Public report — SuperPVZTrainner, published 8 Aug 2026.
Concrete security findings (CVE IDs, secret matches, dependency versions) are hidden in this version;
ask the repo owner for the full report.
117findings with an exact file:lineof 132 — the remainder are repo-wide signals (a dimension-level measurement, not a single line); open any file:line and verify
37/92dimensions across the health lenses4557 LoC · 9 projects — wide & deep
Executive summary
Read through the Production lens — the standard calibration. *Green* means good enough to run in production. The score is absolute and comparable across repos.
Lazuplis-Mei/SuperPVZTrainner carries serious gaps (41%). Several issues below can materially affect correctness, security, or the cost of changing it — and propagate to everything that depends on it.
It is strongest in Security (100%) — its security and compliance posture is in good shape. Architecture (95%) is solid too.
The area that most needs attention is Readiness (17%) — releases are harder to depend on — versioning, release notes and dependency hygiene are thin, so consumers can't easily tell what changed or trust an upgrade. Maturity (36%) is the next concern — onboarding is slow — key decisions and the architecture aren't written down, so contributors have to reverse-engineer the intent.
Leadership focus, highest impact first: CI workflow that builds and runs the test suite on every push/PR (CI/CD gates); ILogger (or Serilog) and log at meaningful points across… (Observability); 1 No automated tests finding(s) in Code Coverage (Code Coverage).
For scale: Small (~4,557 production lines); rebuilding it from scratch would take roughly ~0.1 person-years (~1 engineer). Approximate, ±~30%.
Encouragingly, the gaps are in documentation and release process — not in the code's correctness, structure or security, which are strong. They're low-risk to close, and doing so would lift the grade without re-engineering anything that already works.
How the score is built — each lens's share of the headlineWidth is the lens's weight in the worst-heaviest fold (the weakest area pulls hardest); colour is that lens's own band. A lens fixes the score in proportion to its width.
A full-fidelity diff against the previous run's complete recorded findings — line-move tolerant: a finding that only shifted line counts as unchanged, only genuinely new titles/files surface here.
This codebase represents roughly ~0.1 person-years of build effort (about ~€13,000 to rebuild). Its weakest lens is Readiness at 17% — the part of that asset most exposed by the findings below.
How we model this: boilerplate at a scaffolding rate + logic × domain Standard (×1.2) — desktop/game, high decision density × a 0.7× quality factor, at €60–95/h; indicative, ±~30%. Indicative only — most sensitive to the hourly rate and the domain tier (both tunable in config).
Top priorities
The highest-leverage moves; the full ranked list is in the Roadmap below.
1
Resolve the 1 No automated tests finding(s) in Code Coverage.
Value concentrated against a weak lens · High · Value at risk
This is a Small asset (~0.1 person-years to rebuild), and its weakest lens is Readiness at 17%. The operational and business risk on an asset this size concentrates there — that's where remediation buys the most protection.
→ Direct remediation budget at Readiness first — highest risk-reduction per euro on an asset this size.
Highest-leverage move · Medium · Leverage
Of everything flagged, the best return on effort is: Add a CI workflow that builds and runs the test suite on every push/PR. The rest can wait behind it.
Evidence: priority ranking: top of 5 ranked by impact/effort
→ Add a CI workflow that builds and runs the test suite on every push/PR.
A velocity tax on every change · Medium · Economics
The code-quality signals (complexity, duplication, cohesion) average 7.3/10, which acts as a tax on every change in the weaker areas: modifications there plausibly cost on the order of 2–5% more than in clean code, and the tax compounds as the codebase grows. (A modelled estimate, not a measured fact.)
Evidence: D1/D2 complexity, D4 duplication, D6 cohesion: averaging 7.3/10 across the code-quality signals
→ Pay it down where churn is highest — the hotspots — not everywhere; that's where the tax is actually paid.
Architecture — module dependency graph
Project dependencies, layered top-to-bottom; arrows show direction. Any dashed red edge points upward or sideways — a layering smell or cycle. A clean layered graph has none.
First, establish a continuous integration workflow to automatically build and test the codebase on every push or pull request. Next, implement structured logging and health checks across all services to improve observability and reliability. Then, address the single gap in automated testing to ensure code coverage is complete. After that, identify and add missing tests to improve test distribution. Finally, expand the README with a getting-started guide, architecture overview, and project map to improve documentation.
Ranked by impact ÷ effort. "Helps" is the estimated gain on the 0–100 health score.
Do this
Helps
Effort
Dimension
Resolve the 1 No automated tests finding(s) in Code Coverage.
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. 35 of 37 evaluated dimensions are computed purely by tools and static analysis (confidence 1.0); 2 documentation/naming judgement(s) are LLM-assisted and labelled advisory. Overall confidence is 0.5 — 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 — 37 dimensions across the health lenses
Each chip is a dimension scored from real signals across architecture, testing, dependencies, security & compliance, documentation, git-history and code quality — in one coherent pass. A surface report typically covers a handful.
How to trust any code-health report — three questions
Can you open the finding? Real findings cite a repo-relative file and line you can open at the cited line — never an absolute scratch path. Here, 117 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.)
Is there a tool behind the number? Every score below names the method that produced it — Roslyn, git, a scanner, or (for a handful of documentation/naming dimensions) an LLM labelled sampled · advisory — not a narrative.
Does re-running give the same result? Run it again on the same commit and the score — and this report, byte for byte — is identical. A report whose numbers move between runs is describing the run, not the code.
This report answers yes to all three. That's the bar to hold any assessment to.
Tools & methods
The actual versions used this run (captured at analysis time) — re-run on the same commit for the identical score.
Method
Backs
Version
Evaluator
Roslyn static analysis
Complexity, cohesion, coupling, dead code, API surface, layering
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.
D24 Comment Value — LLM provider failed — The model provider returned an unusable result, so this LLM-assisted dimension fell back to a measurement gap (confidence 0) rather than a penalty. Re-run with a reachable provider to score it.
D30 Dependency Vulnerabilities — scanner not present in this environment — The backing tool was not installed where this scan ran, so this dimension was not scored. Install the tool (or run in the hosted environment, where it is always present) for a graded result.
D31 IaC & Container Security — scanner not present in this environment — The backing tool was not installed where this scan ran, so this dimension was not scored. Install the tool (or run in the hosted environment, where it is always present) for a graded result.
D32 Data Compliance (PII/GDPR) — scanner not present in this environment — The backing tool was not installed where this scan ran, so this dimension was not scored. Install the tool (or run in the hosted environment, where it is always present) for a graded result.
D33 JS/npm Dependency Vulnerabilities — scanner not present in this environment — The backing tool was not installed where this scan ran, so this dimension was not scored. Install the tool (or run in the hosted environment, where it is always present) for a graded result.
D36 Supply-chain Provenance & Signing — scanner not present in this environment — The backing tool was not installed where this scan ran, so this dimension was not scored. Install the tool (or run in the hosted environment, where it is always present) for a graded result.
D37 Vulnerability-disclosure Policy — scanner not present in this environment — The backing tool was not installed where this scan ran, so this dimension was not scored. Install the tool (or run in the hosted environment, where it is always present) for a graded result.
D38 OSV Dependency Vulnerabilities — scanner not present in this environment — The backing tool was not installed where this scan ran, so this dimension was not scored. Install the tool (or run in the hosted environment, where it is always present) for a graded result.
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 (jscpd) — it finds copy-paste, not semantic duplication expressed differently. Committed machine-written code (EF migration scaffolds, *.Designer.cs, model snapshots) is EXCLUDED — its repetition is the tool's, not the team's — so the score reflects hand-written duplication only; the generated footprint is reported separately under Solution Shape.
D5 Coupling: Coupling is measured between projects/assemblies — runtime coupling through DI, reflection, messaging or shared databases is invisible to a static reference graph.
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.
D8 Code Coverage: Coverage is measured by building and running the suite (`dotnet test --collect`) inside Watchdog's isolated image — the target repo is never modified, and nothing on your systems runs. So coverage exists only when the suite builds and runs within the inline time budget; one that needs external services, can't build, or exceeds the budget yields no coverage (D8 then degrades to not-measured, not a low score). Line coverage also says nothing about assertion quality.
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.
D12 Dependency Hygiene: Dependency health reads manifests and lockfiles — a vulnerability in a vendored/copied dependency, or risk from how a dependency is actually used, is outside this view.
D13 Secret Scanning: Secret detection is signature- and entropy-based on the current tree — a secret that does not match a known pattern, or one already rotated, will not be flagged (a clean scan is "nothing matched", not "no secrets exist").
D15 Churn × Complexity Hotspots: Churn hotspots come from git history — a freshly imported or squashed repository has no churn signal, and recent rewrites can mask a historically risky file.
D17 Explicit Debt: Acknowledged-debt signals (TODO/FIXME, suppressions, dead code) are textual — undocumented debt that nobody marked, and debt that lives in design rather than annotations, is invisible. Committed machine-written code (EF migrations, designer files, snapshots) is excluded — it is never the team's dead code to delete.
D18 Solution Shape: Build integrity reflects whether the solution compiled in this environment — a build that needs a private feed, a specific SDK, or a generated file absent from the repo can read as broken when it is merely unreproducible here.
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.
D20 ADR Quality: ADR quality is an LLM read of the decision records present — it cannot know about decisions made and never recorded, and its verdict is sampled and advisory.
D21 Naming Consistency: Naming quality is an LLM judgement over a bounded sample — it assesses clarity/consistency of the names it sees, not domain-correctness, and is advisory.
D26 Project Cohesion: Project focus is sized from members/namespaces per project — a project that is broad by deliberate design reads the same as one that has sprawled.
D28 Secrets (history): Secret-history scanning sweeps the git log for known patterns — a secret that predates the available history, or never matched a signature, is not found (clean means "nothing matched in the history we can see").
D29 Static Analysis (SAST): SAST findings are pattern-based (semgrep) — it finds classes of bug it has rules for; logic flaws, auth/authorization gaps and issues needing runtime context are out of reach (and clean means "no rule matched").
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.
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.
The LLM boundary
LLM-set scores this run (4): D19, D20, D21, M4 (model: Local LLM). For these, a model reads a bounded sample and sets the numeric score (documentation, ADR quality, naming, comment value, onboarding) — D25 sets the ADR-conformance fraction over sampled code, D22 judges API accuracy over a sample. These 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.
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.
+ 11 more group(s) — more in Appendix A; the complete list is findings.md.
What to do
Resolve the 1 UserControl1.ImageBackground_MouseDown (cyclomatic 37) finding(s) in Cyclomatic Complexity — start with UserControl1.xaml.cs. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 Program.Mainloop (cyclomatic 27) finding(s) in Cyclomatic Complexity — start with Program.cs. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 LawnStringsManager.FindItem (cyclomatic 26) finding(s) in Cyclomatic Complexity — start with LawnStringsManager.xaml.cs. — One of this dimension's main actionable groups (1 warning-level).
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.
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.
+ 26 more group(s) — more in Appendix A; the complete list is findings.md.
What to do
Resolve the 1 LawnStringsManager.FindItem (cognitive 82) finding(s) in Cognitive Complexity — start with LawnStringsManager.xaml.cs. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 ModifyWindow.BtnSetZombieSeed_Click (cognitive 70) finding(s) in Cognitive Complexity — start with ModifyWindow.xaml.vb. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 UserControl1.ImageBackground_MouseDown (cognitive 65) finding(s) in Cognitive Complexity — start with UserControl1.xaml.cs. — One of this dimension's main actionable groups (1 warning-level).
Enforce Cognitive Complexity in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Prevented — provenance only; does not change the score.
Detailed fixes: d2_recommendation.md · top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D3 · God Classes8.7 / 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.
Resolve the 5 FileTooLong finding(s) in God Classes — start with MainWindow.xaml.vb, ModifyWindow.xaml.vb, MonitorWindow.xaml.vb. — One of this dimension's main actionable groups (5 warning-level).
Resolve the 5 TooManyMethods finding(s) in God Classes — start with PVZClass.vb (2), MainWindow.xaml.vb, ModifyWindow.xaml.vb. — One of this dimension's main actionable groups (5 warning-level).
Resolve the 1 ClassTooLong finding(s) in God Classes — start with PVZClass.vb. — One of this dimension's main actionable groups (1 warning-level).
Enforce God Classes in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Prevented — provenance only; does not change the score.
Detailed fixes: d3_recommendation.md · top locations in Appendix A, every location in findings.md.
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.
+ 11 more group(s) — more in Appendix A; the complete list is findings.md.
✓ On the Gold path — maintain.
Detailed fixes: d4_recommendation.md · top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D5 · Coupling8.2 / 10Strong✓ Tool-verified
What it measures: Whether volatile projects sit underneath others that depend on them (so their churn ripples upward), and whether project dependencies form cycles. A widely-depended-on but stable shared/kernel project is healthy, not penalised.
Method: Dependency cycles via elementary-DFS over real .csproj references, plus Martin instability (afferent/efferent) per project. Exhaustive over the reference graph, deterministic.
Coverage: Exhaustive · type-level: afferent/efferent coupling + cycles computed over every production type — the population is all types, not a name convention.
Resolve the 2 Off the main sequence finding(s) in Coupling. — One of this dimension's main actionable groups (2 warning-level).
Enforce Coupling in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Prevented — provenance only; does not change the score.
Detailed fixes: d5_recommendation.md · top locations in Appendix A, every location in findings.md.
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.
Resolve the 8 Low cohesion finding(s) in Cohesion (LCOM4) — start with InputDialog.xaml.vb, MainWindow.xaml.vb, ModifyWindow.xaml.vb. — One of this dimension's main actionable groups (8 warning-level).
Enforce Cohesion (LCOM4) in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Verified — provenance only; does not change the score.
Detailed fixes: d6_recommendation.md · top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D8 · Code Coverage0.0 / 10Critical✓ Tool-verified
What it measures: How much of the code is actually exercised by tests.
Method: Coverage from coverlet runs or committed reports (Cobertura/OpenCover/lcov), computed per-file with structured exclusions for generated, trivial, and glue code. When the suite can't be built/run in-image AND no report is committed, coverage is reported NOT-MEASURED (excluded from the score) with the precondition to make it measurable — never a LoC-ratio proxy folded in as if measured. Deterministic.
No automated tests — the solution has no test code.
No automated tests
What to do
Resolve the 1 No automated tests finding(s) in Code Coverage. — One of this dimension's main actionable groups (1 issue-level).
Enforce Code Coverage in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Verified — provenance only; does not change the score.
Detailed fixes: d8_recommendation.md · top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D9 · Test Distribution0.0 / 10Critical✓ 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.
What it measures: Whether dependencies are current, secure, and not bloated.
Method: Manifest scan via dotnet list package across all projects; worst-signal-per-package deduction (saturating for vulnerabilities, capped-linear for deprecation/outdated) per KLoC. Exhaustive, deterministic.
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.
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.
Detailed fixes: d15_recommendation.md · top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D17 · Explicit Debt8.8 / 10Strong✓ 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.
Resolve the 10 EmptyCatchBlock finding(s) in Explicit Debt — start with MonitorWindow.xaml.vb (6), MainWindow.xaml.vb (2), ITrainerExtension.cs. — One of this dimension's main actionable groups (10 issue-level).
Resolve the 2 ObsoleteWithCallers finding(s) in Explicit Debt — start with ExpendWindow.xaml.vb (2). — One of this dimension's main actionable groups (2 warning-level).
Resolve the 2 ObsoleteWithoutCallers finding(s) in Explicit Debt — start with Application.xaml.vb, ExpendWindow.xaml.vb. — One of this dimension's main actionable groups (2 recommendation-level).
Enforce Explicit Debt in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Prevented — provenance only; does not change the score.
Detailed fixes: d17_recommendation.md · top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D18 · Solution Shape8.2 / 10Strong✓ Tool-verified
What it measures: Whether the solution is laid out in a sensible, conventional structure.
Method: Solution structure: project count, decomposition, shell-project detection, build success (confirmed failures cap the score); traced to actual .sln files and binaries. Deterministic.
Resolve the 2 Shell project finding(s) in Solution Shape — start with PVZClass.vbproj, WPFTrainner.vbproj. — One of this dimension's main actionable groups (2 recommendation-level).
Resolve the 1 Monorepo finding(s) in Solution Shape. — One of this dimension's main actionable groups (1 warning-level).
Detailed fixes: d18_recommendation.md · top locations in Appendix A, every location in findings.md.
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.
The only visible document is a single README for the SuperPVZTrainner project that describes itself as 'Super PlantsVsZombies Trainner' and contains no installation, usage, or architecture information. No architecture/design docs exist in the directory tree, and XML documentation coverage across all referenced assemblies is zero (0/10) to 53% (WPFTrainner), with only IZFormatSetter at 10%, indicating comprehensive code doc coverage is missing.
No installation, prerequisites, or usage instructions for the trainer.README.md
No architecture or component-design description of what the trainer does.README.md
Resolve the 1 No installation, prerequisites, or usage instructions for the trainer. finding(s) in Documentation Quality — start with README.md. — One of this dimension's main actionable groups (1 recommendation-level).
Resolve the 1 No architecture or component-design description of what the trainer… finding(s) in Documentation Quality — start with README.md. — One of this dimension's main actionable groups (1 recommendation-level).
Detailed fixes: d19_recommendation.md · top locations in Appendix A, every location in findings.md.
What it measures: Whether architecture decisions are recorded well (context, decision, consequences).
Method: Per-ADR judgment by language model at low temperature with two-pass stability; confidence is share of ADRs evaluated; enforcement-field presence detected deterministically. Advisory.
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.
What it measures: Whether any secrets were ever committed — scanned across the full git history, not just now.
Method: Git-history secret scan via gitleaks detect over full history in an isolated checkout; each match flagged High. Exhaustive; degrades cleanly when tool absent.
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).
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; coupling through a build step, config, or non-source file isn't seen.
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.
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 — check that business logic isn't leaking into the application/infrastructure layers (a thin domain is the anemic-domain smell).
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.
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.
Other · Architecture — Whether the codebase has a recognisable, scale-appropriate structure (a named architectural style, or modular enough for its size) rather than being an ad-hoc ball of mud.
Method: Roslyn plus csproj analysis: architecture style detection (DDD, clean, vertical-slice, CQRS) and structure fitness for repo size. Deterministic.
Other · Code Health — Unreviewed-generation residue: shipped members still throwing NotImplementedException, and placeholder string literals left in non-test, non-generated code. Scored as a quality signature, never as a claim about authorship.
Method: Roslyn syntax scan: NotImplementedException throws and placeholder string literals in non-test, non-generated shipped code. Deterministic, code-shape signature.
Other · Code Health — Unfinished work detected by code SHAPE, not keywords: members that only throw a "not implemented" exception, methods that take inputs and return a constant, async methods that never await, dead `if (false)` / `#if false` branches, and skeleton types most of whose members are holes. A real, objective slice of technical debt.
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.
The root README is 5 words — likely missing build/run/architecture context.
What to do
Expand the README with getting-started, architecture overview and a project map.
Add a build/run (quick start) section to the root README — the first thing a newcomer needs.
Add a 'Testing' section to the root README — how to run the test suite.
Add an 'Architecture' / 'How it works' section to the root README — the high-level shape.
Add a README to the 9 of 9 project(s) that lack one — worth up to 2 pts.
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.
Projects aren't grouped under a src/ folder — production and tooling code are mixed at the root.
Test projects aren't grouped under a tests/ folder — the test surface isn't separable from production code at a glance.
Only 1/9 projects share a common root namespace — the code's module identity is inconsistent.
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.
Group test projects under tests/ (or test/, spec/) so the test surface is discoverable and CI can scope it.
Adopt a consistent root-namespace convention (a shared prefix, e.g. Acme.*); short project-file/directory names are fine as long as the RootNamespace is uniform.
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.
Do you agree with this assessment?
P1 · CI/CD gates0.0 / 10Critical✓ Tool-verified
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.
No CI workflow found (.github/workflows, azure-pipelines.yml, .gitlab-ci.yml, …) — changes aren't gated by an automated build/test.
What to do
Add a CI workflow that builds and runs the test suite on every push/PR.
Do you agree with this assessment?
P2 · Observability0.0 / 10Critical✓ Tool-verified
Readiness · Readiness — Whether the code is diagnosable in production — structured logging, tracing/metrics, health checks.
Readiness · Readiness — Whether SAST, secret/dependency scanning and performance benchmarking are wired in (presence, not runtime).
Method: Filesystem/Roslyn scan: CodeQL, Dependabot, secret-scanning, and BenchmarkDotNet presence in pipelines and projects. Exhaustive, deterministic.
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.
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.
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. — ITrainerExtension.cs:53
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. Deterministic.
Do you agree with this assessment?
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.
Not included — 56 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 — no DI registrations detected
AX2 Stateful singletons — no singleton implementations detected
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
C1 Data Protection — No personal data detected in the analyzed source — no PII-typed entity/column names (Email, FirstName, DateOfBirth, …), no ASP.NET Identity / user-account model, and no stored user credentials. GDPR data-protection controls are therefore N/A here. If this is intentional, record the no-PII posture in an ADR; if the app does process personal data, name those fields conventionally so this dimension activates.
C2 Access Controls — No access-control surface detected in the analyzed source — no web/app surface to authorize (no HTTP API or web-UI project) and no authorization code at all (no [Authorize]/policies, no imperative guard methods). Access control is therefore N/A here — this is a library/CLI, which is authorized by its CALLER, 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 the analyzed source — no PII-typed entity/column names (Email, FirstName, DateOfBirth, …), no ASP.NET Identity / user-account model, and no stored user credentials. GDPR data-protection controls are therefore N/A here. If this is intentional, record the no-PII posture in an ADR; if the app does process personal data, name those fields conventionally so this dimension activates.
C4 Data Retention — No personal data detected in the analyzed source — no PII-typed entity/column names (Email, FirstName, DateOfBirth, …), no ASP.NET Identity / user-account model, and no stored user credentials. GDPR data-protection controls are therefore N/A here. If this is intentional, record the no-PII posture in an ADR; if the app does process personal data, name those fields conventionally so this dimension activates.
C5 Data-Subject Rights — No personal data detected in the analyzed source — no PII-typed entity/column names (Email, FirstName, DateOfBirth, …), no ASP.NET Identity / user-account model, and no stored user credentials. GDPR data-protection controls are therefore N/A here. If this is intentional, record the no-PII posture in an ADR; if the app does process personal data, name those fields conventionally so this dimension activates.
D10 Test Quality — No tests in the analyzed solution to assess for quality.
D11 Test Reliability — Test reliability not included
D14 License Compliance — license scan produced no result — the tool ran but its JSON output could not be parsed; the offline NuGet fallback resolved nothing
D16 Bus Factor — single-maintainer — knowledge-concentration (bus factor) risk
D22 Internal API Consistency — No exposed public API
D23 Boundary Type-Coupling — Bounded contexts not declared
D24 Comment Value — LLM evaluation failed
D25 ADR Conformance — no ADRs to check
D27 Navigability — symbol resolution incomplete — navigability not assessed
D30 Dependency Vulnerabilities — the solution did not restore on the analyzer's .NET SDK (an SDK/target-framework/restore mismatch, common for an older codebase), so there was no restored dependency graph to scan for NuGet CVEs — excluded rather than scored; re-run on an SDK that can restore this solution
D31 IaC & Container Security — No Infrastructure-as-Code or container manifests found (Dockerfile, Terraform, Kubernetes/Helm, CloudFormation); nothing to scan.
D32 Data Compliance (PII/GDPR) — No PII/GDPR ruleset is bundled (the public p/gdpr semgrep pack was retired) — data compliance is not assessed in this scan.
D33 JS/npm Dependency Vulnerabilities — No JS/npm manifest or lockfile found outside bin/obj (package.json, package-lock.json, yarn.lock, pnpm-lock.yaml, bun.lockb); no JS dependencies to scan.
D34 Knowledge Freshness — early-stage repository — too little history to judge knowledge freshness
D36 Supply-chain Provenance & Signing — No CI/build pipeline found (.github/workflows, .gitlab-ci.yml, azure-pipelines.yml, Jenkinsfile, .circleci); there is no build to attest provenance for.
D37 Vulnerability-disclosure Policy — No vulnerability-disclosure policy file found (SECURITY.md, .github/SECURITY.md, docs/SECURITY.md, .well-known/security.txt). A coordinated-disclosure policy may live off-repo, so this is not evidenced rather than failed.
D38 OSV Dependency Vulnerabilities — No JS/npm lockfile found outside bin/obj (package-lock.json, yarn.lock, pnpm-lock.yaml, bun.lockb); nothing for OSV to scan.
D39 IL Efficiency — The target did not build, so no IL was available to measure.
D7 Architectural Integrity — no checkable ADRs and no dependency cycles — architectural integrity not assessed
DM1 Domain Modelling — not run — 0/3 markers found
ED1 Event-Driven — not run — 0/3 markers found
ED5 Idempotency — no mutating command handlers or message consumers detected — idempotency check not applicable
ES1 Event Sourcing — not run — 0/3 markers found
P12 CI test-gate honesty — no CI workflow found
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
P6 Release Hygiene — not evidenced — no changelog, version stamp or semver release tag in the repo
P7 Outbound HTTP resilience — not applicable — this isn't a service/API/worker
P8 Schema migrations — no EF Core usage detected
P9 Domain vs controller coverage — no coverage report found on disk — run tests with `--collect:"XPlat Code Coverage"` (or in CI) to enable this cross-layer check
PF1 Benchmark discipline — Performance is assessed only for perf-relevant repos — a packaged library, one that ships benchmarks, or one already using allocation-aware APIs. This repo isn't one, so the Performance lens is not applicable and is excluded from the score.
PF2 Allocation hygiene — Performance is assessed only for perf-relevant repos — a packaged library, one that ships benchmarks, or one already using allocation-aware APIs. This repo isn't one, so the Performance lens is not applicable and is excluded from the score.
PF3 Async & latency hygiene — Performance is assessed only for perf-relevant repos — a packaged library, one that ships benchmarks, or one already using allocation-aware APIs. This repo isn't one, so the Performance lens is not applicable and is excluded from the score.
S1 Web-Security Posture — No web surface detected in the analyzed source — no HTTP API or web-UI project (no controllers/minimal-API endpoints, no Razor/Blazor views) and no web middleware (HTTPS redirection, HSTS, security headers, cookies). Transport security, security headers, secure cookies, CSRF/input-validation and middleware-order controls are therefore N/A here — this is a library/CLI/worker, not a web app. Crypto hygiene was still checked and found nothing to flag. If this codebase becomes web-facing, the dimension reactivates automatically.
SC1 Supply-chain hygiene — no data
X2 Cancellation propagation — no async methods found
X5 Nullable reference types — no NRT-eligible projects
X6 Hand-rolled structured-format parsing — no data
X7 Silent fallback defaults — no data
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.
Low cohesion: ModifyWindow (LCOM4 64) WPFTrainner/WPFTrainner/ModifyWindow.xaml.vb:4— ModifyWindow's methods form 64 groups that share no state and don't call each other — a sign it may have several responsibilities. Review whether it splits into focused classes.
Low cohesion: MonitorWindow (LCOM4 17) WPFTrainner/WPFTrainner/MonitorWindow.xaml.vb:5— MonitorWindow's methods form 17 groups that share no state and don't call each other — a sign it may have several responsibilities. Review whether it splits into focused classes.
Low cohesion: MainWindow (LCOM4 17) WPFTrainner/WPFTrainner/MainWindow.xaml.vb:10— MainWindow's methods form 17 groups that share no state and don't call each other — a sign it may have several responsibilities. Review whether it splits into focused classes.
Low cohesion: OperationWindow (LCOM4 9) WPFTrainner/WPFTrainner/OperationWindow.xaml.vb:4— OperationWindow's methods form 9 groups that share no state and don't call each other — a sign it may have several responsibilities. Review whether it splits into focused classes.
Low cohesion: WaveManageDialog (LCOM4 8) WPFTrainner/WPFTrainner/WaveManageDialog.xaml.vb:4— WaveManageDialog's methods form 8 groups that share no state and don't call each other — a sign it may have several responsibilities. Review whether it splits into focused classes.
Low cohesion: ProcessSelector (LCOM4 6) WPFTrainner/WPFTrainner/ProcessSelector.xaml.vb:6— ProcessSelector's methods form 6 groups that share no state and don't call each other — a sign it may have several responsibilities. Review whether it splits into focused classes.
Low cohesion: ZombieListDialog (LCOM4 4) WPFTrainner/WPFTrainner/ZombieListDialog.xaml.vb:3— ZombieListDialog's methods form 4 groups that share no state and don't call each other — a sign it may have several responsibilities. Review whether it splits into focused classes.
Low cohesion: InputDialog (LCOM4 4) WPFTrainner/WPFTrainner/InputDialog.xaml.vb:1— InputDialog's methods form 4 groups that share no state and don't call each other — a sign it may have several responsibilities. Review whether it splits into focused classes.
Off the main sequence: PVZClass — PVZClass: abstractness 0.00, instability 0.00, distance 1.00 — zone of pain — concrete and heavily depended-on, so it's rigid to change.
Off the main sequence: DarkStyle — DarkStyle: abstractness 0.00, instability 0.00, distance 1.00 — zone of pain — concrete and heavily depended-on, so it's rigid to change.
Monorepo: only 1 of 4 solutions was scored — This repository contains 4 .NET solutions, but a scan analyzes ONE. Every score, lens, and finding here reflects only `WPFTrainner/WPFTrainner.sln` — the other 3 (`IZFormatSetter/IZFormatSetter.sln`, `PVZClass/PVZClass.sln`, `PVZScript/PVZScript.sln`) were not analyzed and are not represented in the headline. To cover them, scan each solution as its own target and group them in a Solution or Product for a portfolio roll-up. If a secondary solution is an archived or vendored tree, declare it — `.gitattributes` (`path/** linguist-vendored`) or `.editorconfig` (`[path/**] generated_code = true`) — to exclude it from discovery the same way generated code is.
LLM evaluation failed — JSON parse error: Expected end of string, but instead reached end of data. Path: $.notable[5].comment | LineNumber: 0 | BytePositionInLine: 971.
Shell project: WPFTrainner WPFTrainner/WPFTrainner/WPFTrainner.vbproj— `WPFTrainner` contributes only 0 significant line(s) — an empty/placeholder project is structural noise. Remove it or fold its contents into a real project.
Shell project: PVZClass PVZClass/PVZClass/PVZClass.vbproj— `PVZClass` contributes only 0 significant line(s) — an empty/placeholder project is structural noise. Remove it or fold its contents into a real project.
D11 · Test Reliability· Test reliability not included · ×1
Test reliability not included — No test projects found, so reliability couldn't be assessed.
D19 · Documentation Quality· No installation, prerequisites, or usage instructions for the trainer. · ×1
No installation, prerequisites, or usage instructions for the trainer. README.md— Add a short 'Getting Started' section covering how to install and run the trainer.
D19 · Documentation Quality· No architecture or component-design description of what the trainer does. · ×1
No architecture or component-design description of what the trainer does. README.md— Describe the trainer's purpose, its role in the SuperPVZ modding pipeline, and any external dependencies it requires.
No ADRs found — No ADRs found at common paths; consider documenting architectural decisions in Docs/ADL/ or similar.
D23 · Boundary Type-Coupling· Bounded contexts not declared · ×1
Bounded contexts not declared — At 16752 LoC across 9 projects the codebase is large and multi-module, so explicit bounded contexts are needed. Declare architecture.contexts (≥2) in config to assess cross-boundary type coupling.
early-stage repository — too little history to judge knowledge freshness — early-stage repository — too little history to judge knowledge freshness (10 commit(s) sampled).
git history depth insufficient — git history depth insufficient — install a full clone for reliable trend signal.
D18 · Solution Shape· Build did not complete in the analyzer · ×1
Build did not complete in the analyzer — `dotnet build` reported 9 error(s) but no C# compiler diagnostic — an SDK / target-framework / restore mismatch in the analyzer environment, not a code defect (common for an older codebase whose target framework the analyzer's SDK can't build). Solution Shape is scored on structure and is NOT capped; the C# semantic analysis loads independently and is unaffected.
D22 · Internal API Consistency· No exposed public API · ×1
No exposed public API — No intentionally-exposed types (IsPackable or .Contracts) to evaluate.
D35 · Change Coupling· git history depth insufficient · ×1
git history depth insufficient — git history depth insufficient — a full clone gives reliable change-coupling.
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.
dotnet: not applicable — the solution did not restore on the analyzer's .NET SDK (an SDK/target-framework/restore mismatch, common for an older codebase), so there was no restored dependency graph to scan for NuGet CVEs — excluded rather than scored; re-run on an SDK that can restore this solution
trivy: not applicable — No Infrastructure-as-Code or container manifests found (Dockerfile, Terraform, Kubernetes/Helm, CloudFormation); nothing to scan.
trivy: not applicable — No JS/npm manifest or lockfile found outside bin/obj (package.json, package-lock.json, yarn.lock, pnpm-lock.yaml, bun.lockb); no JS dependencies to scan.
provenance: not applicable — No CI/build pipeline found (.github/workflows, .gitlab-ci.yml, azure-pipelines.yml, Jenkinsfile, .circleci); there is no build to attest provenance for.
disclosure: not applicable — No vulnerability-disclosure policy file found (SECURITY.md, .github/SECURITY.md, docs/SECURITY.md, .well-known/security.txt). A coordinated-disclosure policy may live off-repo, so this is not evidenced rather than failed.
osv-scanner: not applicable — No JS/npm lockfile found outside bin/obj (package-lock.json, yarn.lock, pnpm-lock.yaml, bun.lockb); nothing for OSV to scan.
0
—
Run 019fdec6-24aa-7713-9318-d31f1445c243 · every finding is also locatable in findings.md, and the complete scoring record (with exit codes + durations) in sidecar.json.
Issues: 11 · Warnings: 97 · Recommendations: 11 · Info: 13 — Appendix A · all findings · full markdown report.
Generated by Watchdog — deterministic code-health analysis. 08-08-2026 @ 00:29 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.