Public report — EventSourcingCQRS, published 18 Jun 2026.
Concrete security findings (CVE IDs, secret matches, dependency versions) are hidden in this version;
ask the repo owner for the full report.
14findings with an exact file:lineof 41 — the remainder are repo-wide signals (a dimension-level measurement, not a single line); open any file:line and verify
51/98dimensions across the health lenses1420 LoC · 9 projects — wide & deep
Executive summary
Read through the Template lens: this is a template / kata / sample / demo — code meant to be read or copied, not operated. The ship-it and operate-it dimensions (CI/CD, observability, ADRs, architecture docs, deployment security) are N/A, and the colour bands on what remains are relaxed to what an example needs. Code correctness stays near-strict; the score is absolute and comparable across repos.
VenomAV/EventSourcingCQRS is in a workable but fragile state (46%). It is not in crisis, but it carries material risk that makes change slower and incidents harder to contain if left unaddressed.
It is strongest in Architecture (99%) — the structure is clean and changes stay contained.
The area that most needs attention is Maturity (33%) — onboarding is slow — key decisions and the architecture aren't written down, so contributors have to reverse-engineer the intent. Readiness (54%) is the next concern — operating, monitoring and recovering the system safely is harder.
Leadership focus, highest impact first: security response headers (Content-Security-Policy (Web-Security Posture); root README: what the system is, how to build/run it, and a map… (Documentation (README)); README describing the system (Documentation accuracy).
For scale: Hobby (~1,420 production lines); rebuilding it from scratch would take roughly ~0.1 person-years (~1 engineer). Approximate, ±~30%.
It builds on a genuinely strong Architecture foundation (99%); the priorities above are the highest-leverage way to bring the rest up to that level.
This codebase represents roughly ~0.1 person-years of build effort (about ~€2,300 to rebuild). Its weakest lens is Maturity at 33% — the part of that asset most exposed by the findings below.
How we model this: boilerplate at a scaffolding rate + logic × domain High (×1.6) — service/app, DDD/clean architecture, CQRS, domain model × 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
Add security response headers (Content-Security-Policy, X-Frame-Options, X-Content-Type-Options) — defense in depth, even when a reverse proxy could set them.
Of everything flagged, the best return on effort is: Add security response headers (Content-Security-Policy, X-Frame-Options, X-Content-Type-Options) — defense in depth, even when a reverse proxy could set them. The rest can wait behind it.
Evidence: priority ranking: top of 5 ranked by impact/effort
→ Add security response headers (Content-Security-Policy, X-Frame-Options, X-Content-Type-Options) — defense in depth, even when a reverse proxy could set them.
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.
Findings mapped to OWASP categories; the specific CVEs/secrets are in the Security dimension cards below and findings.md (redacted only on the public version of this report).
OWASP category
Findings
Severity
A05:2021 — Security Misconfiguration
2
High / Critical
Roadmap
Top priorities: Add security response headers (Content-Security-Policy, X-Frame-Options, X-Content-Type-Options) — defense in depth, even when a reverse proxy could set them; Add a root README: what the system is, how to build/run it, and a map of the projects; Add a README describing the system, how to build/run it, and keep it current.
Ranked by impact ÷ effort. "Helps" is the estimated gain on the 0–100 health score.
Do this
Helps
Effort
Dimension
Add security response headers (Content-Security-Policy, X-Frame-Options, X-Content-Type-Options) — defense in depth, even when a reverse proxy could set them.
Enforce accessibility in the toolchain: add eslint-plugin-jsx-a11y (or vuejs-accessibility), assert with jest-axe / playwright-axe in tests, then gate axe/pa11y/Lighthouse in CI.
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. 51 of 51 evaluated dimensions are computed purely by tools and static analysis (confidence 1.0); none rely on LLM judgement. Overall confidence is 0.6 — 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 — 51 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, 14 of 41 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.
D19 Documentation Quality — LLM provider failed — The model provider was unreachable or errored, 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.
D21 Naming Consistency — LLM provider failed — The model provider was unreachable or errored, 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.
D23 Boundary Type-Coupling — evaluation did not complete — Dimension evaluation failed — excluded from the score.
D24 Comment Value — LLM provider failed — The model provider was unreachable or errored, 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.
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.
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.
D10 Test Quality: Assertion density is structural — it cannot tell a meaningful behavioural assertion from a trivial one, only that an assertion is present.
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").
D14 License Compliance: License compatibility is checked against declared package metadata and a policy — mislabelled or missing license metadata, and obligations that depend on how you distribute, are not resolved here.
D15 Churn × Complexity Hotspots: Churn hotspots come from git history — a freshly imported or squashed repository has no churn signal, and recent rewrites can mask a historically risky file.
D17 Explicit Debt: Acknowledged-debt signals (TODO/FIXME, suppressions, dead code) are textual — undocumented debt that nobody marked, and debt that lives in design rather than annotations, is invisible. Committed machine-written code (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.
D22 Internal API Consistency: API-surface coherence is an LLM judgement over a sample of the public surface — consistency of intent across the whole API is approximated, not exhaustively verified.
D26 Project Cohesion: Project focus is sized from members/namespaces per project — a project that is broad by deliberate design reads the same as one that has sprawled.
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").
D31 IaC & Container Security: IaC scanning checks Dockerfiles/Terraform/Kubernetes against best-practice rules — it cannot see the live cloud account, runtime configuration, or drift between the committed config and what is actually deployed.
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.
AC2 Forms & labels: Label association is read from static markup — a label wired up at runtime (JS-set aria-labelledby, framework-injected ids) reads as missing, a present label says nothing about whether its text is correct, and component-wrapped fields (e.g. a <TextField>) are skipped. A clean result is "no unlabelled native control found", not a labelling proof.
AC3 Page structure: Page structure is read from the static markup tree — landmarks, headings and lang injected at runtime aren't seen, heading ORDER is checked structurally (not against the rendered visual hierarchy), and lang/title/main fire only on full documents, never partials. Static readiness, not conformance.
AC5 ARIA correctness: ARIA correctness is checked against the static role/attribute shape — roles/attributes set dynamically aren't seen, a valid role says nothing about whether it matches the element's real behaviour, and required-state checks are suppressed when a JSX spread could supply them.
AC7 A11y enforcement: Enforcement is scored from in-repo config/CI evidence only — an a11y gate enforced in external tooling with no in-repo trace can't be credited, and a configured linter is presence, not proof the rules actually run or block a merge.
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 ADVISORY: an infrastructure-heavy design (a gateway, an ETL, a driver) is legitimately low without being unhealthy.
DM4 Rich vs anemic model: Behaviour is detected as state mutation inside a method body — a method that enforces an invariant by validating-and-throwing without mutating reads as a query, and mutation delegated through an interface the scan can't resolve isn't credited; entities with zero public properties still drop out of the population. It detects that state changes, not whether the rule is correct.
DM6 Domain ↔ infrastructure boundary: Infrastructure reached through a hand-rolled wrapper, a domain-named facade, reflection, or a string-keyed service locator resolves to a non-infra type and isn't seen; the body scan is symbol resolution over syntax, not full dataflow. A clean result means "no resolved infra reference in a domain body", not a proof of purity.
ED5 Idempotency: Idempotency is judged from the handler body's visible writes and guards — a guard enforced by a database unique constraint, a broker's exactly-once delivery, or a domain method whose no-op-when-applied logic the scan can't follow may read as at-risk; the at-risk candidates are confirmed by a SAMPLED LLM verdict (advisory, not exhaustive) and degrade to heuristic-only when no model is configured. It flags the at-least-once double-apply SHAPE, not a runtime proof of a duplicate effect.
M4 Documentation accuracy: Onboarding quality is an LLM read of the docs/setup present — it cannot run the onboarding or measure how long a real new joiner takes; the verdict is sampled and advisory.
P4 Deployment & Rollback: Approval/branch-protection rules live in repository settings the scan cannot see — only their in-repo evidence (config files, workflows) is checked, so a control enforced purely in the host's settings reads as "not evidenced".
P5 DR & Backup: Backup/restore and disaster-recovery readiness is judged from in-repo evidence — a config that exists is not a tested restore, so the absence of positive evidence is reported as "not evidenced", never scored as present.
The LLM boundary
LLM-set scores this run (3): D22, ED5, M4 (model: openai-compatible). 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.
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.
0 method(s) exceeded the cognitive complexity threshold of 15.
✓ On the Gold path — maintain.
Detailed fixes: d2_recommendation.md.
Do you agree with this assessment?
D3 · God Classes10.0 / 10Exemplary✓ 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.
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.
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.
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.
Detailed fixes: d6_recommendation.md · top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D9 · Test Distribution10.0 / 10Exemplary✓ Tool-verified
What it measures: Whether the test suite has a healthy mix of unit / integration / end-to-end tests.
Method: Test projects classified (Unit/Integration/BDD/E2E) from compiled metadata; test methods counted exhaustively across projects with placement-agnostic disk fallback. Deterministic.
33 test methods: 33 unit, 0 integration, 0 BDD, 0 e2e.
Unit tests
Integration tests
BDD tests
E2E tests
✓ On the Gold path — maintain.
Detailed fixes: d9_recommendation.md · top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D10 · Test Quality9.1 / 10Exemplary✓ Tool-verified
What it measures: Whether the tests truly assert behaviour rather than just running the code.
Method: Per-test assertions, skips, and mock references analyzed via Roslyn; structured skip-reason tags (BUG:/ENV:) separate documented deferrals from debt. 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: 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.
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.
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.
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.
9 projects, 60 .cs files, 2039 hand-written lines of code (1420 production / 619 test), 13 inter-project edges (build status unknown — did not finish).
+ 5 more group(s) — more in Appendix A; the complete list is findings.md.
✓ On the Gold path — maintain.
Detailed fixes: d18_recommendation.md · top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D22 · Internal API Consistency / 10Exemplary◐ Sampled · advisory
What it measures: Whether the internal API surface is consistent and coherent.
Method: Judged by language model at low temperature over a sample of the public API surface (IsPackable or .Contracts types). Sampled, advisory; confidence discounted by model uncertainty.
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 --config auto across the repo; severity rules (ERROR/WARNING/INFO) map to a 0-10 wide normalizer. 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.
No strong hidden change-coupling between production files.
git history depth insufficient
✓ On the Gold path — maintain.
Detailed fixes: d35_recommendation.md · top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
Frontend & cross-cutting dimensions
R = React/JS · M = Maturity · P = Readiness.
AC2 · Forms & labels6.0 / 10Healthy✓ Tool-verified
Other · Accessibility — Whether form controls have a programmatic label (an associated label, aria-label or aria-labelledby), buttons have text, fieldsets have a legend, and a placeholder isn't used as the only label. Static markup readiness, not a WCAG conformance claim.
Method: Static markup-model scan: inputs/selects/textareas checked for an associated label[for]/wrapping label/aria-label/aria-labelledby (per document), buttons for accessible text, fieldsets for a legend; placeholder-only labelling flagged. Deterministic, hard fact per control.
This control has no associated label. Add a <label for> / wrapping <label> / aria-label / aria-labelledby so assistive tech can name it. — DetailsAsync.cshtml:82
What to do
Give every control a programmatic label (a <label for> / wrapping <label> / aria-label) and every button text — a placeholder is not a label.
Do you agree with this assessment?
AC3 · Page structure4.3 / 10Fair✓ Tool-verified
Other · Accessibility — Whether pages declare a language and title, expose a main landmark and a sane heading order, keep zoom enabled, title their iframes and avoid meta-refresh. Static markup readiness, not a WCAG conformance claim.
Method: Static markup-model scan: html lang, document <title>, a main landmark and heading order on full documents only, plus zoom-disabling viewports, untitled iframes and meta-refresh anywhere. Deterministic, per structural checkpoint.
Skipping heading levels breaks the document outline assistive tech relies on. Don't jump levels — increase by at most one. (×2) — DetailsAsync.cshtml:52, IndexAsync.cshtml:45
The page declares no language, so assistive tech can't pick the right pronunciation. Add lang (e.g. lang="en"). — _Layout.cshtml:2
No <main> (or role="main") means no "skip to content" target and a weaker landmark map. Wrap the primary content in <main>. — _Layout.cshtml:2
What to do
Declare <html lang>, a document <title> and a <main> landmark, keep headings in order, leave zoom enabled, title iframes and drop meta-refresh.
Other · Accessibility — Whether ARIA is used correctly — valid non-abstract roles, the ARIA state a role requires, and no aria-hidden on a focusable element. Static markup readiness, not a WCAG conformance claim.
Method: Static markup-model scan: role values checked against the WAI-ARIA role set (abstract/invalid flagged), required ARIA state for a role, and aria-hidden on a focusable element. Deterministic, role/attribute level.
Do you agree with this assessment?
AC7 · A11y enforcement4.0 / 10Fair✓ Tool-verified
Other · Accessibility — Whether accessibility is ENFORCED in the toolchain — an a11y linter (eslint-plugin-jsx-a11y / vuejs-accessibility) configured, and axe/pa11y/Lighthouse wired into tests or CI — on the Documented→Verified→Prevented ladder.
Method: Repo config/CI scan: an a11y linter (eslint-plugin-jsx-a11y / vuejs-accessibility) configured, and axe/pa11y/Lighthouse in tests or CI, graded on the Documented→Verified→Prevented rungs. Deterministic, presence/rung detection.
No accessibility enforcement found — no a11y linter (eslint-plugin-jsx-a11y / vuejs-accessibility) and no axe/pa11y/Lighthouse in tests or CI. Start with the linter to catch issues at author time.
What to do
Enforce accessibility in the toolchain: add eslint-plugin-jsx-a11y (or vuejs-accessibility), assert with jest-axe / playwright-axe in tests, then gate axe/pa11y/Lighthouse in CI.
Other · Architecture — Whether any singleton service captures a scoped/transient dependency — a silent lifetime/threading bug.
Method: Roslyn scan: DI registrations parsed from AddSingleton/Scoped/Transient; each singleton checked for captured shorter-lifetime dependencies. Exhaustive, deterministic.
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.
Other · Architecture — Whether singleton services avoid mutable shared instance state that concurrent callers would race on.
Method: Roslyn scan: singleton field mutations unguarded by lock or Interlocked, per type; syntax-based guard detection. Deterministic, traceable per field.
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 · Architecture — Whether interfaces stay focused rather than fat — the Interface-Segregation principle (SOLID 'I').
Method: Roslyn scan: public interface member counts; fat-interface threshold (over 15 members) flagged per type. Deterministic, type-level.
Do you agree with this assessment?
AX8 · Test isolation10.0 / 10Exemplary✓ Tool-verified
Other · Architecture — Whether production projects stay free of references to test projects — tests may depend on production, never the reverse.
Method: Csproj graph: each production project checked for references to test projects (identified by test-framework presence, not name). Zero violations is clean. Deterministic.
Other · Domain Modelling — Whether aggregates reference each other by identity (id) rather than by direct object reference — the core DDD consistency-boundary rule.
Method: Roslyn (DDD-gated): aggregate roots identified by convention; each aggregate field checked for direct references to other aggregates versus id-only. Deterministic, DDD-native.
Coverage: Population: aggregate roots identified by AggregateRoot/IAggregateRoot base/interface NAME convention; reference-by-identity then checked exhaustively within that set — a root not using those names is invisible.
Other · Domain Modelling — How much of the domain uses strongly-typed ids vs raw Guid/string/int — adoption curve, not all-or-nothing.
Method: Roslyn (DDD-gated): strongly-typed id adoption on domain entities/events; raw Guid/int/string ids counted versus wrapped types. Deterministic, adoption percentage.
Coverage: Population: id-like members by *Id/*Key NAME suffix; strongly-typed-ID shape then checked semantically — non-suffixed identifiers are not seen.
`DomainEventBase.EventId` is a raw `Guid` — give it a strongly-typed id (`readonly record struct EventId { Guid Value }`). — DomainEventBase.cs:23
What to do
Adopt strongly-typed ids across the domain — finish the migration or document the boundary; primitive ids invite transposed-argument bugs.
Do you agree with this assessment?
DM4 · Rich vs anemic model3.0 / 10Poor✓ Tool-verified
Other · Domain Modelling — Whether aggregates/entities carry the behaviour that protects their invariants, rather than being data bags driven by external services.
Method: Roslyn (DDD-gated): entity method BODIES classified mutator-vs-query — only methods that mutate the entity's own declared state count as invariant-protecting behaviour, so a getter/passthrough doesn't rescue an anemic class. Deterministic, exhaustive over domain-layer entities.
Coverage: Population: entities by name/base convention; rich-vs-anemic judged by classifying each method body mutator-vs-query — logic-bearing domain types outside the convention are invisible.
`AggregateBase` is an aggregate/entity with 1 data propert(ies) but no state-changing behaviour (only data and queries) — the business logic lives in a service. — AggregateBase.cs:7
What to do
Move business rules onto the aggregates/entities they govern so invariants are enforced at the source, not in anemic services.
Other · Domain Modelling — Whether entities protect their state (private/init-only setters) instead of exposing public setters that bypass invariants. Softened when a rehydration framework (Marten/EF) is present.
Method: Roslyn (DDD-gated): public setters on entities detected; score softened when Marten/EF rehydration frameworks present. Deterministic, framework-aware.
Coverage: Population: entities by convention; encapsulation (setter shape) checked exhaustively within the set.
Other · Domain Modelling — Whether the domain layer stays free of infrastructure dependencies (EF/Marten/HTTP/ASP.NET) — the clean-architecture dependency rule.
Method: Roslyn (DDD-gated): domain-layer types scanned for infrastructure usage in member SIGNATURES and inside method/accessor BODIES — resolved calls and object-creations into EF/Marten/HTTP/Mongo/Redis/message-bus types (not just a namespace allowlist). Deterministic, symbol-resolved, exhaustive over domain-layer bodies, DDD-native.
Coverage: Domain layer identified by NAMESPACE heuristic; infrastructure then resolved by symbol in member SIGNATURES and method/accessor BODIES — rename the layer and the check evaporates.
Other · Domain Modelling — Whether clusters of primitives that travel together (a missing value object) are extracted — a low-weight suggestion, LLM-confirmed when configured.
Method: Roslyn (DDD-gated): primitive parameter clusters recurring three or more times across signatures extracted, then confirmed by language model when configured. Advisory, low-weight.
Do you agree with this assessment?
ED5 · Idempotency3.0 / 10Poor◐ Sampled · advisory
Other · Readiness — Whether retry-prone mutations (command handlers + message/event consumers) are idempotent so an at-least-once redelivery or client retry doesn't double-apply the effect — heuristic at-risk detection confirmed by language model, advisory.
Method: Roslyn heuristic (any mutation, ungated): command handlers and message/event consumers that mutate persistent state without a visible idempotency guard (exists/dedup check, upsert, idempotency-key/inbox, conditional/versioned write, fixed-value set) flagged as at-risk; each at-risk candidate then confirmed or cleared by a language model as genuinely non-idempotent versus naturally-idempotent. Advisory without a model (heuristic-only, degraded), per-candidate judged with one.
Coverage: Population: retry-prone mutations — command handlers (CQRS write side) + message/event consumers (IConsumer/I*EventHandler) — that mutate persistent state; runs on any repo with mutations, not only event-driven ones. The at-risk subset (no obvious guard) is a HEURISTIC candidate set, each then LLM-JUDGED non-idempotent vs safe; a handler outside those conventions, or a guard the LLM can't confirm, is bounded by the sample. Degrades to heuristic-only when no model is configured.
`Handlers.CartUpdater.HandleAsync` mutates persistent state (a repository write) with no visible idempotency guard. Under a client retry or at-least-once redelivery a re-run could double-apply it — confirm it's safe to re-run, or add an exists/dedup check, an upsert, an idempotency-key/inbox, or a versioned write. (Configure an LLM to auto-classify this.) (×2) — CartUpdater.cs:32, CartUpdater.cs:45
What to do
Make retry-prone mutations idempotent — guard each write with an exists/dedup check, an upsert, an idempotency-key/inbox, or a versioned write, so a re-run doesn't double-apply.
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.
No README at the repository root — newcomers have no entry point.
What to do
Add a root README: what the system is, how to build/run it, and a map of the projects.
Add a README to the 9 of 9 project(s) that lack one — worth up to 2 pts.
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.
There is no README, so nothing documents what the system is or how it works.
What to do
Add a README describing the system, how to build/run it, and keep it current.
Readiness · Readiness — Whether releases are automated and safely reversible (probes, rolling updates, approval gates) — from manifests/pipeline files, not the live environment.
Method: Filesystem scan: deployment manifests/IaC (K8s YAML, Helm, Terraform) for rolling updates, probes, approval gates, migration hooks. Exhaustive, deterministic.
Deployment automation exists but no readiness/liveness probes, rolling-update strategy, lifecycle hooks or migration job were evidenced — a bad release is harder to detect and reverse.
What to do
Add readiness/liveness probes and a rolling-update (or blue/green) strategy so a bad release is caught and rolled back automatically.
Add an approval/environment gate (required reviewers / protection rules) before production promotion.
Do you agree with this assessment?
P5 · DR & Backup0.0 / 10Critical✓ Tool-verified
Readiness · Readiness — Whether disaster recovery is planned and codified — backups, geo-recovery, RTO/RPO, persistence guarantees — from IaC + container manifests + docs, never the live cloud.
Method: Filesystem scan: disaster recovery, backup, geo-recovery, RTO/RPO, persistence guarantees from IaC, manifests, and docs. Exhaustive, deterministic, never a live environment.
A persistence guard (data volume / purge-protection) was found, but no backup, geo-recovery or RTO/RPO controls were evidenced — a volume that survives a container recreate is not a tested restore from catastrophic loss.
What to do
Codify backups + geo-recovery in IaC and document RTO/RPO and the restore procedure — a persistence guard alone is not disaster recovery.
Other · Security — Transport security, security headers, secure cookies, input validation, middleware order and crypto hygiene (presence, not runtime).
No Content-Security-Policy / X-Frame-Options / X-Content-Type-Options configuration found — defense in depth, even when a reverse proxy could set them. (−2.0 on this card.)
No UseHttpsRedirection/UseHsts and no reverse-proxy signal — transport security is unverified at the app layer. (−2.0 on this card.)
No ModelState/[ApiController]/FluentValidation signal — inbound payloads reach handlers unvalidated. (−2.0 on this card.)
No CookieSecurePolicy/HttpOnly/SameSite configuration found. (−1.5 on this card; skip if the app sets no cookies.)
What to do
Add security response headers (Content-Security-Policy, X-Frame-Options, X-Content-Type-Options) — defense in depth, even when a reverse proxy could set them.
Enforce HTTPS at the app layer (UseHttpsRedirection / UseHsts) — only skip this if a reverse proxy demonstrably terminates TLS.
Validate inbound models (ModelState/[ApiController]/FluentValidation) to reduce injection and bad-data risk.
Set secure cookie flags — CookieSecurePolicy.Always, HttpOnly, and SameSite (Strict/Lax) on auth/session cookies. Skip only if the app sets no cookies.
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.
Blocking on a Task with `.Wait()`/`.GetAwaiter().GetResult()` can deadlock (and wastes a thread). Make the caller `async` and `await` instead. — Startup.cs:88
Other · Code Health — Whether async methods accept a CancellationToken so work can be cancelled (adoption curve).
Method: Roslyn scan: every async method (excluding framework-fixed overrides/Blazor handlers) checked for CancellationToken parameter presence. Deterministic, adoption percentage.
Only 0/23 async methods accept a CancellationToken, so requests can't be cancelled cleanly under load or on client disconnect. In Blazor Server circuits and other short-write hosts, omitting it can be an accepted convention — judge against your hosting model.
No CancellationToken parameter — work can't be cancelled cleanly on disconnect/shutdown. (×23) — CartsController.cs:29, CartsController.cs:38, CartsController.cs:45, …
What to do
Thread a CancellationToken through async methods so work stops promptly on cancellation.
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.
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?
WCAG coverage — what static analysis assessed
Statically assessed 8 of 55 WCAG 2.2 Level A/AA success criteria — partial signal only (a clean result is necessary, not sufficient; static analysis fully verifies none). This is accessibility readiness, not a conformance claim — a WCAG conformance claim requires manual evaluation (WCAG-EM 1.0).
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 — 47 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 image/media element found in the parsed markup — AC1 not applicable here.
AC4 Keyboard semantics — No interactive element found in the parsed markup — AC4 not applicable here.
AC6 Visual & motion safety — No styled element found in the parsed markup — AC6 not applicable here.
AX7 Slice cohesion — not applicable — not a vertical-slice architecture
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 — This is a dotnet-new template — authorization is deferred to the application you build from it. Add [Authorize]/policies (or imperative guards) when you wire up real users; until then there are no real endpoints to protect.
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.
D11 Test Reliability — Test reliability not included
D16 Bus Factor — early-stage repository — too few commits for a meaningful bus factor
D19 Documentation Quality — LLM evaluation failed
D20 ADR Quality — N/A — this repo declares itself a template / kata / sample / demo; a formal ADR log is deferred to a real application built from it.
D27 Navigability — Navigability unmeasured — symbol resolution incomplete
D30 Dependency Vulnerabilities — Not applicable
D32 Data Compliance (PII/GDPR) — Not applicable
D33 JS/npm Dependency Vulnerabilities — Not applicable
D34 Knowledge Freshness — early-stage repository — too little history to judge knowledge freshness
D36 Supply-chain Provenance & Signing — Not applicable
D37 Vulnerability-disclosure Policy — Not applicable
D38 OSV Dependency Vulnerabilities — Not applicable
D7 Architectural Integrity — No checkable ADRs to assess
D8 Code Coverage — Coverage not measured
DM3 Integration-event coupling — no integration events detected — coupling check not applicable
DM7 Repository granularity — no repository abstraction detected (e.g. uses a document session)
ED1 Event-Driven — not run — only 2/3 markers (1 event handler(s); 1 CQRS handler(s))
ES1 Event Sourcing — not run — only 2/3 markers (an event-store package (Marten/EventStore); 1 aggregate(s) with Apply/When folds)
M2 Architecture documentation — This repo declares itself a template / kata / sample / demo — formal architecture documentation (ADRs, C4 diagrams) is deferred to a real application built from it, so its absence is not a defect here.
P1 CI/CD gates — This repo declares itself a template / kata / sample / demo — code meant to be read or copied, not operated. Automated CI/CD gates are deferred to the application you build from it, so their absence is not a defect here. The dimension reactivates once the repo becomes a real app.
P12 CI test-gate honesty — no CI workflow found
P2 Observability — This repo declares itself a template / kata / sample / demo — code meant to be read or copied, not operated. Structured logging, tracing/metrics and health checks are deferred to the application you build from it, so their absence is not a defect here. The dimension reactivates once the repo becomes a real app.
P3 Security & performance tooling — This repo declares itself a template / kata / sample / demo — code meant to be read or copied, not operated. SAST, secret/dependency scanning and performance benchmarks are deferred to the application you build from it, so their absence is not a defect here. The dimension reactivates once the repo becomes a real app.
P6 Release Hygiene — not evidenced — no changelog, version stamp or semver release tag in the repo
P7 Outbound HTTP resilience — no outbound HTTP usage detected
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.
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.
No assertions: TestPerformance EventSourcingCQRS.Domain.EventStore.Tests/EventStoreTest.cs:41— Test method has no assertions — it may not test anything.
Low cohesion: TransientDomainEventPubSub (LCOM4 4) EventSourcingCQRS.Application/PubSub/TransientDomainEventPubSub.cs:9— TransientDomainEventPubSub'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.
Coverage not measured — The test suite couldn't be built/run in-image and no coverage report is committed, so line coverage was not measured — and it is EXCLUDED from the score rather than scored on a LoC-ratio proxy. Commit the Cobertura/OpenCover/lcov report your CI already produces (anywhere in the repo), or make the suite runnable in-image, and real coverage will be measured.
Recommendation — 13 finding(s)
D11 · Test Reliability· Test reliability not included · ×1
Test reliability not included — Test reliability not included — no test tier completed within its budget.
early-stage repository — too few commits for a meaningful bus factor — early-stage repository — too few commits for a meaningful bus factor (3 author(s) across 3 commit(s) sampled).
Navigability unmeasured — symbol resolution incomplete — 60 % of sampled invocations could not be resolved to a symbol (the workspace likely loaded without all references) — the indirection fractions would be computed over an unrepresentative slice, so navigability is reported as not measured rather than a misleading score.
D30 · Dependency Vulnerabilities· Not applicable · ×1
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
Low IaC: DS-0026 EventSourcingCQRS/Dockerfile— No HEALTHCHECK defined
D32 · Data Compliance (PII/GDPR)· Not applicable · ×1
Not applicable — No PII/GDPR-handling patterns detected (p/gdpr ruleset) — no data-compliance surface to assess.
D33 · JS/npm Dependency Vulnerabilities· Not applicable · ×1
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.
early-stage repository — too little history to judge knowledge freshness — early-stage repository — too little history to judge knowledge freshness (3 commit(s) sampled).
D36 · Supply-chain Provenance & Signing· Not applicable · ×1
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.
D37 · Vulnerability-disclosure Policy· Not applicable · ×1
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.
D38 · OSV Dependency Vulnerabilities· Not applicable · ×1
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.
D7 · Architectural Integrity· No checkable ADRs to assess · ×1
No checkable ADRs to assess — No architecture decision records were found and the project graph is acyclic, so architectural integrity could not be assessed. Add ADRs (with `enforcement: analyzer|test`) to make the architecture's rules checkable.
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 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 019edc41-74f9-717e-a609-619776e1f1d3 · every finding is also locatable in findings.md, and the complete scoring record (with exit codes + durations) in sidecar.json.
Issues: 3 · Warnings: 7 · Recommendations: 13 · Info: 18 — Appendix A · all findings · full markdown report.
Generated by Watchdog — deterministic code-health analysis. 18-06-2026 @ 19:42 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.