Public report of Textualize/rich, published 25 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, 25 October 2026, 01:48 UTC · Survey ID cd_b727ca72f67840ed84540e9fd42bd591

Textualize/rich

Measured 25 October 2026, 01:46 UTC, at code version 9d8f9a3

Regression: 1 dimension fell since the last survey Supply-chain provenance & signing: not measured

A regression is a drop of 0.5 points or more in the score, or of 2.5 or more out of 10 in a dimension, since the last survey.

Supply-chain provenance & signing is not measured: Supply-chain provenance is not scored (this pipeline releases no artifact), but its build steps or GitHub Actions workflows have integrity defects, or nothing watches its dependency set for published advisories.

CAI score 66out of 100 Adequate
CriticalWeakAdequateStrongExemplary
Down 1 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.

Performance 90 Exemplary Security and Compliance 87 Strong Architecture 85 Adequate Production Readiness 81 Strong Code Health 79 Adequate Maturity 49 Weak

A medium codebase: 25,059 lines of product code in 2 projects, tests not counted · Estimated rebuild effort: about 0.3 person-years · Weakest lens: Maturity, 49

Findings by how serious they are

20 critical 98 serious 14 minor

13 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
25 October 2026, 01:46 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.

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 55 dimensions measured by tools. The other 3 are advisory notes from an AI model, which explain the code but don't count towards the score.
122of 132 findings point to an exact file and line, so you can open each one in the code. The other 10 concern the repository as a whole, such as missing documentation.
55dimensions across 6 lenses, read from 25,059 lines of product code in 2 projects.
Chapters

Executive summary

Textualize/rich scores 66 out of 100 and is rated Adequate, while five of its six lenses score higher still: Performance at 90, rated Exemplary, Security and Compliance at 87 and Production Readiness at 81, both rated Strong, and Architecture at 85 and Code Health at 79, both rated Adequate.

The score is lower than those five because the weakest lens counts most, and here that is Maturity, which scores 49 and is rated Weak. Its Architecture documentation dimension scores 0 out of 10, and until that reaches 4, Maturity can't be rated higher than Adequate. The first actions are to record your significant design decisions and to resolve the 1 Orphaned knowledge finding(s) in Knowledge Freshness, and if Maturity rose to 70, the score would rise from 66 to about 76.

20 findings are critical: 16 in Static Analysis (SAST), two in Dependency Vulnerabilities, one in Knowledge Freshness and one in Secret Scanning.

Watchdog couldn't measure 11 dimensions in this code, among them Code Coverage, Internal API Consistency and Data Protection, so they are left out of the score. The product code is 25,059 lines, which would take an estimated 0.3 person-years, around €41,000, to rebuild.

Code Health 79 Adequate, capped by Cognitive Complexity Architecture 85 Adequate, capped by Project Cohesion Maturity 49 Weak, capped by Architecture documentation Production Readiness 81 Strong Security and Compliance 87 Strong Performance 90 ★ Exemplary

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

How the score is built: what each lens counts for The lenses don't count equally. The weakest lens counts most, the next weakest a little less, and so on, so a weak area pulls the score down instead of being averaged away. In the bar below, each part's width shows how much that lens counts and its colour shows its rating. Improving the widest part moves the score most, and as that lens improves, it counts for less, because another lens becomes the weakest.
Maturity 49 · counts for 46%Code Health 79 · counts for 25%Production Readiness 81 · counts for 14%Architecture 85 · counts for 8%Security and Compliance 87 · counts for 4%Performance 90 · counts for 2%

If Maturity rose from 49 to 70, the lowest score rated Strong, the score would rise from 66 to about 76.

Code composition: what the lines of code are
Product code 74%Tests 26%
New since the last survey: 6 findings

These 6 critical or serious findings weren't in the previous survey, on 11 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.

Fixed since the last survey: 4 findings

These 4 critical or serious findings were in the previous survey, on 11 October 2026, and are gone from this one.

  • Dependency Vulnerabilities · High CVE: [GHSA redacted] REDACTED
  • Dependency Vulnerabilities · Medium CVE: [GHSA redacted] REDACTED
  • Supply-chain Provenance & Signing REDACTED
  • Supply-chain Provenance & Signing REDACTED
Rebuild cost: about €41,000 · Estimate
Cost to rebuild€14,000 to €69,000, for 228 to 724 hours of work, about 0.3 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×0.9 at a score of 66. 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.
SizeMedium: 25,059 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
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 14 points · Medium effort · Architecture documentation
2
Resolve the 1 Orphaned knowledge finding(s) in Knowledge Freshness — start with _win32_console.py.
Raises the score by about 3 points · Low effort · Knowledge Freshness
3
Resolve the 1 Off-boarding risk finding(s) in Bus Factor.
Raises the score by about 2 points · Low effort · Bus Factor

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 €41,000 to build again, about 0.3 person-years of work. Its weakest lens is Maturity, at 49 (Weak). Maturity is about how well the project explains and looks after itself, which decides whether a new developer, or a new supplier, can take over. Because the weakest lens counts most in the score, work on Maturity also moves the score most.
Based on: the rebuild estimate · the Maturity grade · how much each lens counts
What to do: Start with the Maturity actions in Top priorities.
If you do one thing first · First action
Record your significant design decisions. Of all the actions in this report, it raises the score most for the work it takes: about 14 points for medium effort. The next survey will show the change in the score.
Based on: the ranked actions in Top priorities, by score gain and effort

Architecture: which parts of the code depend on which

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

70 modules, with 90 dependencies between them. Every module uses only modules listed above it, so there are no loops.

The table shows the 40 modules with the most connections; 30 more are left out to keep it readable.

Which modules use which. The module on each row uses the module in each column, and the number counts the pairs of types that connect them. A cell above the diagonal is part of a loop.
uses →1 examples.top_lite_simulator2 rich.color_triplet3 rich.jupyter4 rich.measure5 rich.align6 rich.color7 rich.panel8 rich.pretty9 rich.spinner10 rich.table11 rich.tree12 examples.fullscreen13 rich.status14 rich.style15 rich._win32_console16 rich.console17 rich.text18 examples.layout19 rich20 rich.__main__21 rich._inspect22 rich.ansi23 rich.bar24 rich.columns25 rich.highlighter26 rich.layout27 rich.live28 rich.live_render29 rich.logging30 rich.markdown31 rich.progress_bar32 rich.prompt33 rich.rule34 rich.syntax35 examples36 examples.highlighter37 examples.log38 examples.rainbow39 rich.progress40 rich.traceback
1 examples.top_lite_simulator
2 rich.color_triplet
3 rich.jupyter
4 rich.measure
5 rich.align22
6 rich.color1
7 rich.panel1
8 rich.pretty1
9 rich.spinner1
10 rich.table11
11 rich.tree1
12 examples.fullscreen1
13 rich.status11
14 rich.style1
15 rich._win32_console1
16 rich.console11
17 rich.text111
18 examples.layout1
19 rich11141
20 rich.__main__12
21 rich._inspect111
22 rich.ansi1
23 rich.bar112
24 rich.columns12
25 rich.highlighter4
26 rich.layout4
27 rich.live11
28 rich.live_render2
29 rich.logging11
30 rich.markdown1124
31 rich.progress_bar1112
32 rich.prompt12
33 rich.rule1121
34 rich.syntax11421
35 examples111111
36 examples.highlighter1
37 examples.log1
38 examples.rainbow1
39 rich.progress12191
40 rich.traceback21
Uses a module listed above itPart of a loopThe module itself
1 examples.top_lite_simulator2 rich.color_triplet3 rich.jupyter4 rich.measure5 rich.align6 rich.color7 rich.panel8 rich.pretty9 rich.spinner10 rich.table11 rich.tree12 examples.fullscreen13 rich.status14 rich.style15 rich._win32_console16 rich.console17 rich.text18 examples.layout19 rich20 rich.__main__21 rich._inspect22 rich.ansi23 rich.bar24 rich.columns25 rich.highlighter26 rich.layout27 rich.live28 rich.live_render29 rich.logging30 rich.markdown31 rich.progress_bar32 rich.prompt33 rich.rule34 rich.syntax35 examples36 examples.highlighter37 examples.log38 examples.rainbow39 rich.progress40 rich.tracebackexamples.top_lite_simulator1rich.color_triplet2rich.jupyter3rich.measure4rich.align5rich.color6rich.panel7rich.pretty8rich.spinner9rich.table10rich.tree11examples.fullscreen12rich.status13rich.style14rich._win32_console15rich.console16rich.text17examples.layout18rich19rich.__main__20rich._inspect21rich.ansi22rich.bar23rich.columns24rich.highlighter25rich.layout26rich.live27rich.live_render28rich.logging29rich.markdown30rich.progress_bar31rich.prompt32rich.rule33rich.syntax34examples35examples.highlighter36examples.log37examples.rainbow38rich.progress39rich.traceback40221111111111111111111114112111111212441121111241112121121114211111111111219121+30 more modules (most-connected shown)

At a glance — Code Health · 79% · Adequate · gated by D2 ·

The Good
D1 · Python Cyclomatic Complexity 7.4 D3 · Python God Classes 8.3 D4 · Python Code Duplication 9.9 D17 · Python Explicit Debt 10.0 X1 · Repo Async correctness 10.0 X12 · Repo Unreachable branch 10.0 X13 · Repo Undrained process stream 10.0 X19 · Repo Unrestored process-global state 10.0 X21 · Repo Side-effecting pattern guard 10.0 X22 · Repo Contradicted release guard 10.0 X23 · Repo Unguarded diagnostic materialisation 10.0 X25 · Repo Inert configuration knob 10.0 X26 · Repo Unsynchronised callback handoff 10.0 X27 · Repo Collection changed while being enumerated 10.0 X28 · Repo Index access outside its own emptiness guard 10.0 X30 · Repo Support guard that admits what it rejects 10.0 X4 · Repo Structured logging 10.0
The Bad
X3 · Repo Exception handling 5.5
The Ugly
D2 · Python Cognitive Complexity 3.9

At a glance — Architecture · 85% · Adequate · gated by D26 ·

The Good
D6 · Python Cohesion (LCOM4) 9.8 D35 · Python Change Coupling 10.0 AX10 · Repo Code composition 10.0 AX3 · Repo Project dependency cycles 10.0 AX4 · Repo Dependency direction 10.0
The Bad
D27 · Python Navigability 6.8
The Ugly
D26 · Python Project Cohesion 0.0

At a glance — Maturity · 49% · Weak · gated by M2 ·

The Good
D15 · Python Churn × Complexity Hotspots 10.0 D16 · Python Bus Factor 8.8 D19 · Python Documentation Quality 9.7 D21 · Python Naming Consistency 10.0 D34 · Python Knowledge Freshness 9.3 M3 · Repo Folder & project structure 8.0 M4 · Repo Documentation accuracy 10.0
The Bad
M1 · Repo Documentation (README) 6.7
The Ugly
M2 · Repo Architecture documentation 0.0

At a glance — Readiness · 81% · Strong ·

The Good
D9 · Python Test Distribution 10.0 D11 · Python Test Reliability 10.0 D14 · Python License Compliance 10.0 P1 · Repo CI/CD gates 10.0 P10 · Repo Library API & versioning 10.0 P2 · Repo Observability 7.0 P3 · Repo Security & performance tooling 7.0 P6 · Repo Release Hygiene 10.0
The Bad
D13 · Python Secret Scanning 5.0

At a glance — Security · 87% · Strong ·

The Good
D28 · Python Secrets (history) 10.0 D30 · Python Dependency Vulnerabilities 8.2 D37 · Python Vulnerability-disclosure Policy 10.0 D43 · Python Malicious Dependencies 10.0 D44 · Python Platform End-of-Life 10.0 X14 · Repo Bypassable address classification 10.0 X15 · Repo Unvalidated length from an untrusted reader 10.0 X17 · Repo Uncapped recursion over a caller-supplied document 10.0 X24 · Repo Document value interpolated into markup unescaped 10.0
The Ugly
D29 · Python Static Analysis (SAST) 4.0

At a glance — Performance · 90% · Exemplary ·

The Good
PF1 · Repo Benchmark discipline 9.0

Security & Compliance — OWASP Top-10 mapping

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

OWASP categoryFindingsSeverity
A05:2025 — Injection21High / Critical
A03:2025 — Software Supply Chain Failures5High / Critical
A07:2025 — Authentication Failures1High / Critical

Roadmap

Begin by documenting significant design decisions in a dedicated ADR folder and clarifying how to run tests in the README. Next, address the off-boarding risk and resolve the orphaned knowledge issue in _win32_console.py to ensure team resilience. Finally, reorganize the project structure by moving production code into a src/ directory to separate it from tooling.

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

Do thisHelpsEffortDimension
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.+14.2 ptsMediumArchitecture documentation
Resolve the 1 Orphaned knowledge finding(s) in Knowledge Freshness — start with _win32_console.py.+3.1 ptsLowKnowledge Freshness
Resolve the 1 Off-boarding risk finding(s) in Bus Factor.+1.9 ptsLowBus Factor
Explain in the README how to run the tests. Add a section called Testing to the README in the repository's top folder, saying how to run the test suite.+3.4 ptsMediumDocumentation (README)
Resolve the 1 Leaked secret finding(s) in Secret Scanning — start with REDACTED.+1.1 ptsLowSecret Scanning
Group production code under src/ (or split deliberately, e.g. backend/ + frontend/) so production and tooling code aren't mixed at the root.+1.7 ptsMediumFolder & project structure
Swallowed exception (caught, then discarded)+1.5 ptsMediumException handling
Resolve the 3 Orphaned file finding(s) in Knowledge Freshness — start with snippets.py, benchmarks.py, _windows_renderer.py.+0.7 ptsLowKnowledge Freshness

File quality

Per-file score 0–10 — a quality signature. Of 36 files carrying findings, judged against the Production bar: 8% slop · 67% mixed · 25% near-clean.

FileScoreBandWorst signal
REDACTED2.1SlopDependency Vulnerabilities: High CVE: REDACTED
REDACTED2.5SlopStatic Analysis (SAST): High: REDACTED
REDACTED3.7SlopStatic Analysis (SAST): High: REDACTED
REDACTED4.0MixedStatic Analysis (SAST): Medium: REDACTED
REDACTED4.8MixedStatic Analysis (SAST): High: REDACTED
REDACTED5.1MixedStatic Analysis (SAST): High: REDACTED
REDACTED5.1MixedStatic Analysis (SAST): High: REDACTED
rich/text.py6.0MixedExplicit Debt: TodoComment
rich/console.py7.0MixedCyclomatic Complexity: Console.__init__ (cyclomatic 32)
rich/table.py7.1MixedCyclomatic Complexity: Table._render (cyclomatic 43)
rich/traceback.py7.1MixedCyclomatic Complexity: Traceback.extract (cyclomatic 31)
rich/segment.py7.1MixedCognitive Complexity: Segment.divide (cognitive 34)
REDACTED7.2MixedSecret Scanning: Leaked secret: REDACTED
REDACTED7.2MixedStatic Analysis (SAST): High: REDACTED
rich/markdown.py7.4MixedCyclomatic Complexity: Markdown.__rich_console__ (cyclomatic 34)
rich/syntax.py7.4MixedCyclomatic Complexity: Syntax._get_syntax (cyclomatic 25)
rich/progress.py7.4MixedGod Classes: FileTooLong: rich/progress.py
rich/_inspect.py7.8MixedCyclomatic Complexity: Inspect._render (cyclomatic 24)
rich/tree.py7.8MixedCyclomatic Complexity: Tree.__rich_console__ (cyclomatic 22)
rich/ansi.py7.8MixedCyclomatic Complexity: AnsiDecoder.decode_line (cyclomatic 21)

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 — 20

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 — 98

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 — 14

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

Could not be resolved — 13

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 55 evaluated dimensions are computed purely by tools and static analysis (confidence 1.0); 3 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 — 55 dimensions across the health lenses
D1D2D3D4D6D9D11D13D14D15D16D17D19D21D26D27D28D29D30D34D35D37D43D44AX10AX3AX4M1M2M3M4P1P10P2P3P6PF1X1X12X13X14X15X17X19X21X22X23X24X25X26X27X28X3X30X4

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, 122 of 132 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 01a170bd-4230-740a-a70d-c0b35e960c70.

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 tests -v --cov=./rich --cov-report=xml:./coverage.xml…`) shows that coverage is collected and tracked in your own CI. The built-in collector has no runner for this ecosystem (.py), so the analyzer could not read the number — a gap in the analyzer's language coverage, not an unmeasured repo. Not scored. To have the real number read, produce a coverage report in a standard format (`coverage run -m pytest` then `coverage xml`) and commit it — a hosted scan measures a clone of the repository, so a report that exists only in a working tree, a CI runner's or your own, never reaches it; the artefact is commonly gitignored, so `git add -f` that one file (or un-ignore its path) and commit it alongside the code it measures. You can widen what we reach: optional: produce a coverage report in a standard format (`coverage run -m pytest` then `coverage xml`) and commit it — a hosted scan measures a clone of the repository, so a report that exists only in a working tree, a CI runner's or your own, never reaches it; the artefact is commonly gitignored, so `git add -f` that one file (or un-ignore its path) and commit it alongside the code it measures — then the real number is read on the next scan.
  • D12 Dependency Hygiene — not measured this run — This is a true statement about the repository that carries nothing for its owner to act on, so it is reported here rather than as a defect in their code. This repository's 3 shipped Python distribution(s) across 2 manifest(s) WERE read; what went unanswered is the currency half, because it grades an EXACT pin against the newest release and every declaration here is a floor or a range — which installs the newest release it admits and so cannot be behind one. So pypi.org was never asked. This is a true statement about the repository, and the healthy one, NOT a gap on our side: no reader we could write would find a currency question here.
  • D22 Internal API Consistency — 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. D22 identifies the intentionally-exposed surface from `IsPackable` and `.Contracts` project names, MSBuild conventions read off the loaded project set. This target exposed no such projects, so the probe never ran; this says nothing about whether the repository has a public API. This repository commits no C#/VB source at all, so there was never an MSBuild project set to read these conventions off. That is OUR side and it is an ADMISSION gap, not an environment fault: it declares a published package (setup.py), but no published-package marker D22 reads admitted any project here. D22 DOES collect the public API of every language in this tree, and admits a project only when its manifest makes that ecosystem's publication act in a form the marker recognises — so what is missing is not a collector but an admission rule for the publication act this repository makes, if it makes one. The remedy is a better discriminator for that marker — not a collector, and no change to the scan image can close it. The marker's rules are measured to refuse applications, so one refused repository is the rule working as calibrated; several are the evidence that it is too strict.
  • 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.
  • 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.
  • X5 Nullable reference types — not measured this run — Watchdog could not measure this here. That is a gap on our side — a collector, parser or image we have not built yet — and it is neither a defect in this repository nor evidence that the check would have passed. This check reads C# syntax and MSBuild project configuration, TypeScript source and its tsconfig files, Java source and its package and module declarations, PHP source and its PHPStan and Psalm configuration, Dart source and its pubspec language version, Ruby source and its Sorbet and Steep configuration, Scala source and its build's explicit-nulls, WartRemover and Scalafix settings, and Kotlin source only, and no C# was loaded, no TypeScript was found, and this repository's Python is not read yet, so it had nothing of this repository's product to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.

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

Limitations & what we did not check

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

Per-dimension blind spots

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

  • D1 Cyclomatic Complexity: Cyclomatic complexity counts branches statically — it cannot tell an essential decision tree from accidental tangle, nor see complexity that lives in data or configuration (large switch-case token tables, DSL lexers/parsers, data-as-code rule tables) rather than control flow: a tokenizer's many single-character cases read as high complexity though each branch is trivial.
  • D2 Cognitive Complexity: Cognitive-complexity heuristics approximate how hard code is to follow; genuine domain difficulty and well-named intent that eases reading are not captured.
  • D3 God Classes: "God class" is sized by members and responsibilities visible in the type — a deliberately broad facade over a coherent subsystem can read the same as an accidental grab-bag. For front-end JS the file-length check is cohesion-aware (a single-responsibility module — one class/IIFE — earns a 3× threshold), but cohesion is approximated from top-level declarations, not true dependency structure.
  • D4 Code Duplication: Duplication is token-similarity — an in-process token-stream comparison over sliding windows, with type-aware normalization — so it finds copy-paste, not semantic duplication expressed differently. Committed machine-written code (scaffolded migrations, designer/codegen output, protobuf/OpenAPI stubs, model snapshots) is EXCLUDED — its repetition is the tool's, not the team's — so the score reflects hand-written duplication only.
  • D6 Cohesion (LCOM4): LCOM4 cohesion is syntactic — it infers connectivity from which methods touch which fields/methods by name, not from real runtime behaviour or intent.
  • D9 Test Distribution: The test-pyramid shape is inferred from project/folder naming and references, with a single test host bucketed per-file by its path tier and content signals — a suite that names tiers unconventionally and gives no per-file signal can still be mis-bucketed.
  • D11 Test Reliability: Flakiness is inferred from history/markers — Watchdog runs the suite once (for coverage), not the repeated runs under varied conditions that reveal nondeterminism, so a flaky test never recorded as failing is invisible here.
  • D13 Secret Scanning: Secret detection is signature- and entropy-based on the current tree — a secret that does not match a known pattern, or one already rotated, will not be flagged (a clean scan is "nothing matched", not "no secrets exist").
  • D14 License Compliance: License compatibility is checked against declared package metadata and a policy — mislabelled or missing license metadata, and obligations that depend on how you distribute, are not resolved here.
  • D15 Churn × Complexity Hotspots: Churn hotspots come from git history — a freshly imported or squashed repository has no churn signal, and recent rewrites can mask a historically risky file.
  • D16 Bus Factor: Bus-factor is a time-decayed model of commit attribution (who has recently, repeatedly worked a file), not comprehension — pairing, review and reading-without-committing spread knowledge it can't see; bot commits and shared accounts still distort it.
  • D17 Explicit Debt: Acknowledged-debt signals (TODO/FIXME, suppressions, dead code) are textual — undocumented debt that nobody marked, and debt that lives in design rather than annotations, is invisible. Committed machine-written code (scaffolded migrations, designer/codegen output, generated stubs) is excluded — it is never the team's dead code to delete.
  • D19 Documentation Quality: Documentation quality is judged by an LLM over a bounded sample of docs — it reads what is written, not whether the docs match the running system, and it is advisory, not a measurement. Its critique rows are drawn from a closed category vocabulary and each row means the same thing in every run, so two scans can be compared row by row; the SET that fires is still a sample, and does not repeat exactly. Measured on one frozen input, six scans at one engine SHA: 2-5 critique rows per scan, 8 distinct rows across the six, 3 of those 8 seen in only one scan. So a D19 row is evidence about the documentation, but a COUNT of D19 rows is not a quantity — never read a change in it as an improvement or a regression.
  • D21 Naming Consistency: Naming quality is an LLM judgement over a bounded sample — it assesses clarity/consistency of the names it sees, not domain-correctness, and is advisory.
  • 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.
  • 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 (3): D19, D21, M4 (model: Local LLM). For these, a model reads a bounded sample and sets the numeric score; each names its own sample and method on its card. They are sampled and advisory by design: they vary at the margins between runs and are never a deterministic measurement. Every other score in this report is tool-computed at confidence 1.0.

Dimensions

D1 · Cyclomatic Complexity7.4 / 10Strong✓ Tool-verified

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

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

Maturity: Documented → Verified → Prevented · effective 7.4 / 10 · rule-coverage 100% · ceiling Prevented

18 method(s) exceeded the cyclomatic complexity threshold of 15; the worst was Style.__init__ at 46.

Style.__init__ (cyclomatic 46)REDACTED:131
Table._render (cyclomatic 43)rich/table.py:755
Style.__str__ (cyclomatic 35)REDACTED:294
Markdown.__rich_console__ (cyclomatic 34)rich/markdown.py:579
Console.__init__ (cyclomatic 32)rich/console.py:619

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

What to do

  1. Bring the 18 bodies over 15 down to 15 or less in Cyclomatic Complexity — start with Style.__init__ (cyclomatic 46), Table._render (cyclomatic 43), Style.__str__ (cyclomatic 35). — 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 18 together lifts Cyclomatic Complexity from 7.4 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 Complexity3.9 / 10Weak✓ 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 3.9 / 10 · rule-coverage 100% · ceiling Prevented

41 method(s) exceeded the cognitive complexity threshold of 15; the worst was Style.__str__ at 105.

Style.__str__ (cognitive 105)REDACTED:294
Table._render (cognitive 88)rich/table.py:755
markup.render (cognitive 80)rich/markup.py:106
Console._write_buffer (cognitive 65)rich/console.py:2059
Traceback.extract (cognitive 65)rich/traceback.py:433

+ 36 more group(s) — more in Appendix A; the complete list is findings.md.

What to do

  1. Bring the 6 bodies over 60 down to 60 or less in Cognitive Complexity — start with Style.__str__ (cognitive 105), Table._render (cognitive 88), markup.render (cognitive 80). — 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 6 together lifts Cognitive Complexity from 3.9 to about 5.1/10, projected with the scoring formula itself and assuming each lands exactly at 60; a cleaner split scores higher.
  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 Classes8.3 / 10Strong✓ Tool-verified

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

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

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

11 god class(es) detected.

FileTooLong: rich/console.py · ×9rich/console.py
TooManyMethods: Console · ×2rich/console.py:581

What to do

  1. Resolve the 9 FileTooLong finding(s) in God Classes — start with console.py, progress.py, text.py. — One of this dimension's main actionable groups (9 warning-level).
  2. Resolve the 2 TooManyMethods finding(s) in God Classes — start with console.py, text.py. — One of this dimension's main actionable groups (2 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 Duplication9.9 / 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 9.9 / 10 · rule-coverage 100% · ceiling Verified

6 duplicated block group(s) detected.

Duplicated block (14 lines × 2) · ×2rich/json.py:38
Duplicated block (44–51 lines × 2)rich/progress.py:322
Duplicated block (19 lines × 2)rich/segment.py:248
Duplicated block (10–12 lines × 2)rich/text.py:995
Duplicated block (7 lines × 2)rich/progress.py:637

What to do

  1. Resolve the 2 Duplicated block (14 lines × 2) finding(s) in Code Duplication — start with json.py, REDACTED. — One of this dimension's main actionable groups (2 warning-level).
  2. Resolve the 1 Duplicated block (44–51 lines × 2) finding(s) in Code Duplication — start with progress.py. — One of this dimension's main actionable groups (1 warning-level).
  3. Resolve the 1 Duplicated block (19 lines × 2) finding(s) in Code Duplication — start with segment.py. — 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)9.8 / 10Stronggated by 1 serious finding✓ Tool-verified

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

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

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

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

1 of 63 classes have LCOM4 above 3.

Low cohesion: Box (LCOM4 4)rich/box.py:10

What to do

  1. Resolve the 1 Low cohesion finding(s) in Cohesion (LCOM4) — start with box.py. — One of this dimension's main actionable groups (1 warning-level).
  2. Enforce Cohesion (LCOM4) in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Verified — provenance only; does not change the score.

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

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

721 test methods: 721 unit, 0 integration, 0 BDD, 0 e2e. The Python suite contributes 721 test function(s) across 63 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.

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

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

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

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

0 flaky across 1 measured tier(s). Python (repository root, 63 test files): measured (0 flaky).

✓ On the Gold path — maintain.

Detailed fixes: d11_recommendation.md.

D13 · Secret Scanning5.0 / 10Adequate✓ Tool-verified

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 5.0 / 10 · rule-coverage 100% · ceiling Prevented

1 secret(s) detected.

REDACTED

What to do

  1. Resolve the 1 Leaked secret finding(s) in Secret Scanning — start with REDACTED. — One of this dimension's main actionable groups (1 issue-level).
  2. Enforce Secret Scanning in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Prevented — provenance only; does not change the score.

Detailed fixes: d13_recommendation.md · top locations in Appendix A, every location in findings.md.

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

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

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

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

0 of 24 shipped Python distribution(s) use a banned license. Licences were resolved from PyPI over the distributions a consumer installs — this repository's 3 declared runtime requirement(s) closed transitively over each distribution's published `requires_dist` (21 reached that way). Requirements it states ONLY under an extra, a PEP 735 dependency group, a Poetry dev group or a dev-named requirements file are excluded: pip does not install any of them for a consumer. ★ This repository commits no dependency lockfile that this pass reads, so each licence is the one PyPI publishes for the distribution's CURRENT release rather than for a pinned version. 9 of them publish no licence on PyPI this pass can read; that is missing data, not a violation, and none of them is charged. This repository publishes itself under MIT, which is its own choice and is not judged here.

✓ On the Gold path — maintain.

Detailed fixes: d14_recommendation.md.

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

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

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

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

No churn × complexity hotspots in the window.

✓ On the Gold path — maintain.

Detailed fixes: d15_recommendation.md.

D16 · Bus Factor8.8 / 10Strong✓ Tool-verified

What it measures: Whether knowledge is concentrated in too few people (the "bus factor").

Method: Living knowledge per author via time-decayed commit attribution (6-month half-life, focus weighting) across largest source files. Deterministic, avoids blame's mechanical-refactor false positives.

Maturity: Documented → Verified → Prevented · effective 8.8 / 10 · rule-coverage 100% · ceiling Documented

7 source file(s) have their living knowledge concentrated in one author (≥90% of recent, decayed contribution). The largest is rich/live.py. Counted over 56 of the 87 production source files in this repository: the rest are under the ~2,400-byte size floor this dimension measures over.

Off-boarding risk: anonymized user #1

What to do

  1. Resolve the 1 Off-boarding risk finding(s) in Bus Factor. — One of this dimension's main actionable groups (1 recommendation-level).

Detailed fixes: d16_recommendation.md · top locations in Appendix A, every location in findings.md.

D17 · Explicit Debt10.0 / 10Stronggated by 2 serious findings✓ Tool-verified

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

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

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

2 deducted task-comment markers across 25059 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.

TodoComment · ×2rich/text.py:562

What to do

  1. Resolve the 2 TodoComment finding(s) in Explicit Debt — start with text.py, test_status.py. — One of this dimension's main actionable groups (2 warning-level).
  2. Enforce Explicit Debt in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Prevented — provenance only; does not change the score.

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

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

Rich's documentation is clear and complete: a root repository README (the first document) gives an overview, installation, usage, contribution guidance, and licence; the architecture/design docs are separate. The benchmarks/README documents its own directory, not the repo, and each of the listed READMEs (benchmarks/, examples/, questions/, tools/) is focused on that tier and does not contradict the root level. Rich's documentation is clear and complete for a library: the README covers console markup (syntax, shorthand, error handling, links, escaping), padding (usage with tuples, style, expand), panels (Panel constructor, fit, title/subtitle), pretty printing (pprint, indent guides, max_length/max_string truncation), progress display (track, add_task, context manager), prompts (Prompt, IntPrompt, FloatPrompt, Confirm), and a protocol guide for custom objects. The architecture/Docs markdown files cover the remaining API surface with detailed reference docs (align, bar, color, columns, emoji, highlighter, init, JSON, layout, live, logging, markdown, markup, measure, padding, panel, pretty, progress_bar, progress, prompt, protocol, rule, segment, spinner, status, style, styled, syntax, table, text, theme, traceback, tree, abc).

✓ On the Gold path — maintain.

Detailed fixes: d19_recommendation.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.

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

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

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

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

1 of 2 build units (Python) flagged as possibly oversized/incoherent.

Projects may be oversized for their cohesion

What to do

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

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

D27 · Navigability6.8 / 10Adequate✓ 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 6.8 / 10 · rule-coverage 100% · ceiling Documented

84 % of calls cross a namespace and 0 % go through an interface, but 25 % 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)4.0 / 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 4.0 / 10 · rule-coverage 100% · ceiling Documented

21 finding(s): 0 critical, 16 high, 4 medium, 1 low. 12 unpinned-GitHub-Actions row(s) are reported here but scored by D36 (supply-chain provenance), which measures that posture as `pinned_actions` — one pinning decision is charged once, not once per lens. Separately, one or more rules could not re-parse an embedded snippet in 1 file(s) (e.g. a workflow `run:` block read as shell). Those files WERE scanned and their other rows are unaffected; only those rules' view of those snippets is missing.

REDACTED
REDACTED
REDACTED
REDACTED
REDACTED

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

What to do

  1. Resolve the 2 REDACTED finding(s) in Static Analysis (SAST) — start with REDACTED, REDACTED. — 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. No action in Static Analysis (SAST) — all 12 REDACTED finding(s) are reported here at file:line but scored by D36 (supply-chain provenance), so none is charged to this dimension. — One of this dimension's main actionable groups (12 issue-level, 0 of them charged here).

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

D30 · Dependency Vulnerabilities8.2 / 10Adequategated by 2 critical findings✓ Tool-verified

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

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

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

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

REDACTED
REDACTED

What to do

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

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

D34 · Knowledge Freshness9.3 / 10Adequategated by 1 critical finding✓ 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 9.3 / 10 · rule-coverage 100% · ceiling Documented

4 of 56 significant source file(s) are orphaned — their living knowledge has decayed to nothing, so no one currently understands them. The largest is rich/_win32_console.py. Counted over 56 of the 87 production source files in this repository: the rest are under the ~2,400-byte size floor this dimension measures over.

Orphaned knowledgerich/_win32_console.py:1
Orphaned file · ×3benchmarks/snippets.py:1
Further orphaned files (smaller)

What to do

  1. Resolve the 1 Orphaned knowledge finding(s) in Knowledge Freshness — start with _win32_console.py. — One of this dimension's main actionable groups (1 issue-level).
  2. Resolve the 3 Orphaned file finding(s) in Knowledge Freshness — start with snippets.py, benchmarks.py, _windows_renderer.py. — One of this dimension's main actionable groups (3 recommendation-level).
  3. Resolve the 1 Further orphaned files (smaller) finding(s) in Knowledge Freshness. — One of this dimension's main actionable groups (1 recommendation-level).

Detailed fixes: d34_recommendation.md · top locations in Appendix A, every location in findings.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.

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 0 platform declaration(s) and 3 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.
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)6.7 / 10Adequate✓ Tool-verified

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

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

What to do

  • Explain in the README how to run the tests. Add a section called Testing to the README in the repository's top folder, saying how to run the test suite.
  • Add an 'Architecture' / 'How it works' section to the root README — the high-level shape.
M2 · Architecture documentation0.0 / 10Critical✓ Tool-verified

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

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

  • No Architecture Decision Records found — no conventional ADR directory, no numbered `NNNN-title` documents in any markup this check reads, and nothing ADR-shaped by content. Design rationale recorded elsewhere (a design-notes tree, a mailing list, pull-request discussion) is not visible to this check and is not re-findable per decision, so a future maintainer cannot ask why one choice was made and get an answer.
  • No C4/Structurizr/PlantUML/Mermaid/Graphviz/D2 diagram, no drawn diagram named for the architecture, no file named `architecture` or `design` in any markup this check reads, and nothing in the README, docs or contributor guides that announces the shape — no `## Architecture` heading, no "architecture overview"/"high-level design" phrasing, no "the architecture is …" introduction, no guided code tour. A shape laid out in prose that never names itself as the architecture is not visible to this check, and neither is one kept outside the repository, so this row reports the absence of a re-findable shape document — not evidence that nobody wrote the shape down.

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.
  • Add a C4 context/container diagram (Structurizr, PlantUML or Mermaid) or an architecture.md overview.
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 · Observability7.0 / 10Strong✓ Tool-verified

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

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

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

  • Add gitleaks/trufflehog in CI to block PRs that introduce committed secrets.
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.

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

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

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

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 handling5.5 / 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. (×7) — rich/traceback.py:480, rich/pretty.py:86, rich/pretty.py:167, …
  • An empty catch block silently discards the error — failures vanish with no log and no rethrow. Log it, handle it, or don't catch it. — rich/pretty.py:661

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.

X4 · Structured logging10.0 / 10Exemplary○ Nothing flagged

Other · Code Health — Whether log calls use message templates (queryable) rather than interpolated strings.

Method: Roslyn syntax scan: every log call-site counted; interpolated-string first-argument violations flagged. Population is all log calls, not estimated. 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 `trace`/`debug`/`info`/`warn`/`error`/`fatal`/`verbose`/`silly`/`http`/`log` call on a receiver named for a logger, in a package whose own or an enclosing `package.json` declares a logger that carries values as fields (pino, pino-http, nestjs-pino, Fastify, winston, bunyan, tslog, LogTape, roarr), whose first deciding argument is a template literal with substitutions; an object-literal fields argument is stepped over, a plain string message clears the call. Python is read the same way: a `debug`/`info`/`warning`/`error`/`exception`/`critical`/`log` call on a logger in a file that imports the standard library’s `logging` or structlog (loguru, which formats at the call, is not judged), whose message is a whole f-string with a non-constant field; a `%`-formatted, `.format()`-ed or concatenated message is not convicted, as in C#. PHP is read the same way: a PSR-3 level call (`emergency`…`debug`, `log`) on a logger (`$logger`, `$this->logger`, Laravel’s `Log::`, `logger()`, `\Drupal::logger()`) in a package whose `composer.json` requires a PSR-3 logger or a framework that hands one out (psr/log, Monolog, Laravel, Symfony, Drupal, CakePHP), or a file that imports one, whose message is a double-quoted string interpolating a variable; a single-quoted message clears the call, and `sprintf` or `.` concatenation is not convicted, as in C#. Dart is read the same way: a `trace`/`debug`/`info`/`warn`/`error`/`fatal` call on Sentry’s structured logger (`Sentry.logger`) whose message is a whole string literal interpolating a value (`$name`, `${…}`); the `Sentry.logger.fmt` template API clears the call. Dart that logs only through loggers with one message and no fields (package:logging, package:logger, talker, dart:developer) is not applicable rather than a reach gap. Ruby is read the same way: a `trace`/`debug`/`info`/`warn`/`error`/`fatal` call on the console gem’s `Console` (declared by a Gemfile, gemspec or Gemfile.lock, or required) or, where SemanticLogger, Ougai or dry-logger is declared or required, on a receiver named for a logger (`logger`, `@logger`, `Rails.logger`, `log`), whose first deciding argument is, as the whole argument, a double-quoted string interpolating a non-constant value (`#{…}`, `#@ivar`); a plain literal clears the call, keyword arguments are the fields, and a block, `%`-format or `+` concatenation is not convicted. Ruby that logs only through the standard Logger (Rails.logger) is not applicable rather than a reach gap. Deterministic.

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 Health79%Adequate — gated by D2Capped at Fair by a Critical contributor — resolve it before relying on this lens.
Architecture85%Adequate — gated by D26Capped at Fair by a Critical contributor — resolve it before relying on this lens.
Maturity49%Weak — gated by M2Capped at Fair by a Critical contributor — resolve it before relying on this lens.
Readiness81%StrongSolid.
Security87%StrongSolid.
Performance90%ExemplaryStrongest area.
Unscored — 3 check(s) recorded observations but carry no score

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

  • D36 Supply-chain Provenance & Signing — 3 observation(s) recorded · The CI pipeline builds and tests but publishes no released artifact — no package publish, container push, GitHub release or deployment step. Supply-chain provenance, signing and SBOM attest RELEASED artifacts, so there is nothing to attest here. Add them to the release pipeline when this repo starts shipping artifacts (a published package, a container image, a deployed service or a tagged release). Build integrity and workflow-token hygiene are reported below: they describe what the CI runs and the token it runs with, neither of which is affected by whether the pipeline ships an artifact.
  • P12 CI test-gate honesty — 1 observation(s) recorded · 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.
  • X10 Duplicated predicate — 1 observation(s) recorded · Advisory — this card reports evidence and never carries a score.
Not evidenced — 2 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.

  • P4 Deployment & Rollback — not evidenced — no deploy/rollback/approval signal in the repo; absence of evidence is not evidence of a manual release
  • P5 DR & Backup — not evidenced — repo shows no backup/RTO/RPO controls; absence of evidence is not evidence of a working control
Not included — 60 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 applicable: this repository's Python imports no dependency-injection container and defines no container of its own — nothing that both registers and resolves bindings, and nothing that names two lifetimes — so nothing holds one lifetime's instance while handing out another's.
  • AX2 Stateful singletons — No container singleton was found, so there is no shared instance for concurrent requests to race on. No function in this Python code is served by a threaded web framework (a Flask, Bottle or FastAPI route, a Django or Pyramid view), so no module is shared between request threads.
  • 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 — ~8958 lines of test source are present (.py) but no test cases reached the test census for this repository — no test root we could resolve declared them, or the files we read declare no cases in a test framework we recognise — so skipped/assertion-free tests couldn't be counted. Not scored — this is a gap in the analyzer, not a finding about this repository.
  • D12 Dependency Hygiene — Dependency currency not established — no declaration carries an exact pin to grade
  • D18 Solution Shape — D18 scores the shape of a .NET solution; this repository has no .NET solution or project files, so the dimension does not apply.
  • D20 ADR Quality — N/A — ADRs are expected on deployable products with a user-facing host, not consumed libraries; no ADR log is required here.
  • D22 Internal API Consistency — The exposed public-API surface could not be collected — no C#/VB projects loaded.
  • 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 (32 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
  • P7 Outbound HTTP resilience — not applicable — no HTTP server, API framework or worker entry point was found in the Python source, so there is no service whose uptime a failing dependency could take down
  • P8 Schema migrations — no ORM, schema-migration tool or schema auto-create was found in this repository's dependency manifests or source, so there is no database schema for this check to judge
  • P9 Domain vs controller coverage — no coverage report found on disk — produce a coverage report in a standard format (`coverage run -m pytest` then `coverage xml`) and commit it — a hosted scan measures a clone of the repository, so a report that exists only in a working tree, a CI runner's or your own, never reaches it; the artefact is commonly gitignored, so `git add -f` that one file (or un-ignore its path) and commit it alongside the code it measures, or wire coverage collection into CI, to enable this cross-layer check
  • PF2 Allocation hygiene — Not applicable: Python runs on a garbage-collected runtime that gives a program no allocation-control idiom to choose on a hot path — no pools, stack allocation or value types — so allocation awareness is not something this code can be rated on.
  • PF3 Async & latency hygiene — Not applicable: this repository declares no async functions, so there is no asynchronous code for a blocking call to stall.
  • S1 Web-Security Posture — Not assessed: these web-security controls are read from a source model (declarative annotations, request middleware, entity/column names, guard methods) that was not loaded for this repository — because the repository is written in a language this check does not yet model, or because its projects failed to load. Absence of an idiom this check recognises is NOT evidence that this repository lacks web-security controls: it may implement them entirely in its own ecosystem. This is a gap in the analyzer's language coverage, not a finding about this repository.
  • X16 Unfloored truncation loop — not analysed — these correctness checks read a source model that was not loaded for this repository, because the repository is written in a language this check does not yet model, or because its projects failed to load. This is a gap in the analyzer, not a finding about this repository
  • X18 Disposal-pattern correctness — not analysed — these correctness checks read a source model that was not loaded for this repository, because the repository is written in a language this check does not yet model, or because its projects failed to load. This is a gap in the analyzer, not a finding about this repository
  • X2 Cancellation propagation — no C# was loaded; this repository's Python was read, and no request in it can be cancelled by a caller — a Python request takes no token: asyncio cancels the task and trio or anyio the scope that made it, from outside the call, and requests, httpx, aiohttp and gRPC take a timeout, not a cancellation
  • X20 Mistyped argument guard — This check asks whether an argument guard reports an EMPTY value as a NULL one, which needs a language that throws a null-specific argument exception — .NET's ArgumentNullException, the JVM's NullPointerException, Dart's ArgumentError.notNull. This repository contains none of those languages: the ones it is written in have a single exception for a bad argument, so there is no pair of exceptions to confuse and nothing here for it to assess. Not a gap in the analyzer and not a finding about your code.
  • X29 Per-element action decided by a fixed element — not analysed — these correctness checks read a source model that was not loaded for this repository, because the repository is written in a language this check does not yet model, or because its projects failed to load. This is a gap in the analyzer, not a finding about this repository
  • X32 Type resolved by simple name across every loaded assembly — This check is about how a .NET program searches the assemblies loaded into its process for a type, and this repository contains no .NET source, so there is nothing here for it to assess. Not a gap in the analyzer and not a finding about your code.
  • 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 — 20 finding(s)
D29 · Static Analysis (SAST) · REDACTED
  • REDACTED
  • REDACTED
  • REDACTED
  • REDACTED
  • REDACTED
  • REDACTED
  • REDACTED
  • REDACTED
  • REDACTED
  • REDACTED
  • REDACTED
  • REDACTED
D29 · Static Analysis (SAST) · REDACTED
  • REDACTED
  • REDACTED
D30 · Dependency Vulnerabilities · High CVE · ×2
  • REDACTED
  • REDACTED
D13 · Secret Scanning · Leaked secret · ×1
  • REDACTED
D29 · Static Analysis (SAST) · REDACTED · ×1
  • REDACTED
D29 · Static Analysis (SAST) · REDACTED · ×1
  • REDACTED
D34 · Knowledge Freshness · Orphaned knowledge · ×1
  • Orphaned knowledge rich/_win32_console.py:1 — No living knowledge remains for this large file — its last meaningful change has decayed away; if it breaks, no one currently understands it. Schedule a read-through / add characterisation tests before it bites.
Serious — 98 finding(s)
D3 · God Classes · FileTooLong · ×9
  • FileTooLong: rich/console.py rich/console.py — FileTooLong — 1583 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 1083 over it, 3.17× the bar. To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
  • FileTooLong: rich/progress.py rich/progress.py — FileTooLong — 1077 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 577 over it, 2.15× the bar. To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
  • FileTooLong: rich/text.py rich/text.py — FileTooLong — 858 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 358 over it, 1.72× the bar. To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
  • FileTooLong: rich/pretty.py rich/pretty.py — FileTooLong — 717 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 217 over it, 1.43× the bar. To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
  • FileTooLong: rich/table.py rich/table.py — FileTooLong — 689 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 189 over it, 1.38× the bar. To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
  • FileTooLong: rich/syntax.py rich/syntax.py — FileTooLong — 687 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 187 over it, 1.37× the bar. To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
  • FileTooLong: rich/traceback.py rich/traceback.py — FileTooLong — 662 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 162 over it, 1.32× the bar. To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
  • FileTooLong: rich/markdown.py rich/markdown.py — FileTooLong — 553 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 53 over it, 1.11× the bar. To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
  • FileTooLong: REDACTED REDACTED — FileTooLong — 551 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 51 over it, 1.10× 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.
X3 · Exception handling · Swallowed exception (caught, then discarded) · ×7
  • Swallowed exception (caught, then discarded) rich/traceback.py:480 — `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) rich/pretty.py:86 — `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) rich/pretty.py:167 — `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) rich/pretty.py:653 — `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) rich/console.py:81 — `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) rich/console.py:85 — `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) rich/console.py:89 — `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.
D29 · Static Analysis (SAST) · REDACTED
  • REDACTED
  • REDACTED
  • REDACTED
  • REDACTED
D30 · Dependency Vulnerabilities · Medium CVE · ×3
  • REDACTED
  • REDACTED
  • REDACTED
D17 · Explicit Debt · TodoComment · ×2
  • TodoComment rich/text.py:562 — # TODO: This is a little inefficient, it is only used by full justify — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `# REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
  • TodoComment tests/test_status.py:22 — # TODO: Testing output is tricky with threads — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `# REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
D3 · God Classes · TooManyMethods · ×2
  • TooManyMethods: Console rich/console.py:581 — TooManyMethods — 53 methods. The bar is 30 methods; this is 23 over it, 1.77× 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.
  • TooManyMethods: Text rich/text.py:118 — TooManyMethods — 49 methods. The bar is 30 methods; this is 19 over it, 1.63× 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.
D36 · Supply-chain Provenance & Signing REDACTED · ×2
  • REDACTED
  • REDACTED
D4 · Code Duplication · Duplicated block (14 lines × 2) · ×2
  • Duplicated block (14 lines × 2) rich/json.py:38 — rich/json.py:38-51 | rich/json.py:85-98 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited.
  • Duplicated block (14 lines × 2) REDACTED:627 — REDACTED:627-640 | REDACTED:650-663 — 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.
D1 · Cyclomatic Complexity · Style.__init__ (cyclomatic 46) · ×1
  • Style.__init__ (cyclomatic 46) REDACTED:131 — Style.__init__ has cyclomatic complexity 46 (threshold 15). To reduce it, name the conditions: bind each compound test to a well-named local or a small predicate function, so the body reads as a sequence of named decisions rather than a chain of operators.
D1 · Cyclomatic Complexity · Table._render (cyclomatic 43) · ×1
  • Table._render (cyclomatic 43) rich/table.py:755 — Table._render has cyclomatic complexity 43 (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 · Style.__str__ (cyclomatic 35) · ×1
  • Style.__str__ (cyclomatic 35) REDACTED:294 — Style.__str__ has cyclomatic complexity 35 (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 · Markdown.__rich_console__ (cyclomatic 34) · ×1
  • Markdown.__rich_console__ (cyclomatic 34) rich/markdown.py:579 — Markdown.__rich_console__ has cyclomatic complexity 34 (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 · Console.__init__ (cyclomatic 32) · ×1
  • Console.__init__ (cyclomatic 32) rich/console.py:619 — Console.__init__ has cyclomatic complexity 32 (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 · Traceback.extract (cyclomatic 31) · ×1
  • Traceback.extract (cyclomatic 31) rich/traceback.py:433 — Traceback.extract has cyclomatic complexity 31 (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 · Syntax._get_syntax (cyclomatic 25) · ×1
  • Syntax._get_syntax (cyclomatic 25) rich/syntax.py:652 — Syntax._get_syntax has cyclomatic complexity 25 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.
D1 · Cyclomatic Complexity · Inspect._render (cyclomatic 24) · ×1
  • Inspect._render (cyclomatic 24) rich/_inspect.py:125 — Inspect._render has cyclomatic complexity 24 (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 · Tree.__rich_console__ (cyclomatic 22) · ×1
  • Tree.__rich_console__ (cyclomatic 22) rich/tree.py:86 — Tree.__rich_console__ has cyclomatic complexity 22 (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 · AnsiDecoder.decode_line (cyclomatic 21) · ×1
  • AnsiDecoder.decode_line (cyclomatic 21) rich/ansi.py:138 — AnsiDecoder.decode_line has cyclomatic complexity 21 (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 · markup.render (cyclomatic 21) · ×1
  • markup.render (cyclomatic 21) rich/markup.py:106 — markup.render has cyclomatic complexity 21 (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 · ProgressBar.__rich_console__ (cyclomatic 21) · ×1
  • ProgressBar.__rich_console__ (cyclomatic 21) rich/progress_bar.py:156 — ProgressBar.__rich_console__ has cyclomatic complexity 21 (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 · _windows_renderer.legacy_windows_render (cyclomatic 20) · ×1
  • _windows_renderer.legacy_windows_render (cyclomatic 20) rich/_windows_renderer.py:7 — _windows_renderer.legacy_windows_render has cyclomatic complexity 20 (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 · Table._calculate_column_widths (cyclomatic 20) · ×1
  • Table._calculate_column_widths (cyclomatic 20) rich/table.py:523 — Table._calculate_column_widths has cyclomatic complexity 20 (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 · Traceback._render_stack (cyclomatic 19) · ×1
  • Traceback._render_stack (cyclomatic 19) rich/traceback.py:768 — Traceback._render_stack has cyclomatic complexity 19 (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 · Console.print (cyclomatic 18) · ×1
  • Console.print (cyclomatic 18) rich/console.py:1652 — Console.print 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 · Console._write_buffer (cyclomatic 18) · ×1
  • Console._write_buffer (cyclomatic 18) rich/console.py:2059 — Console._write_buffer 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 · LogRender.__call__ (cyclomatic 17) · ×1
  • LogRender.__call__ (cyclomatic 17) rich/_log_render.py:32 — LogRender.__call__ has cyclomatic complexity 17 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.
D2 · Cognitive Complexity · Style.__str__ (cognitive 105) · ×1
  • Style.__str__ (cognitive 105) REDACTED:294 — Style.__str__ has cognitive complexity 105 (threshold 15). Drivers by points: if/else 20 (52 pts), ternaries 13 (52 pts), boolean chains 1 (nesting depth added 71). To reduce it, flatten the nesting: this score is depth rather than breadth — most of its points come from checks stacked inside one another, so the work sits several levels in. Invert each enclosing check into an early exit (a return, or the language's equivalent) so the happy path stays at one level, and where a level cannot be exited early, lift the block it encloses into its own named function.
D2 · Cognitive Complexity · Table._render (cognitive 88) · ×1
  • Table._render (cognitive 88) rich/table.py:755 — Table._render has cognitive complexity 88 (threshold 15). Drivers by points: if/else 17 (39 pts), loops 6 (17 pts), boolean chains 16, ternaries 7 (16 pts) (nesting depth added 42). 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 · markup.render (cognitive 80) · ×1
  • markup.render (cognitive 80) rich/markup.py:106 — markup.render has cognitive complexity 80 (threshold 15). Drivers by points: if/else 13 (37 pts), error handling 4 (22 pts), ternaries 4 (19 pts), loops 2 (nesting depth added 57). To reduce it, flatten the nesting: this score is depth rather than breadth — most of its points come from checks stacked inside one another, so the work sits several levels in. Invert each enclosing check into an early exit (a return, or the language's equivalent) so the happy path stays at one level, and where a level cannot be exited early, lift the block it encloses into its own named function.
D2 · Cognitive Complexity · Console._write_buffer (cognitive 65) · ×1
  • Console._write_buffer (cognitive 65) rich/console.py:2059 — Console._write_buffer has cognitive complexity 65 (threshold 15). Drivers by points: if/else 15 (47 pts), error handling 2 (9 pts), loops 1 (6 pts), boolean chains 3 (nesting depth added 44). To reduce it, flatten the nesting: this score is depth rather than breadth — most of its points come from checks stacked inside one another, so the work sits several levels in. Invert each enclosing check into an early exit (a return, or the language's equivalent) so the happy path stays at one level, and where a level cannot be exited early, lift the block it encloses into its own named function.
D2 · Cognitive Complexity · Traceback.extract (cognitive 65) · ×1
  • Traceback.extract (cognitive 65) rich/traceback.py:433 — Traceback.extract has cognitive complexity 65 (threshold 15). Drivers by points: if/else 14 (43 pts), boolean chains 11, loops 3 (7 pts), ternaries 2 (4 pts) (nesting depth added 35). 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 · Markdown.__rich_console__ (cognitive 64) · ×1
  • Markdown.__rich_console__ (cognitive 64) rich/markdown.py:579 — Markdown.__rich_console__ has cognitive complexity 64 (threshold 15). Drivers by points: if/else 19 (54 pts), boolean chains 9, loops 1 (nesting depth added 35). To reduce it, flatten the nesting: this score is depth rather than breadth — most of its points come from checks stacked inside one another, so the work sits several levels in. Invert each enclosing check into an early exit (a return, or the language's equivalent) so the happy path stays at one level, and where a level cannot be exited early, lift the block it encloses into its own named function.
D2 · Cognitive Complexity · Syntax._get_syntax (cognitive 51) · ×1
  • Syntax._get_syntax (cognitive 51) rich/syntax.py:652 — Syntax._get_syntax has cognitive complexity 51 (threshold 15). Drivers by points: if/else 19 (34 pts), loops 4 (10 pts), boolean chains 4, ternaries 3 (nesting depth added 21). 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 · Traceback._render_stack (cognitive 48) · ×1
  • Traceback._render_stack (cognitive 48) rich/traceback.py:768 — Traceback._render_stack has cognitive complexity 48 (threshold 15). Drivers by points: if/else 12 (30 pts), error handling 2 (8 pts), loops 2 (5 pts), ternaries 1 (3 pts), boolean chains 2 (nesting depth added 29). 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 · Inspect._render (cognitive 47) · ×1
  • Inspect._render (cognitive 47) rich/_inspect.py:125 — Inspect._render has cognitive complexity 47 (threshold 15). Drivers by points: if/else 19 (36 pts), ternaries 2 (8 pts), boolean chains 2, loops 1 (nesting depth added 23). To reduce it, flatten the nesting: this score is depth rather than breadth — most of its points come from checks stacked inside one another, so the work sits several levels in. Invert each enclosing check into an early exit (a return, or the language's equivalent) so the happy path stays at one level, and where a level cannot be exited early, lift the block it encloses into its own named function.
D2 · Cognitive Complexity · Style.__init__ (cognitive 45) · ×1
  • Style.__init__ (cognitive 45) REDACTED:131 — Style.__init__ has cognitive complexity 45 (threshold 15). Drivers by points: boolean chains 40, ternaries 5. To reduce it, name the conditions: bind each compound test to a well-named local or a small predicate function, so the body reads as a sequence of named decisions rather than a chain of operators.
D2 · Cognitive Complexity · Tree.__rich_console__ (cognitive 44) · ×1
  • Tree.__rich_console__ (cognitive 44) rich/tree.py:86 — Tree.__rich_console__ has cognitive complexity 44 (threshold 15). Drivers by points: if/else 6 (17 pts), ternaries 4 (13 pts), boolean chains 8, loops 2 (4 pts), error handling 1 (2 pts) (nesting depth added 23). 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 · Console.__init__ (cognitive 43) · ×1
  • Console.__init__ (cognitive 43) rich/console.py:619 — Console.__init__ has cognitive complexity 43 (threshold 15). Drivers by points: if/else 18 (29 pts), boolean chains 9, ternaries 5 (nesting depth added 11). 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 · Style._make_ansi_codes (cognitive 43) · ×1
  • Style._make_ansi_codes (cognitive 43) REDACTED:344 — Style._make_ansi_codes has cognitive complexity 43 (threshold 15). Drivers by points: if/else 12 (35 pts), loops 2 (8 pts) (nesting depth added 29). To reduce it, flatten the nesting: this score is depth rather than breadth — most of its points come from checks stacked inside one another, so the work sits several levels in. Invert each enclosing check into an early exit (a return, or the language's equivalent) so the happy path stays at one level, and where a level cannot be exited early, lift the block it encloses into its own named function.
D2 · Cognitive Complexity · AnsiDecoder.decode_line (cognitive 36) · ×1
  • AnsiDecoder.decode_line (cognitive 36) rich/ansi.py:138 — AnsiDecoder.decode_line has cognitive complexity 36 (threshold 15). Drivers by points: if/else 7 (26 pts), loops 2 (4 pts), boolean chains 3, ternaries 1 (3 pts) (nesting depth added 23). 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 · Segment.divide (cognitive 34) · ×1
  • Segment.divide (cognitive 34) rich/segment.py:630 — Segment.divide has cognitive complexity 34 (threshold 15). Drivers by points: if/else 9 (27 pts), loops 3 (4 pts), ternaries 1 (3 pts) (nesting depth added 21). 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 · Console.export_html (cognitive 33) · ×1
  • Console.export_html (cognitive 33) rich/console.py:2244 — Console.export_html has cognitive complexity 33 (threshold 15). Drivers by points: if/else 9 (21 pts), loops 3 (6 pts), ternaries 2 (5 pts), boolean chains 1 (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 · Console.print (cognitive 32) · ×1
  • Console.print (cognitive 32) rich/console.py:1652 — Console.print has cognitive complexity 32 (threshold 15). Drivers by points: if/else 14 (21 pts), loops 5 (10 pts), ternaries 1 (nesting depth added 12). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
D2 · Cognitive Complexity · Table._calculate_column_widths (cognitive 32) · ×1
  • Table._calculate_column_widths (cognitive 32) rich/table.py:523 — Table._calculate_column_widths has cognitive complexity 32 (threshold 15). Drivers by points: if/else 8 (16 pts), boolean chains 8, ternaries 2 (5 pts), loops 1 (3 pts) (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 · Lines.justify (cognitive 31) · ×1
  • Lines.justify (cognitive 31) rich/containers.py:111 — Lines.justify has cognitive complexity 31 (threshold 15). Drivers by points: loops 6 (15 pts), if/else 4 (11 pts), ternaries 1 (5 pts) (nesting depth added 20). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
D2 · Cognitive Complexity · Console.export_svg (cognitive 30) · ×1
  • Console.export_svg (cognitive 30) rich/console.py:2352 — Console.export_svg has cognitive complexity 30 (threshold 15). Drivers by points: if/else 8 (16 pts), ternaries 2 (8 pts), boolean chains 3, loops 2 (3 pts) (nesting depth added 15). 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 · _wrap.divide_line (cognitive 27) · ×1
  • _wrap.divide_line (cognitive 27) rich/_wrap.py:26 — _wrap.divide_line has cognitive complexity 27 (threshold 15). Drivers by points: if/else 7 (21 pts), loops 2 (5 pts), boolean chains 1 (nesting depth added 17). 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 · cells.split_graphemes (cognitive 27) · ×1
  • cells.split_graphemes (cognitive 27) rich/cells.py:161 — cells.split_graphemes has cognitive complexity 27 (threshold 15). Drivers by points: if/else 9 (22 pts), ternaries 1 (4 pts), loops 1 (nesting depth added 16). To reduce it, flatten the nesting: this score is depth rather than breadth — most of its points come from checks stacked inside one another, so the work sits several levels in. Invert each enclosing check into an early exit (a return, or the language's equivalent) so the happy path stays at one level, and where a level cannot be exited early, lift the block it encloses into its own named function.
D2 · Cognitive Complexity · Columns.__rich_console__ (cognitive 26) · ×1
  • Columns.__rich_console__ (cognitive 26) rich/columns.py:62 — Columns.__rich_console__ has cognitive complexity 26 (threshold 15). Drivers by points: if/else 9 (13 pts), loops 4 (8 pts), ternaries 3 (5 pts) (nesting depth added 10). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
D2 · Cognitive Complexity · ProgressBar.__rich_console__ (cognitive 25) · ×1
  • ProgressBar.__rich_console__ (cognitive 25) rich/progress_bar.py:156 — ProgressBar.__rich_console__ has cognitive complexity 25 (threshold 15). Drivers by points: if/else 7 (12 pts), boolean chains 7, ternaries 6 (nesting depth added 5). 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 · Text.divide (cognitive 25) · ×1
  • Text.divide (cognitive 25) rich/text.py:1106 — Text.divide has cognitive complexity 25 (threshold 15). Drivers by points: if/else 9 (17 pts), loops 4 (8 pts) (nesting depth added 12). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
D2 · Cognitive Complexity · LogRender.__call__ (cognitive 24) · ×1
  • LogRender.__call__ (cognitive 24) rich/_log_render.py:32 — LogRender.__call__ has cognitive complexity 24 (threshold 15). Drivers by points: if/else 11 (14 pts), boolean chains 5, ternaries 2 (5 pts) (nesting depth added 6). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
D2 · Cognitive Complexity · Color.downgrade (cognitive 24) · ×1
  • Color.downgrade (cognitive 24) rich/color.py:513 — Color.downgrade has cognitive complexity 24 (threshold 15). Drivers by points: if/else 10 (17 pts), ternaries 3 (6 pts), boolean chains 1 (nesting depth added 10). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
D2 · Cognitive Complexity · Segment.split_and_crop_lines (cognitive 22) · ×1
  • Segment.split_and_crop_lines (cognitive 22) rich/segment.py:307 — Segment.split_and_crop_lines has cognitive complexity 22 (threshold 15). Drivers by points: if/else 6 (17 pts), loops 2 (4 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 · Style.parse (cognitive 21) · ×1
  • Style.parse (cognitive 21) REDACTED:498 — Style.parse has cognitive complexity 21 (threshold 15). Drivers by points: if/else 6 (13 pts), error handling 2 (6 pts), boolean chains 1, loops 1 (nesting depth added 11). 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 · _ratio.ratio_resolve (cognitive 20) · ×1
  • _ratio.ratio_resolve (cognitive 20) rich/_ratio.py:14 — _ratio.ratio_resolve has cognitive complexity 20 (threshold 15). Drivers by points: if/else 3 (7 pts), loops 3 (6 pts), boolean chains 4, ternaries 1 (3 pts) (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 · _windows_renderer.legacy_windows_render (cognitive 20) · ×1
  • _windows_renderer.legacy_windows_render (cognitive 20) rich/_windows_renderer.py:7 — _windows_renderer.legacy_windows_render has cognitive complexity 20 (threshold 15). Drivers by points: if/else 6 (16 pts), loops 2 (4 pts) (nesting depth added 12). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
D2 · Cognitive Complexity · Text.expand_tabs (cognitive 20) · ×1
  • Text.expand_tabs (cognitive 20) rich/text.py:817 — Text.expand_tabs has cognitive complexity 20 (threshold 15). Drivers by points: if/else 8 (16 pts), loops 2 (4 pts) (nesting depth added 10). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
D2 · Cognitive Complexity · Node.iter_tokens (cognitive 19) · ×1
  • Node.iter_tokens (cognitive 19) rich/pretty.py:424 — Node.iter_tokens has cognitive complexity 19 (threshold 15). Drivers by points: if/else 7 (14 pts), loops 1 (4 pts), boolean chains 1 (nesting depth added 10). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
D2 · Cognitive Complexity · Table._collapse_widths (cognitive 19) · ×1
  • Table._collapse_widths (cognitive 19) rich/table.py:589 — Table._collapse_widths has cognitive complexity 19 (threshold 15). Drivers by points: if/else 3 (7 pts), ternaries 2 (6 pts), boolean chains 4, loops 1 (2 pts) (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 · Text.wrap (cognitive 19) · ×1
  • Text.wrap (cognitive 19) rich/text.py:1201 — Text.wrap has cognitive complexity 19 (threshold 15). Drivers by points: if/else 5 (10 pts), loops 3 (6 pts), boolean chains 3 (nesting depth added 8). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
D2 · Cognitive Complexity · Segment.split_lines (cognitive 17) · ×1
  • Segment.split_lines (cognitive 17) rich/segment.py:247 — Segment.split_lines has cognitive complexity 17 (threshold 15). Drivers by points: if/else 5 (12 pts), loops 2 (4 pts), boolean chains 1 (nesting depth added 9). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body. This shape REPEATS in the file: one other method here (Segment.split_lines_terminator) has the same decision points, in the same order, at the same nesting depths — so this is one pattern written twice rather than two separate problems. Splitting this body alone leaves the other exactly as it is. Where these are variations on one operation, the change that clears both is the shared one: lift the common shape into a single routine the variants call, parameterised by whatever genuinely differs between them, and keep in each method only the part that is not shared.
D2 · Cognitive Complexity · Segment.split_lines_terminator (cognitive 17) · ×1
  • Segment.split_lines_terminator (cognitive 17) rich/segment.py:276 — Segment.split_lines_terminator has cognitive complexity 17 (threshold 15). Drivers by points: if/else 5 (12 pts), loops 2 (4 pts), boolean chains 1 (nesting depth added 9). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body. This shape REPEATS in the file: one other method here (Segment.split_lines) has the same decision points, in the same order, at the same nesting depths — so this is one pattern written twice rather than two separate problems. Splitting this body alone leaves the other exactly as it is. Where these are variations on one operation, the change that clears both is the shared one: lift the common shape into a single routine the variants call, parameterised by whatever genuinely differs between them, and keep in each method only the part that is not shared.
D2 · Cognitive Complexity · Text.highlight_regex (cognitive 17) · ×1
  • Text.highlight_regex (cognitive 17) rich/text.py:593 — Text.highlight_regex has cognitive complexity 17 (threshold 15). Drivers by points: if/else 4 (9 pts), loops 2 (3 pts), ternaries 1 (3 pts), boolean chains 2 (nesting depth added 8). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
D2 · Cognitive Complexity · cells._split_text (cognitive 16) · ×1
  • cells._split_text (cognitive 16) rich/cells.py:235 — cells._split_text has cognitive complexity 16 (threshold 15). Drivers by points: if/else 7 (15 pts), loops 1 (nesting depth added 8). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
D2 · Cognitive Complexity · Color.get_ansi_codes (cognitive 16) · ×1
  • Color.get_ansi_codes (cognitive 16) rich/color.py:485 — Color.get_ansi_codes has cognitive complexity 16 (threshold 15). Drivers by points: ternaries 7 (14 pts), if/else 2 (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 · Panel.__rich_console__ (cognitive 16) · ×1
  • Panel.__rich_console__ (cognitive 16) rich/panel.py:141 — Panel.__rich_console__ has cognitive complexity 16 (threshold 15). Drivers by points: if/else 8, ternaries 4, boolean chains 3, loops 1. To reduce it, split the body: this score is breadth rather than depth — many checks laid out side by side rather than nested inside one another, so inverting conditions into early returns has nothing left to flatten. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.
D36 · Supply-chain Provenance & Signing REDACTED · ×1
  • REDACTED
D4 · Code Duplication · Duplicated block (44–51 lines × 2) · ×1
  • Duplicated block (44–51 lines × 2) rich/progress.py:322 — rich/progress.py:322-365 | rich/progress.py:442-492 — 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 (19 lines × 2) · ×1
  • Duplicated block (19 lines × 2) rich/segment.py:248 — rich/segment.py:248-266 | rich/segment.py:279-297 — 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 (10–12 lines × 2) · ×1
  • Duplicated block (10–12 lines × 2) rich/text.py:995 — rich/text.py:995-1006 | rich/text.py:1019-1028 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. The `return` at the foot of the matched lines is the enclosing body's own terminal exit, not an early one: it moves with them unchanged, and each site calls the extracted unit from the position that `return` occupied — no decision has to be handed back and re-acted on.
D4 · Code Duplication · Duplicated block (7 lines × 2) · ×1
  • Duplicated block (7 lines × 2) rich/progress.py:637 — rich/progress.py:637-643 | rich/progress.py:763-769 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. The `return` at the foot of the matched lines is the enclosing body's own terminal exit, not an early one: it moves with them unchanged, and each site calls the extracted unit from the position that `return` occupied — no decision has to be handed back and re-acted on.
D6 · Cohesion (LCOM4) · Low cohesion · ×1
  • Low cohesion: Box (LCOM4 4) rich/box.py:10 — Box's methods fall into 4 groups that share no field and call none of each other, against a bar of more than 3 for this run (LCOM4, configurable — your repository's bar is the one quoted here). Each group is a set of methods reachable from one another through shared fields or direct calls, so 4 groups means the type has that many internally-connected clusters with nothing tying them together. Types whose shape makes a high count expected — and which would otherwise dominate this list — are excluded before this row is raised, so this is a genuine split candidate rather than a metric reading. It is still a shape, not a defect: confirm the groups match responsibilities you can name before splitting.
P12 · CI test-gate honesty · Coverage collected but not gated · ×1
  • Coverage collected but not gated — CI collects a coverage report but no step enforces a minimum — coverage could halve and CI stays green. Add a step that fails the build when coverage drops below a floor (your coverage tool's minimum-threshold flag, or a coverage-gate action) so the number guards something. What was searched, so you can tell an absence from a miss: this repository's CI files AND its coverage configuration — the well-known coverage and test-runner config files, read at the repository root and inside workspace package directories two levels down, so a floor declared beside the tests rather than in the pipeline is credited — matched against the threshold settings this check knows by name. A floor set in your coverage service's web UI rather than in a committed file, or under a setting whose name is not one of those, is not seen here.
X3 · Exception handling · Swallowed exception (empty catch) · ×1
  • Swallowed exception (empty catch) rich/pretty.py:661 — An empty catch block silently discards the error — failures vanish with no log and no rethrow. Log it, handle it, or don't catch it.
Minor — 13 finding(s)
D34 · Knowledge Freshness · Orphaned file · ×3
  • Orphaned file benchmarks/snippets.py:1 — No one still active in this repository holds living knowledge of this file: everyone who made a meaningful change to it has gone quiet, or what the current team did to it (moves, reformatting, log-level or import edits, renames) never needed understanding it. If it breaks, no one currently understands it. Attach the read to the next change that touches it: have a second person review that change, and leave behind a short comment or test recording what the file is for.
  • Orphaned file benchmarks/benchmarks.py:1 — No one still active in this repository holds living knowledge of this file: everyone who made a meaningful change to it has gone quiet, or what the current team did to it (moves, reformatting, log-level or import edits, renames) never needed understanding it. If it breaks, no one currently understands it. Attach the read to the next change that touches it: have a second person review that change, and leave behind a short comment or test recording what the file is for.
  • Orphaned file rich/_windows_renderer.py:1 — No one still active in this repository holds living knowledge of this file: everyone who made a meaningful change to it has gone quiet, or what the current team did to it (moves, reformatting, log-level or import edits, renames) never needed understanding it. If it breaks, no one currently understands it. Attach the read to the next change that touches it: have a second person review that change, and leave behind a short comment or test recording what the file is for.
D16 · Bus Factor · Off-boarding risk · ×1
  • Off-boarding risk: anonymized user #1 — If anonymized user #1 becomes unavailable, 7 significant file(s) lose their only recent owner: rich/live.py, rich/cells.py, rich/default_styles.py, rich/__main__.py, rich/ansi.py, rich/__init__.py, rich/_unicode_data/__init__.py. Pair on, review, or document these before any departure.
D26 · Project Cohesion · Projects may be oversized for their cohesion · ×1
  • Projects may be oversized for their cohesion — 1 of 2 project(s) overshoot their size bounds, lowering Project Cohesion to 0.0/10. The most over is `(repository root)` (25003 LoC, 238 module-visible types across 4 directories). Review these for cohesion — draw the boundary inside the module first (group each responsibility into its own package or directory and keep the cross-boundary members non-public), since splitting a published package moves types between packages and breaks consumers.
D27 · Navigability · Scattered collaborators · ×1
  • Scattered collaborators — 84 % of calls cross a namespace and only 25 % of collaborators are co-located — group each feature's code into a vertical slice so a call's collaborators sit together.
D29 · Static Analysis (SAST) · REDACTED · ×1
  • REDACTED
D34 · Knowledge Freshness · Further orphaned files (smaller) · ×1
  • Further orphaned files (smaller) — 3 smaller file(s) also have no living knowledge — folded into the freshness score and metrics rather than raised one row each — most significant first: benchmarks/snippets.py, benchmarks/benchmarks.py, rich/_windows_renderer.py (4 orphaned of 56 analysed files in total, counted over production source files of roughly 2,400 bytes or more, excluding vendored, generated and example/demo trees and test files identified by path convention, largest first; 56 of the 87 production source files in this repository met that bar). Attach the read to the next change that touches one of them: have a second person review that change, and leave behind a short comment or test recording what the file is for, so the knowledge comes back at the cost of a change you were making anyway.
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.
M2 · Architecture documentation · No architecture diagram/doc · ×1
  • No architecture diagram/doc — No C4/Structurizr/PlantUML/Mermaid/Graphviz/D2 diagram, no drawn diagram named for the architecture, no file named `architecture` or `design` in any markup this check reads, and nothing in the README, docs or contributor guides that announces the shape — no `## Architecture` heading, no "architecture overview"/"high-level design" phrasing, no "the architecture is …" introduction, no guided code tour. A shape laid out in prose that never names itself as the architecture is not visible to this check, and neither is one kept outside the repository, so this row reports the absence of a re-findable shape document — not evidence that nobody wrote the shape down.
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'.
X10 · Duplicated predicate · Duplicated predicate · ×1
  • Duplicated predicate rich/pretty.py:331 — `self.indent_guides and not options.ascii_only` appears character-identically in 2 files — rich/pretty.py, rich/syntax.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.
Minor — 1 finding(s)
D12 · Dependency Hygiene · Dependency hygiene PARTLY measured · ×1
  • Dependency hygiene PARTLY measured — Python dependencies read, no exact pin to grade for currency — This repository's Python dependencies were read: 3 shipped distribution(s) across 2 manifest(s) (11 development or optional declaration(s) excluded, because a consumer does not install them). Whether any of them is behind its current release is the dependency-CURRENCY question, and no declaration here carries an EXACT pin to ask it about — every one is a floor or a range, which installs the newest release it admits and therefore cannot be behind one. That is a healthy declaration style, NOT a defect and NOT a gap in this analyzer; there is simply no currency question to answer. This is NOT a finding that these dependencies are current or healthy. Lockfiles are deliberately not read (REDACTED, uv.lock, Pipfile.lock, pdm.lock): the four disagree about dev/optional membership, and misreading one would charge a test-only package a consumer never receives. Known CVEs in the same dependency graph are a separate question, reported under D30.

Appendix B — Reproduction & audit trail

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

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-2836a2f11939436692ff61373c0348ab/history.json --exit-code 0 --source .1artifacts/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-2836a2f11939436692ff61373c0348ab/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 .21artifacts/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 .5artifacts/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 01a170bd-4230-740a-a70d-c0b35e960c70 · every finding is also locatable in findings.md, and the complete scoring record (with exit codes + durations) in sidecar.json.

Issues: 20 · Warnings: 98 · Recommendations: 13 · Info: 1 — Appendix A · all findings · full markdown report.
Generated by Watchdog — deterministic code-health analysis. 25-10-2026 @ 01:46 UTC.

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