strong ·

At a glance — Performance · 100% · Exemplary ·

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 categoryFindingsSeverity
A03:2025 — Software Supply Chain Failures11High / Critical
A05:2025 — Injection5High / Critical

Roadmap

First, implement structured logging with JSON formatting across all runnable modules and establish a dedicated folder for Architecture Decision Records to document significant design choices. Next, update the Dependabot configuration to monitor pip dependencies, ensuring they receive the same automated security and update coverage as other ecosystems. Finally, enhance the root README by adding a high-level 'Architecture' or 'How it works' section to clarify the system's overall shape for all readers.

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

Do thisHelpsEffortDimension
Resolve the 1 No ADRs found finding(s) in ADR Quality.+4.2 ptsLowADR Quality
Log through `logging.getLogger(__name__)` (or structlog) with a JSON formatter at meaningful points in the modules you run.+7.1 ptsMediumObservability
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.+3.0 ptsMediumArchitecture documentation
Dependabot is configured but does not watch `pip` — add that `package-ecosystem` entry to REDACTED so those dependencies get the same automatic update and advisory pressure as the ones it already covers.+2.2 ptsMediumSecurity & performance tooling
Add an 'Architecture' / 'How it works' section to the root README — the high-level shape.+1.5 ptsMediumDocumentation (README)
Swallowed exception (caught, then discarded)+1.3 ptsMediumException handling
Group production code under src/ (or split deliberately, e.g. backend/ + frontend/) so production and tooling code aren't mixed at the root.+1.0 ptsMediumFolder & project structure
Resolve the 2 REDACTED finding(s) in Static Analysis (SAST) — start with REDACTED (2).+0.2 ptsLowStatic Analysis (SAST)

File quality

Per-file score 0–10 — a quality signature. Of 6 files carrying findings, judged against the Production bar: 33% slop · 67% mixed · 0% near-clean.

FileScoreBandWorst signal
REDACTED0.8SlopDependency Vulnerabilities: Critical CVE: REDACTED
REDACTED2.8SlopStatic Analysis (SAST): High: REDACTED
REDACTED7.2MixedStatic Analysis (SAST): High: REDACTED
REDACTED7.2MixedStatic Analysis (SAST): High: REDACTED
injex/planning.py7.8MixedCognitive Complexity: planning._get_callable_plan (cognitive 16)
REDACTED7.9MixedStatic Analysis (SAST): Medium: REDACTED

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 — 10

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 — 30

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 — 8

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

Could not be resolved — 17

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 56 evaluated dimensions are computed purely by tools and static analysis (confidence 1.0); 4 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 — 56 dimensions across the health lenses
D1D2D3D4D6D9D13D15D17D19D20D21D22D26D27D28D29D30D34D35D36D37D43D44AX10AX2AX3AX4M1M2M3M4P1P10P2P3P4P6PF3X1X12X13X14X15X17X19X21X22X23X24X25X26X27X28X3X30

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
  1. 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, 36 of 48 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.)
  2. 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.
  3. 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.

MethodBacksVersionEvaluator
Roslyn static analysisComplexity, cohesion, coupling, dead code, API surface, layering5.3.0✓ deterministic
Native secret scannerHardcoded secrets / credentials1.0.0✓ deterministic
Watchdog duplication detector (in-process)Code duplication1.0.0✓ deterministic
Coverage (coverlet / dotnet-coverage)Line & branch coverage10.0.400✓ deterministic
NuGet / dotnetOutdated, vulnerable & deprecated dependencies10.0.400✓ deterministic
git / LibGit2SharpChurn hotspots, knowledge concentration, history2.43.0 · 0.31.0✓ deterministic
gitleaks · semgrep · trivySecrets in history, SAST, CVEs, IaC & container, PII / GDPR1.86.0 · 0.69.3✓ deterministic
LLM (sampled · advisory)Documentation quality, ADR conformance, naming — sampled over a bounded sample; advisory, never a deterministic measurementLocal LLM◐ LLM · sampled · advisory

Every finding is locatable in findings.md. Run 01a1637b-e61f-7f61-b928-80c333b531ea.

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 (`pytest --cov=injex --cov`) 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.
  • D11 Test Reliability — 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. Test source is present (.py) and this repository declares a Python test suite (repository root, 34 test files), but it was not re-run: no test result was produced. Not scored — this is a gap in the analyzer's language coverage, not a finding about this repository.
  • D12 Dependency Hygiene — 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. Not scored — 0 shipped Python distribution(s) were read, but the outdated signal needs pypi.org, and no declaration here carries an exact pin to ask about — a floor or a range installs the newest release it admits and cannot be behind one, so this dimension's own question is only partly answered. NOT a finding that these dependencies are current or healthy.
  • D14 License Compliance — 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. Not scored — this repository's package manifest is not parsed for licence data yet. A gap in the analyzer's language coverage, NOT a finding that the repository's licenses are compliant (a Python REDACTED/requirements.txt (pip/uv/Poetry)), which this pass does not parse yet — so this dimension asserts nothing about this repository's licensing in either direction.
  • 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 (6 contributor(s) across 134 commit(s) sampled, automation and bot accounts excluded). One of them holds 95% of the history; the other 5 hold 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.
  • 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's container is dependency-injector and dishka and lagom and punq and wireup, 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.
  • 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.
  • 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.
  • P5 DR & Backup — 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. No backup/snapshot/replication config, RTO/RPO or restore-procedure documentation was found — and no production persistence was detected either (no data-access packages, no data-store services, no database resources), so there is nothing in this repository whose loss a DR control would recover. If this system's data lives in a platform or ops repo we can't see, that's where the DR evidence belongs.
  • 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.
  • 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").
  • 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.
  • D20 ADR Quality: ADR quality is an LLM read of the decision records present — it cannot know about decisions made and never recorded, and its verdict is sampled and advisory.
  • 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.
  • 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.
  • D27 Navigability: Indirection/navigability is structural — it measures hops to follow a call, not whether that indirection buys real flexibility or just ceremony.
  • 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.
  • 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".
  • 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 (4): D19, D21, D22, 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 Complexity9.6 / 10Stronggated by 3 serious findings✓ 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 9.6 / 10 · rule-coverage 100% · ceiling Prevented

3 method(s) exceeded the cyclomatic complexity threshold of 15; the worst was Container._build_fast_creator at 18.

Container._build_fast_creator (cyclomatic 18)REDACTED:1174
Container._resolve_dependency_plan (cyclomatic 18)REDACTED:1395
Container.graph (cyclomatic 16)REDACTED:566

What to do

  1. Bring the 3 bodies over 15 down to 15 or less in Cyclomatic Complexity — start with Container._build_fast_creator (cyclomatic 18), Container._resolve_dependency_plan (cyclomatic 18), Container.graph (cyclomatic 16). — This score is capped by its worst body, so a finding fixed alone moves it by almost nothing — the next one down takes its place. Refactoring these 3 together lifts Cyclomatic Complexity from 9.6 to about 10.0/10, projected with the scoring formula itself and assuming each lands exactly at 15.
  2. 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.

D2 · Cognitive Complexity8.5 / 10Strong✓ 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 8.5 / 10 · rule-coverage 100% · ceiling Prevented

5 method(s) exceeded the cognitive complexity threshold of 15; the worst was Container.graph at 33.

Container.graph (cognitive 33)REDACTED:566
Container._resolve_dependency_plan (cognitive 30)REDACTED:1395
Container._build_fast_creator (cognitive 26)REDACTED:1174
Container._validate_callable (cognitive 17)REDACTED:727
planning._get_callable_plan (cognitive 16)injex/planning.py:182

What to do

  1. Bring the 5 bodies over 15 down to 15 or less in Cognitive Complexity — start with Container.graph (cognitive 33), Container._resolve_dependency_plan (cognitive 30), Container._build_fast_creator (cognitive 26). — This score is capped by its worst body, so a finding fixed alone moves it by almost nothing — the next one down takes its place. Refactoring these 5 together lifts Cognitive Complexity from 8.5 to about 10.0/10, projected with the scoring formula itself and assuming each lands exactly at 15.
  2. 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.

D3 · God Classes9.2 / 10Stronggated by 2 serious findings✓ 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 9.2 / 10 · rule-coverage 100% · ceiling Prevented

2 god class(es) detected.

FileTooLong: REDACTEDREDACTED
TooManyMethods: ContainerREDACTED:180

What to do

  1. Resolve the 1 FileTooLong finding(s) in God Classes — start with REDACTED. — One of this dimension's main actionable groups (1 warning-level).
  2. Resolve the 1 TooManyMethods finding(s) in God Classes — start with REDACTED. — One of this dimension's main actionable groups (1 warning-level).
  3. 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.

D4 · Code Duplication9.6 / 10Stronggated by 6 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 9.6 / 10 · rule-coverage 100% · ceiling Verified

5 duplicated block group(s) detected. One further row reports members as variants of one another; it aggregates block groups already counted above and is not itself counted.

Near-duplicate member pair (57 shared lines)REDACTED:874
Duplicated block (35–36 lines × 2)injex/planning.py:144
Duplicated block (23–24 lines × 2)REDACTED:964
Duplicated block (11–14 lines × 2)REDACTED:903
Duplicated block (13 lines × 2)REDACTED:913

+ 1 more group(s) — more in Appendix A; the complete list is findings.md.

What to do

  1. Resolve the 1 Near-duplicate member pair (57 shared lines) finding(s) in Code Duplication — start with REDACTED. — One of this dimension's main actionable groups (1 warning-level).
  2. Resolve the 1 Duplicated block (35–36 lines × 2) finding(s) in Code Duplication — start with planning.py. — One of this dimension's main actionable groups (1 warning-level).
  3. Resolve the 1 Duplicated block (23–24 lines × 2) finding(s) in Code Duplication — start with REDACTED. — One of this dimension's main actionable groups (1 warning-level).
  4. 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.

D6 · Cohesion (LCOM4)10.0 / 10Exemplary✓ 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 10.0 / 10 · rule-coverage 100% · ceiling Verified

0 of 9 classes have LCOM4 above 3.

✓ On the Gold path — maintain.

Detailed fixes: d6_recommendation.md.

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

206 test methods: 206 unit, 0 integration, 0 BDD, 0 e2e. The Python suite contributes 206 test function(s) across 32 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.

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.

D15 · Churn × Complexity Hotspots9.9 / 10Stronggated by 1 serious finding✓ 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 9.9 / 10 · rule-coverage 100% · ceiling Documented

Top hotspots: REDACTED (25×18=450)

Hotspot: REDACTEDREDACTED:1174

What to do

  1. Resolve the 1 Hotspot finding(s) in Churn × Complexity Hotspots — start with REDACTED. — One of this dimension's main actionable groups (1 warning-level).

Detailed fixes: d15_recommendation.md · top locations in Appendix A, every location in findings.md.

D17 · Explicit Debt10.0 / 10Exemplary○ Nothing flagged

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 10.0 / 10 · rule-coverage 100% · ceiling Prevented

0 deducted task-comment markers across 3987 LoC (0.0/KLoC) → score 10.0. 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.

✓ On the Gold path — maintain.

Detailed fixes: d17_recommendation.md.

D19 · Documentation QualityExemplary◐ 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 Exemplary / 10 · rule-coverage 100% · ceiling Documented

Injex's documentation is clear and complete for a project that claims to be tiny typed dependency injection with zero runtime dependencies. The repository root README gives an overview of what Injex does (catching missing dependencies and cycles before startup) plus installation, usage, and a quick start example; benchmarks/README documents the benchmarks directory, not the repo, so its content is scoped appropriately; architecture/design docs are present and cover API reference, async resolution, comparison guide, FastAPI dependency integration, and migration from factories modules. The visible material is well-structured with headings and an outline for every named document. Injex's documentation is clear and complete: the READMEs cover installation/usage (the root README plus two README docs), architecture/design docs (architecture/Docs markdown files), a detailed performance benchmark with local results, recipes for container composition across entry points, releasing instructions, resolve-all usage, validation, why-injex rationale, an API reference, async support, and a comparison guide. The visible content is well-structured and the outline confirms every section present. The documentation is excellent: it contains two READMEs (one focused on getting started with Injex, one covering migration from factories) plus architecture/Docs markdown files for a total of 30 documents. The READMEs are well-structured and complete for their directories — the get-started README explains what Injex does and gives install/register/validate/resolution steps with code examples; the root index.html overview is clear, covering scope (typed DI container), features (zero runtime deps, PEP 561 typed, composition root validation), and a comparison guide. The architecture docs are well written for an internals doc set.

✓ On the Gold path — maintain.

Detailed fixes: d19_recommendation.md.

D20 · ADR Quality0.0 / 10Critical✓ Tool-verified

What it measures: Whether architecture decisions are recorded well (context, decision, consequences).

Method: Per-ADR judgment by language model at low temperature with two-pass stability; confidence is share of ADRs evaluated; enforcement-field presence detected deterministically. Advisory.

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

No architecture decision records were found.

No ADRs found

What to do

  1. Resolve the 1 No ADRs found finding(s) in ADR Quality. — One of this dimension's main actionable groups (1 recommendation-level).

Detailed fixes: d20_recommendation.md · top locations in Appendix A, every location in findings.md.

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.

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 43 exposed types.

Redundant registration methods. `register` accepts a `lifestyle` string argument, while `add_singleton`, `add_transient`, and `add_scoped` hardcode the lifestyle. This creates two ways to achieve the same result (e.g., `register(..., 'singleton')` vs `add_singleton(...)`), leading to API confusion and potential inconsistency if the string values don't match the enum/constant definitions.
Redundant factory registration methods. Similar to the instance registration issue, `register_factory` takes a `lifestyle` string, while the specific `add_*_factory` methods hardcode it. This duplicates intent and API surface.
Conflicting overload signatures. The class defines three overloads for `resolve`, but the third overload `interface: type | str` is a superset of the first two. In Python typing, this makes the first two overloads unreachable or ambiguous for type checkers, as the third one will always match. It also creates inconsistency between `type[T]` (returning `T`) and `type | str` (returning `Any`), which is confusing for users expecting type safety.
Conflicting overload signatures. Same issue as `resolve`. The `type | str` overload shadows the more specific `type[T]` overload, breaking type inference for users who pass a type hint.
Inconsistent naming and purpose for injection markers. `cli.Inject` is a function returning `Any` (likely a marker), `tasks.inject` is a decorator factory taking a container, and `planning.inject` is a decorator taking a function. The name `inject` is used for different mechanisms (decorator vs marker) across modules, and `Inject` (capitalized) is used in CLI. This is confusing for users trying to understand how to inject dependencies in different contexts.

What to do

  1. Resolve the 1 Redundant registration methods. `register` accepts a `lifestyle` string… finding(s) in Internal API Consistency. — One of this dimension's main actionable groups (1 warning-level).
  2. Resolve the 1 Redundant factory registration methods. Similar to the instance… finding(s) in Internal API Consistency. — One of this dimension's main actionable groups (1 warning-level).
  3. Resolve the 1 Conflicting overload signatures. The class defines three overloads for… 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.

D26 · Project Cohesion10.0 / 10Exemplary✓ 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 10.0 / 10 · rule-coverage 100% · ceiling Documented

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

✓ On the Gold path — maintain.

Detailed fixes: d26_recommendation.md.

D27 · Navigability8.4 / 10Strong✓ Tool-verified

What it measures: How far you must trace to follow a call — low indirection and co-located slices read easier.

Method: Call indirection (interface hops, cross-namespace calls, slice-locality scaled) over a sampled set of method invocations, size-aware baseline. Sampled; confidence discounted by symbol-resolution gaps. C# also names each pass-through layer (a class whose every public method only forwards its own parameters to one collaborator) as a located finding; the score is not affected.

Coverage: Slice locality from the first namespace segments, SAMPLED (≤400 methods) — not exhaustive.

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

70 % of calls cross a namespace and 1 % go through an interface, but 55 % of collaborators are co-located — so following a call takes several hops. Baseline: small — navigation cost is tolerated.

Scattered collaborators

What to do

  1. Resolve the 1 Scattered collaborators finding(s) in Navigability. — One of this dimension's main actionable groups (1 recommendation-level).

Detailed fixes: d27_recommendation.md · top locations in Appendix A, every location in findings.md.

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.

D29 · Static Analysis (SAST)4.8 / 10Weak✓ 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 4.8 / 10 · rule-coverage 100% · ceiling Documented

5 finding(s): 0 critical, 4 high, 1 medium, 0 low. semgrep hit a parse error in 3 file(s) — `site/docs/async.html` (lines 74–80, lines 99–106, lines 119–123, …), `site/docs/fastapi-depends.html` (lines 84–91, lines 100–101, lines 126–127), `site/docs/getting-started.html` (lines 67–82) — so no absence of findings in the named regions is evidence of anything; rows reported elsewhere in those files are real. Fix the syntax error (or exclude the file deliberately) and re-scan to cover them.

REDACTED
REDACTED
REDACTED
REDACTED

What to do

  1. Resolve the 2 REDACTED finding(s) in Static Analysis (SAST) — start with REDACTED (2). — One of this dimension's main actionable groups (2 issue-level).
  2. Resolve the 1 REDACTED finding(s) in Static Analysis (SAST) — start with REDACTED. — One of this dimension's main actionable groups (1 issue-level).
  3. Resolve the 1 REDACTED finding(s) in Static Analysis (SAST) — start with REDACTED. — One of this dimension's main actionable groups (1 issue-level).

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

D30 · Dependency Vulnerabilities4.4 / 10Weak✓ 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 4.4 / 10 · rule-coverage 100% · ceiling Documented

9 finding(s): 2 critical, 4 high, 3 medium, 0 low.

REDACTED
REDACTED
REDACTED
REDACTED
REDACTED

What to do

  1. Resolve the 3 High CVE finding(s) in Dependency Vulnerabilities — start with REDACTED (3). — One of this dimension's main actionable groups (3 issue-level).
  2. Resolve the 1 Critical CVE finding(s) in Dependency Vulnerabilities — start with REDACTED. — One of this dimension's main actionable groups (1 issue-level).
  3. 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.

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 12 of the 23 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.

D35 · Change Coupling10.0 / 10Exemplary✓ 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 10.0 / 10 · rule-coverage 100% · ceiling Documented

No strong hidden change-coupling between production files.

✓ On the Gold path — maintain.

Detailed fixes: d35_recommendation.md.

D36 · Supply-chain Provenance & Signing7.5 / 10Strong✓ Tool-verified

What it measures: Whether the build pipeline provides supply-chain integrity — generated provenance/attestation, signed artifacts (cosign/sigstore), an SBOM, and pinned build actions. Presence of the configuration, not a runtime guarantee.

Method: Supply-chain provenance/signing read deterministically from CI/build config (.github/workflows, .gitlab-ci.yml, azure-pipelines, Jenkinsfile, .circleci) + the release surface: four signals — generated provenance/attestation (SLSA/in-toto/actions-attest), artifact signing (cosign/sigstore/gitsign), an SBOM (syft/sbom-action/*.spdx.json/*.cdx.json), and SHA-pinned build actions — scored 10·present/denom. NotApplicable without a build pipeline. Detects configuration presence, not runtime enforcement.

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

3/4 supply-chain integrity signals present (provenance, signing, SBOM, pinned actions).

REDACTED
REDACTED

What to do

  1. Resolve the 1 REDACTED finding(s) in Supply-chain Provenance & Signing. — One of this dimension's main actionable groups (1 recommendation-level).
  2. Resolve the 1 REDACTED finding(s) in Supply-chain Provenance & Signing. — One of this dimension's main actionable groups (1 recommendation-level).

Detailed fixes: d36_recommendation.md · top locations in Appendix A, every location in findings.md.

D37 · Vulnerability-disclosure Policy10.0 / 10Exemplary✓ Tool-verified

What it measures: Whether the repository publishes a coordinated-vulnerability-disclosure policy (SECURITY.md or security.txt) with a reporting contact, so finders know how to report a vulnerability. Presence of a policy file with a contact, not whether the policy is adequate or honoured.

Method: Vulnerability-disclosure policy read deterministically from the repo: a SECURITY.md (root/.github/docs) or .well-known/security.txt / security.txt, regex-checked for a reporting contact (email / URL / mailto). Present + contact → 10; present without a contact → 4; NotApplicable when no policy file exists (it may live off-repo). Detects the policy file's presence + contact, not its adequacy.

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

A vulnerability-disclosure policy (SECURITY.md) is published with a reporting contact.

✓ On the Gold path — maintain.

Detailed fixes: d37_recommendation.md.

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.

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 0 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.

Frontend & cross-cutting dimensions

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

AX10 · Code composition10.0 / 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.

What to do

  • The domain core is a small share of production code, but most of the rest matched no layer vocabulary at all — so this is not yet an anemic-domain finding. The namespace/path convention could not place that code, which makes the composition above a statement about the naming, not about the design. Name the layers (or check that the repository's conventions differ from the ones this check knows) before reading a thin domain into it.
AX2 · Stateful singletons10.0 / 10Exemplary✓ Tool-verified

Other · Architecture — Whether singleton services avoid mutable shared instance state that concurrent callers would race on.

Method: Roslyn scan: singleton field mutations unguarded by lock or Interlocked, per type; syntax-based guard detection. Deterministic, traceable per field.

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.

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.

M1 · Documentation (README)7.3 / 10Strong✓ 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

  • Add an 'Architecture' / 'How it works' section to the root README — the high-level shape.
M2 · Architecture documentation5.0 / 10Adequate✓ 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.
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.
M4 · Documentation accuracy10.0 / 10Exemplary◐ 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.

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.

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.

P2 · Observability0.0 / 10Critical✓ 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.

  • No logging call was found in the 20 Python production file(s) this check read across 1 module(s). Each was searched for its ecosystem's logging libraries (Python: logging, structlog, loguru) and for a call on a receiver named `log`/`logger` (or ending in `Logger`/`_logger`) with a level verb. It cannot see logging through a repo-local wrapper named otherwise, or in source it did not read — this is 'no logging found by this walk', not a verdict that nothing here logs. If it is right, production issues will be hard to diagnose.

What to do

  • Log through `logging.getLogger(__name__)` (or structlog) with a JSON formatter at meaningful points in the modules you run.
  • Consider OpenTelemetry tracing/metrics (opentelemetry-sdk) and a health-check endpoint (a /health route) for operability.
P3 · Security & performance tooling7.0 / 10Strong✓ 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.

What to do

  • Dependabot is configured but does not watch `pip` — add that `package-ecosystem` entry to REDACTED so those dependencies get the same automatic update and advisory pressure as the ones it already covers.
  • Add gitleaks/trufflehog in CI to block PRs that introduce committed secrets.
P4 · Deployment & Rollback7.0 / 10Strong✓ 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.

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.

PF3 · Async & latency hygiene10.0 / 10Exemplary✓ Tool-verified

Readiness · Performance — Whether asynchronous code stays responsive — it avoids sync-over-async blocking (a .NET .Wait()/.GetAwaiter().GetResult(), a time.sleep or blocking HTTP call inside a Python coroutine, a *Sync call inside an async JavaScript function, block_on inside a Rust async fn, runBlocking inside a Kotlin suspend function, block() inside a Reactor publisher) that stalls a thread or event loop and risks deadlock, and, where the code is a reusable library on .NET, awaits with ConfigureAwait(false) so it never captures and stalls its caller's context.

Method: Production-source scan: sync-over-async blocking counted everywhere — .Wait()/.GetAwaiter().GetResult() in .NET; off .NET, read from the language model, a blocking call inside an async function (Python, TS/JS, Rust, Kotlin, Swift, Dart) or inside a Java method returning a Reactor Mono/Flux or a Scala method returning a Future or effect — and, for a .NET library with ≥5 awaits, the share of awaits using ConfigureAwait(false). Deterministic, syntax/text detection.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

X3 · Exception handling5.2 / 10Adequate✓ Tool-verified

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.

  • `except Exception` takes every exception and records none of it — the body neither logs it, rethrows it, nor even names it, so the failure is discarded as completely as by an empty catch and only the substituted value survives. Log it through whatever this codebase already uses to report problems, narrow the catch to the exception this call can actually raise, or say in a comment on the catch why the failure genuinely cannot matter. (×3) — injex/planning.py:139, injex/planning.py:190, REDACTED:745

What to do

  • Swallowed exception (caught, then discarded)
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.

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.

LensScoreRatingImpact
Code Health80%StrongSolid.
Architecture100%ExemplarySolid.
Maturity70%StrongSolid.
Readiness61%Adequate — gated by P2Capped at Fair by a Critical contributor — resolve it before relying on this lens.
Security81%StrongSolid.
Performance100%ExemplaryStrongest area.
Unscored — 1 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.

  • X10 Duplicated predicate — 2 observation(s) recorded · Advisory — this card reports evidence and never carries a score.
Not evidenced — 1 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.

  • P5 DR & Backup — not evidenced — repo shows no backup/RTO/RPO controls; absence of evidence is not evidence of a working control
Not included — 62 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
  • AX5 Architecture & structure — not assessed — architecture style/structure is computed from a project graph (projects, types, module namespaces) 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
  • 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
  • AXB1 Runtime evidence locked — no reproducible boot — This repository has nothing the runtime tiers could boot or serve — no markup, no UI framework or web-server dependency, no UI component source, no native UI project and no API definition — nothing here is a surface to boot — so runtime a11y/egress/header evidence has no subject here. Not applicable: this is neither a gap in the scan nor a finding about your code.
  • AXB2 Runtime readiness — Advisory — this card reports evidence and never carries a score, so there is nothing missing here.
  • 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.
  • C3 Audit Trail — No personal data detected in a persisted data model — no PII-named field (email, first_name, date_of_birth, phone, …) or stored credential in a Django, SQLAlchemy, SQLModel, Peewee, Tortoise or MongoEngine model, a migration or a SQL schema — and no database or data-store client (Django ORM, SQLAlchemy, psycopg, PyMongo, …) in the source either, so this repository keeps no sensitive data whose changes an audit trail would record. If it does (through a store configured outside this repository, for instance), the trail belongs to wherever that data is stored.
  • C4 Data Retention — No personal data detected in a persisted data model — no PII-named field (email, first_name, date_of_birth, phone, …) or stored credential on a Django, SQLAlchemy, SQLModel, Peewee, Tortoise or mongoengine model, in a migration or in a SQL schema — and no database or data-store client (django.db, sqlalchemy, psycopg2, pymongo, sqlite3, …) imported either, so this repository keeps no personal data whose lifetime a retention limit would bound.
  • C5 Data-Subject Rights — No personal data detected in a persisted data model — no PII-named field (email, first_name, date_of_birth, phone, …) or stored credential on a Django, SQLAlchemy, SQLModel, Peewee, Tortoise or mongoengine model, in a migration or in a SQL schema — and no database or data-store client (django.db, sqlalchemy, psycopg2, pymongo, sqlite3, …) imported either, so this repository keeps no personal data for a data subject to erase, export or consent over.
  • D10 Test Quality — ~3416 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.
  • D11 Test Reliability — Test reliability not included — the .py suite was found but not re-run
  • D12 Dependency Hygiene — Not scored — 0 shipped Python distribution(s) were read, but the outdated signal needs pypi.org, and no declaration here carries an exact pin to ask about — a floor or a range installs the newest release it admits and cannot be behind one, so this dimension's own question is only partly answered. NOT a finding that these dependencies are current or healthy.
  • D14 License Compliance — Package manifest not parsed for licence data — analyzer language-coverage gap
  • 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.
  • D23 Boundary Type-Coupling — No bounded-context organisation was detected either — neither a context-shaped layout, nor 2+ sibling source directories each declaring an aggregate root, nor 2+ projects each declaring an entity of their own. Declaring this codebase's bounded contexts (≥2) would let cross-boundary type coupling be assessed. Declare them in `.codehealth/config.yaml` at the repository root (create it if absent), mapping each context name to the module-path or namespace prefixes that belong to it — e.g. `architecture:` → `contexts:` → `Billing: ["src/billing", "Acme.Billing"]`, `Catalog: ["src/catalog", "Acme.Catalog"]`.
  • D24 Comment Value — No inline comments to assess — comment value is not applicable here.
  • D25 ADR Conformance — no ADRs to check
  • D31 IaC & Container Security — No Infrastructure-as-Code or container manifests found (Dockerfile, Docker Compose, Terraform, Kubernetes/Helm, CloudFormation, ARM, Bicep, Ansible); nothing to scan.
  • 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.
  • 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 — not scored — this repository shows only 1 of the 3 signals this lens looks for (15 value object(s))
  • 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 — no outbound HTTP usage detected — no HTTP client call or construction in the Python source (service entry point: injex/ext/starlette.py:21 ())
  • 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
  • PF1 Benchmark discipline — Not applicable: no benchmark suite was found. This check searched for a pytest-benchmark or pytest-codspeed dependency with tests taking the `benchmark` fixture, an asv.conf.json with its `time_`/`mem_`/`peakmem_` benchmarks, or a pyperf Runner, and for a `*benchmark*` script that this repository's CI runs. Benchmarks are credited as a bonus, so their absence is neither scored nor deducted.
  • 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.
  • 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 — 10 finding(s)
D30 · Dependency Vulnerabilities · High CVE · ×3
  • REDACTED
  • REDACTED
  • REDACTED
D29 · Static Analysis (SAST) · REDACTED
  • REDACTED
  • REDACTED
D29 · Static Analysis (SAST) · REDACTED · ×1
  • REDACTED
D29 · Static Analysis (SAST) · REDACTED · ×1
  • REDACTED
D30 · Dependency Vulnerabilities · Critical CVE · ×1
  • REDACTED
D30 · Dependency Vulnerabilities · Critical vulnerability · ×1
  • REDACTED
D30 · Dependency Vulnerabilities · High vulnerability · ×1
  • REDACTED
Serious — 30 finding(s)
D30 · Dependency Vulnerabilities · Medium CVE · ×3
  • REDACTED
  • REDACTED
  • REDACTED
X3 · Exception handling · Swallowed exception (caught, then discarded) · ×3
  • Swallowed exception (caught, then discarded) injex/planning.py:139 — `except Exception` takes every exception and records none of it — the body neither logs it, rethrows it, nor even names it, so the failure is discarded as completely as by an empty catch and only the substituted value survives. Log it through whatever this codebase already uses to report problems, narrow the catch to the exception this call can actually raise, or say in a comment on the catch why the failure genuinely cannot matter.
  • Swallowed exception (caught, then discarded) injex/planning.py:190 — `except Exception` takes every exception and records none of it — the body neither logs it, rethrows it, nor even names it, so the failure is discarded as completely as by an empty catch and only the substituted value survives. Log it through whatever this codebase already uses to report problems, narrow the catch to the exception this call can actually raise, or say in a comment on the catch why the failure genuinely cannot matter.
  • Swallowed exception (caught, then discarded) REDACTED:745 — `except Exception` takes every exception and records none of it — the body neither logs it, rethrows it, nor even names it, so the failure is discarded as completely as by an empty catch and only the substituted value survives. Log it through whatever this codebase already uses to report problems, narrow the catch to the exception this call can actually raise, or say in a comment on the catch why the failure genuinely cannot matter.
D1 · Cyclomatic Complexity · Container._build_fast_creator (cyclomatic 18) · ×1
  • Container._build_fast_creator (cyclomatic 18) REDACTED:1174 — Container._build_fast_creator has cyclomatic complexity 18 (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 · Container._resolve_dependency_plan (cyclomatic 18) · ×1
  • Container._resolve_dependency_plan (cyclomatic 18) REDACTED:1395 — Container._resolve_dependency_plan has cyclomatic complexity 18 (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 · Container.graph (cyclomatic 16) · ×1
  • Container.graph (cyclomatic 16) REDACTED:566 — Container.graph has cyclomatic complexity 16 (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.
D15 · Churn × Complexity Hotspots · Hotspot · ×1
  • Hotspot: REDACTED REDACTED:1174 — REDACTED changed 25 times in last 90 days, and the most complex body those changes touched has cyclomatic complexity 18 in Container._build_fast_creator at line 1174. 3 of those changes were fix/bug commits, and the other 22 changed it for other reasons — this file is under both repair and feature pressure. Before the next change lands here, make sure the area it touches is under test, then split that area out of the file so the following change is smaller than this one — a file this often edited pays the complexity back every time. Counted over 2026-04-29..2026-07-28, the 90 days ending at the analysed commit. Reproduce with `git log --since='2026-04-29 00:52:15 +03:00' --until='2026-07-28 00:52:15 +03:00' --full-history --no-merges -- REDACTED`: merges are excluded because a merge re-states changes already counted at their own commits, and history is NOT path-simplified because a change that reached the file through a merged branch is still a change to it. That command counts raw commits and can read HIGHER than this row, which counts a cherry-picked re-land, and a revert together with the commit it undoes, once each — a difference of several commits on a file whose history was re-landed or reverted inside the window.
D2 · Cognitive Complexity · Container.graph (cognitive 33) · ×1
  • Container.graph (cognitive 33) REDACTED:566 — Container.graph has cognitive complexity 33 (threshold 15). Drivers by points: if/else 7 (19 pts), loops 3 (6 pts), boolean chains 4, ternaries 1 (4 pts) (nesting depth added 18). 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 · Container._resolve_dependency_plan (cognitive 30) · ×1
  • Container._resolve_dependency_plan (cognitive 30) REDACTED:1395 — Container._resolve_dependency_plan has cognitive complexity 30 (threshold 15). Drivers by points: if/else 16 (29 pts), boolean chains 1 (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.
D2 · Cognitive Complexity · Container._build_fast_creator (cognitive 26) · ×1
  • Container._build_fast_creator (cognitive 26) REDACTED:1174 — Container._build_fast_creator has cognitive complexity 26 (threshold 15). Drivers by points: if/else 14 (23 pts), boolean chains 2, loops 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 · Container._validate_callable (cognitive 17) · ×1
  • Container._validate_callable (cognitive 17) REDACTED:727 — Container._validate_callable has cognitive complexity 17 (threshold 15). Drivers by points: if/else 5 (12 pts), boolean chains 2, error handling 2, loops 1 (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.
D2 · Cognitive Complexity · planning._get_callable_plan (cognitive 16) · ×1
  • planning._get_callable_plan (cognitive 16) injex/planning.py:182 — planning._get_callable_plan has cognitive complexity 16 (threshold 15). Drivers by points: if/else 3 (9 pts), error handling 2 (3 pts), boolean chains 2, loops 1 (2 pts) (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.
D22 · Internal API Consistency · Redundant registration methods. `register` accepts a `lifestyle` string argument, while `add_singleton`, `add_transient`, and `add_scoped` hardcode the lifestyle. This creates two ways to achieve the same result (e.g., `register(..., 'singleton')` vs `add_singleton(...)`), leading to API confusion and potential inconsistency if the string values don't match the enum/constant definitions. · ×1
  • Redundant registration methods. `register` accepts a `lifestyle` string argument, while `add_singleton`, `add_transient`, and `add_scoped` hardcode the lifestyle. This creates two ways to achieve the same result (e.g., `register(..., 'singleton')` vs `add_singleton(...)`), leading to API confusion and potential inconsistency if the string values don't match the enum/constant definitions. — Remove `register` and the specific `add_*` methods. Use a single `add` or `register` method that accepts a `Lifestyle` enum (from `LifeStyle`) instead of a string, or keep only the specific `add_singleton/add_transient/add_scoped` methods and remove the generic `register` if the enum approach is too verbose. (signatures: Container.register(self, interface: type, implementation: type | None, lifestyle: str, name: str | None): None | Container.add_singleton(self, interface: type, implementation: type | None, name: str | None): None | Container.add_transient(self, interface: type, implementation: type | None, name: str | None): None | Container.add_scoped(self, interface: type, implementation: type | None, name: str | None): None)
D22 · Internal API Consistency · Redundant factory registration methods. Similar to the instance registration issue, `register_factory` takes a `lifestyle` string, while the specific `add_*_factory` methods hardcode it. This duplicates intent and API surface. · ×1
  • Redundant factory registration methods. Similar to the instance registration issue, `register_factory` takes a `lifestyle` string, while the specific `add_*_factory` methods hardcode it. This duplicates intent and API surface. — Unify into a single `register_factory` method that accepts a `Lifestyle` enum, or remove the generic `register_factory` in favor of the specific methods if the enum is not preferred. (signatures: Container.register_factory(self, interface: type, factory: Callable[..., Any], lifestyle: str, name: str | None): None | Container.add_singleton_factory(self, interface: type, factory: Callable[..., Any], name: str | None): None | Container.add_transient_factory(self, interface: type, factory: Callable[..., Any], name: str | None): None | Container.add_scoped_factory(self, interface: type, factory: Callable[..., Any], name: str | None): None)
D22 · Internal API Consistency · Conflicting overload signatures. The class defines three overloads for `resolve`, but the third overload `interface · ×1
  • Conflicting overload signatures. The class defines three overloads for `resolve`, but the third overload `interface: type | str` is a superset of the first two. In Python typing, this makes the first two overloads unreachable or ambiguous for type checkers, as the third one will always match. It also creates inconsistency between `type[T]` (returning `T`) and `type | str` (returning `Any`), which is confusing for users expecting type safety. — Remove the `interface: str` and `interface: type | str` overloads. If string-based resolution is supported, it should likely return `Any` or be handled via a separate method. If only type-based resolution is intended, remove the string overloads entirely. The current signature set is technically broken for static type checking. (signatures: Scope.resolve(self, interface: type[T], name: str | None): T | Scope.resolve(self, interface: str, name: str | None): Any | Scope.resolve(self, interface: type | str, name: str | None): Any | Container.resolve(self, interface: type[T], name: str | None): T | Container.resolve(self, interface: str, name: str | None): Any | Container.resolve(self, interface: type | str, name: str | None): Any)
D22 · Internal API Consistency · Conflicting overload signatures. Same issue as `resolve`. The `type | str` overload shadows the more specific `type[T]` overload, breaking type inference for users who pass a type hint. · ×1
  • Conflicting overload signatures. Same issue as `resolve`. The `type | str` overload shadows the more specific `type[T]` overload, breaking type inference for users who pass a type hint. — Align with the `resolve` method fix: remove ambiguous overloads or ensure they are ordered correctly and distinct. (signatures: Scope.resolve_all(self, interface: type[T], name: str | None): list[T] | Scope.resolve_all(self, interface: str, name: str | None): list[Any] | Scope.resolve_all(self, interface: type | str, name: str | None): list[Any] | Container.resolve_all(self, interface: type[T], name: str | None): list[T] | Container.resolve_all(self, interface: str, name: str | None): list[Any] | Container.resolve_all(self, interface: type | str, name: str | None): list[Any])
D22 · Internal API Consistency · Inconsistent naming and purpose for injection markers. `cli.Inject` is a function returning `Any` (likely a marker), `tasks.inject` is a decorator factory taking a container, and `planning.inject` is a decorator taking a function. The name `inject` is used for different mechanisms (decorator vs marker) across modules, and `Inject` (capitalized) is used in CLI. This is confusing for users trying to understand how to inject dependencies in different contexts. · ×1
  • Inconsistent naming and purpose for injection markers. `cli.Inject` is a function returning `Any` (likely a marker), `tasks.inject` is a decorator factory taking a container, and `planning.inject` is a decorator taking a function. The name `inject` is used for different mechanisms (decorator vs marker) across modules, and `Inject` (capitalized) is used in CLI. This is confusing for users trying to understand how to inject dependencies in different contexts. — Standardize the naming. If `Inject` is a marker, use it consistently. If `inject` is a decorator, ensure the signature is consistent. Consider renaming `cli.Inject` to `cli.InjectMarker` or similar to distinguish it from the `inject` decorator in `tasks` and `planning`. (signatures: cli.Inject(): Any | tasks.inject(container: Container): Callable[[Callable[..., T]], Callable[..., T]] | planning.inject(func: Callable[..., Any]): Callable[..., Any])
D29 · Static Analysis (SAST) · REDACTED · ×1
  • REDACTED
D3 · God Classes · FileTooLong · ×1
  • FileTooLong: REDACTED REDACTED — FileTooLong — 1482 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 982 over it, 2.96× 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.
D3 · God Classes · TooManyMethods · ×1
  • TooManyMethods: Container REDACTED:180 — TooManyMethods — 75 methods. The bar is 30 methods; this is 45 over it, 2.50× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
D4 · Code Duplication · Near-duplicate member pair (57 shared lines) · ×1
  • Near-duplicate member pair (57 shared lines) REDACTED:874 — REDACTED:874-998 | REDACTED:1022-1172 — These two members are variants of one another: 57 of their lines are already reported as duplicated blocks below, spread through both bodies rather than gathered into one. Read them as a single construct written twice. The repair is at the members' grain — factor the shared pipeline into one implementation the two call with their differences as parameters or as an injected step, or, where the difference is systematic (sync against async, one transport against another), generate one from the other. Extracting the individual blocks below is not the same fix: it leaves the two bodies in place and the next edit still has to be made twice.
D4 · Code Duplication · Duplicated block (35–36 lines × 2) · ×1
  • Duplicated block (35–36 lines × 2) injex/planning.py:144 — injex/planning.py:144-179 | injex/planning.py:195-229 — 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 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 (23–24 lines × 2) · ×1
  • Duplicated block (23–24 lines × 2) REDACTED:964 — REDACTED:964-986 | REDACTED:1135-1158 — 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 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. ★ These copies have DRIFTED, and that is worth reading before extracting anything: just after the matched lines, `REDACTED:1160` calls `delegate` and `REDACTED:988` 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 (11–14 lines × 2) · ×1
  • Duplicated block (11–14 lines × 2) REDACTED:903 — REDACTED:903-916 | REDACTED:1037-1047 — 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. Read the line range as the matched WINDOW rather than a finished unit: at `REDACTED:903` it does not close everything it opens, 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. Note that the copies do not run to the end of the range shown: their LAST lines are different code, not the same code under different names — the matched region ends inside that line. Extract the lines above it, and read the last line of each site separately.
D4 · Code Duplication · Duplicated block (13 lines × 2) · ×1
  • Duplicated block (13 lines × 2) REDACTED:913 — REDACTED:913-925 | REDACTED:1086-1098 — 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) · ×1
  • Duplicated block (11 lines × 2) REDACTED:988 — REDACTED:988-998 | REDACTED:1162-1172 — 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 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. ★ These copies have DRIFTED, and that is worth reading before extracting anything: just before the matched lines, `REDACTED:1160` calls `delegate` and `REDACTED:986` 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.
P2 · Observability · No structured logging · ×1
  • No structured logging — No logging call was found in the 20 Python production file(s) this check read across 1 module(s). Each was searched for its ecosystem's logging libraries (Python: logging, structlog, loguru) and for a call on a receiver named `log`/`logger` (or ending in `Logger`/`_logger`) with a level verb. It cannot see logging through a repo-local wrapper named otherwise, or in source it did not read — this is 'no logging found by this walk', not a verdict that nothing here logs. If it is right, production issues will be hard to diagnose.
Minor — 8 finding(s)
X10 · Duplicated predicate · Duplicated predicate · ×2
  • Duplicated predicate injex/cli.py:42 — `callable(target) and not isinstance(target, Container)` appears character-identically in 2 files — injex/cli.py, injex/ext/django.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 REDACTED:751 — `param.annotation == inspect.Parameter.empty and name not in type_hints` appears character-identically in 2 files — REDACTED, injex/planning.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.
D20 · ADR Quality · No ADRs found · ×1
  • No ADRs found — No ADRs found. No recognised ADR directory (`docs/adr/`, `docs/decisions/`, `adr/`, `docs/rfcs/`, an `ADR0001/` folder, or their siblings) exists anywhere in this tree. What was searched, so you can tell an empty log from a search that missed one: every directory under the tree (build output, dependencies and VCS metadata excepted), for a document that is either any non-index page inside a recognised ADR directory, whatever its name and however deeply nested (`docs/adr/use-postgres.md`, `docs/adr/2024/0001-x.md`); or a file anywhere whose name is ADR-shaped (`0001-use-postgres.md`, `adr-012-caching.md`); or, when neither turned anything up, a document carrying the decision-record signature (an "Architecture Decision Record" heading, or Status / Context / Decision / Consequences as section headings). A decision log that clears none of these — unnumbered files outside any recognised directory, without those headings — is not seen by this check and this row is then wrong. If that is your case, say so rather than renaming anything; otherwise, consider recording architectural decisions in `docs/adr/`.
D27 · Navigability · Scattered collaborators · ×1
  • Scattered collaborators — 70 % of calls cross a namespace and only 55 % of collaborators are co-located — group each feature's code into a vertical slice so a call's collaborators sit together.
D36 · Supply-chain Provenance & Signing · REDACTED · ×1
  • REDACTED
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'.

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.

DimensionToolVersionCommandFindingsRaw output
D28 · Secrets (history)gitleaks—gitleaks detect --no-banner --config /opt/gitleaks-rules/watchdog-gitleaks.toml --report-format json --report-path /tmp/watchdog-gitleaks-400db52cab9e40cfa6387673bc43579c/history.json --exit-code 0 --source .0artifacts/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-400db52cab9e40cfa6387673bc43579c/tree.json --exit-code 0 --source .0artifacts/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 .5artifacts/raw/semgrep.json
D30 · Dependency Vulnerabilitiesosv-scanner—osv-scanner --format json --recursive --experimental-disable-plugins transitivedependency/requirements --experimental-disable-plugins dotnet/csproj --experimental-disable-plugins dotnet/nugetcpm .9artifacts/raw/osv-scanner.json
D31 · IaC & Container Securitytrivy—trivy: not applicable — No Infrastructure-as-Code or container manifests found (Dockerfile, Docker Compose, Terraform, Kubernetes/Helm, CloudFormation, ARM, Bicep, Ansible); nothing to scan.0—
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—
D40 · Network Egress Confinementruntime-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 Confinementruntime-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 Enforcementruntime-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 Dependenciesosv-scanner—osv-scanner --format json --recursive --experimental-disable-plugins transitivedependency/requirements --experimental-disable-plugins dotnet/csproj --experimental-disable-plugins dotnet/nugetcpm .0artifacts/raw/osv-scanner.json

Run 01a1637b-e61f-7f61-b928-80c333b531ea · every finding is also locatable in findings.md, and the complete scoring record (with exit codes + durations) in sidecar.json.

Downloadable artifacts

Machine-readable and reproducible from this commit + frozen rubric — drop them straight into a contract appendix, a CRA dossier, or a downstream SCA / VEX tool.

⬇ Findings, MITRE CWE-tagged .sarif⬇ Health changelog .md