Public report — lynx, published 21 Jun 2026.
Concrete security findings (CVE IDs, secret matches, dependency versions) are hidden in this version;
ask the repo owner for the full report.
17findings with an exact file:lineof 45 — the remainder are repo-wide signals (a dimension-level measurement, not a single line); open any file:line and verify
63/101dimensions across the health lenses1055 LoC · 8 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.
ahmed-ramsey-shahin/lynx carries serious risk (45%). Several issues below can materially affect reliability, security, or the cost of change and warrant near-term attention.
It is strongest in Code Health (92%) — the code is clean and low-risk to change. Performance (81%) is solid too.
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 (35%) is the next concern — operating, monitoring and recovering the system safely is harder.
Leadership focus, highest impact first: 1 No ADRs found finding(s) in ADR Quality (ADR Quality); Expand the README with getting-started (Documentation (README)); Start an ADR log (docs/adr/) recording significant decisions… (Architecture documentation).
For scale: Hobby (~1,055 production lines); rebuilding it from scratch would take roughly ~0.1 person-years (~1 engineer). Approximate, ±~30%.
It builds on a genuinely strong Code Health foundation (92%); the priorities above are the highest-leverage way to bring the rest up to that level.
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.
This codebase represents roughly ~0.1 person-years of build effort (about ~€9,700 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 Very high (×1.9) — service/app, DDD/clean architecture, CQRS, domain model, event-driven integration × 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 ADRs found finding(s) in ADR Quality.
Of everything flagged, the best return on effort is: Resolve the 1 No ADRs found finding(s) in ADR Quality. The rest can wait behind it.
Evidence: priority ranking: top of 5 ranked by impact/effort
→ Resolve the 1 No ADRs found finding(s) in ADR Quality.
Architecture — bounded-context dependency graph
Each box is a bounded context (its layer projects grouped, or a project count when large); arrows show dependencies between contexts. A shared kernel is where many arrows converge.
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
6
High / Critical
A06:2021 — Vulnerable & Outdated Components
1
Medium
Roadmap
Top priorities: Resolve the 1 No ADRs found finding(s) in ADR Quality; Expand the README with getting-started, architecture overview and a project map; Start an ADR log (docs/adr/) recording significant decisions and their rationale.
Ranked by impact ÷ effort. "Helps" is the estimated gain on the 0–100 health score.
Do this
Helps
Effort
Dimension
Resolve the 1 No ADRs found finding(s) in ADR Quality.
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.
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. 63 of 63 evaluated dimensions are computed purely by tools and static analysis (confidence 1.0); none rely on LLM judgement. Overall confidence is 0.7 — 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 — 63 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, 17 of 45 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.
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.
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.
D10 Test Quality: Assertion density is structural — it cannot tell a meaningful behavioural assertion from a trivial one, only that an assertion is present.
D11 Test Reliability: Flakiness is inferred from history/markers — Watchdog runs the suite once (for coverage), not the repeated runs under varied conditions that reveal nondeterminism, so a flaky test never recorded as failing is invisible here.
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.
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.
D26 Project Cohesion: Project focus is sized from members/namespaces per project — a project that is broad by deliberate design reads the same as one that has sprawled.
D28 Secrets (history): Secret-history scanning sweeps the git log for known patterns — a secret that predates the available history, or never matched a signature, is not found (clean means "nothing matched in the history we can see").
D29 Static Analysis (SAST): SAST findings are pattern-based (semgrep) — it finds classes of bug it has rules for; logic flaws, auth/authorization gaps and issues needing runtime context are out of reach (and clean means "no rule matched").
D30 Dependency Vulnerabilities: CVE matching depends on accurate package/version metadata and the advisory database — a vulnerability with no published advisory, or in code not declared as a dependency, is not seen.
D31 IaC & Container Security: IaC scanning checks Dockerfiles/Terraform/Kubernetes against best-practice rules — it cannot see the live cloud account, runtime configuration, or drift between the committed config and what is actually deployed.
D34 Knowledge Freshness: Freshness is decayed commit RECENCY, not comprehension — code read often but rarely committed reads as orphaned, and stable code that genuinely needs no changes is penalised the same as forgotten code; bot/squash commits distort it like the bus factor.
D35 Change Coupling: Change coupling is co-change in COMMITS — files split across separate commits, or coupled only through a shared config/build step, read as uncoupled, and a sweeping commit (rename/format) is excluded so it doesn't couple everything. It shows that files change together, not WHY: a high coupling can be a healthy cohesive pair as readily as a hidden leak.
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.
AX9 CQS / query purity: Handlers are found by interface/name convention — a query handler using neither is not seen. Mutation is a resolved write/publish invocation (SaveChanges/repository/bus), so a write hidden behind a hand-rolled wrapper, reflection, or a string-keyed service locator resolves to a non-persistence type and isn't flagged; it detects that a query writes state, not whether the write is a legitimate read-side cache update. Clean means "no resolved write/publish in a query body", not a proof of CQS purity.
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.
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 (2): D20, ED5. 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.
Detailed fixes: d2_recommendation.md · top locations in Appendix A, every location in findings.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.
Detailed fixes: d4_recommendation.md · top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D5 · Coupling10.0 / 10Exemplary✓ 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.
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.
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.
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.
7 test methods: 7 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 Quality10.0 / 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.
0 skipped, 0 zero-assertion, no mocking-framework packages referenced (hand-written doubles or no mocking) across 138 tests.
✓ On the Gold path — maintain.
Detailed fixes: d10_recommendation.md.
Do you agree with this assessment?
D11 · Test Reliability10.0 / 10Exemplary✓ Tool-verified
What it measures: Whether the tests pass reliably, with no flakiness.
Method: Suite re-run N times within tiered wall-clock budgets (unit to e2e); tests failing non-deterministically across runs flagged; guarded tests retried when #if guards detected.
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.
Resolve the 1 Banned license finding(s) in License Compliance. — One of this dimension's main actionable groups (1 issue-level).
Enforce License Compliance in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Verified — provenance only; does not change the score.
Detailed fixes: d14_recommendation.md · top locations in Appendix A, every location in findings.md.
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.
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 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 any dependencies have known published vulnerabilities (CVEs), direct or transitive.
Method: NuGet CVE scan via dotnet list package --vulnerable including transitive; severity tally (Critical/High/Medium/Low) to 0-10 tight normalizer. Exhaustive, deterministic; degrades when absent.
High IaC: DS-0002 · ×4Lynx.IdentityService/Dockerfiledetected by trivy finding
Low IaC: DS-0026 · ×2Lynx.IdentityService/Dockerfiledetected by trivy finding
What to do
Resolve the 4 High IaC finding(s) in IaC & Container Security — start with Dockerfile (4). — One of this dimension's main actionable groups (4 issue-level).
Resolve the 2 Low IaC finding(s) in IaC & Container Security — start with Dockerfile (2). — One of this dimension's main actionable groups (2 recommendation-level).
Detailed fixes: d31_recommendation.md · top locations in Appendix A, every location in findings.md.
What it measures: Whether anyone still has living knowledge of each file, or it has been orphaned — last understood long ago by someone now gone quiet. The sibling of the bus factor: D16 asks who owns it, D34 asks whether anyone still knows it.
Method: File orphaning as total living-knowledge decay below one focused-commit's worth within a year, computed per-file from the D16 decay model. Exhaustive, deterministic over fixed history.
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.
What it measures: Whether the build pipeline provides supply-chain integrity — generated provenance/attestation, signed artifacts (cosign/sigstore), an SBOM, and pinned build actions. Presence of the configuration, not a runtime guarantee.
Method: Supply-chain provenance/signing read deterministically from CI/build config (.github/workflows, .gitlab-ci.yml, azure-pipelines, Jenkinsfile, .circleci) + the release surface: four signals — generated provenance/attestation (SLSA/in-toto/actions-attest), artifact signing (cosign/sigstore/gitsign), an SBOM (syft/sbom-action/*.spdx.json/*.cdx.json), and SHA-pinned build actions — scored 10·present/denom. NotApplicable without a build pipeline. Detects configuration presence, not runtime enforcement.
Resolve the 1 Unpinned build actions finding(s) in Supply-chain Provenance & Signing. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 No build provenance finding(s) in Supply-chain Provenance & Signing. — One of this dimension's main actionable groups (1 recommendation-level).
Resolve the 1 No artifact signing finding(s) in Supply-chain Provenance & Signing. — One of this dimension's main actionable groups (1 recommendation-level).
Detailed fixes: d36_recommendation.md · top locations in Appendix A, every location in findings.md.
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 · Architecture — Whether read (query) handlers stay side-effect-free — a query that writes persistent state or raises events breaks CQS and makes reads unsafe to retry, cache, or route to a read replica.
Method: Roslyn scan: CQRS handlers classified query-vs-command by interface (IQueryHandler/ICommandHandler/IRequestHandler<TQuery,TResult>) and name convention (*Query/Get*/Find* vs *Command); each query handler's body checked for persistent-state writes (SaveChanges/repository Add-Update) or event publishes by resolved invocation. Deterministic, type-level, exhaustive over the detected handlers.
Coverage: Population: CQRS handlers identified by IQueryHandler/ICommandHandler/IRequestHandler interface + *Query/Get*/Find*/*Command NAME convention; query purity then checked exhaustively within that set — a query handler using neither convention is invisible, and mutation is a resolved persistence/publish CALL, not full dataflow.
`GetUrlByAlias.GetUrlByAliasQueryHandler` is a read (query) handler but its body raises events — a query must stay side-effect-free so reads are safe to retry, cache, and route to a read replica. — GetUrlByAliasQueryHandler.cs:12
What to do
Keep query handlers read-only — move the writes/event-publishes into a command handler so reads stay safe to retry, cache, and route to a read replica.
Other · Security — Whether access is authorized by default — [Authorize]/policies or imperative guard methods (throw-on-violation) called from handlers.
Method: Roslyn scan: [Authorize] usage and authorization policies, plus imperative throw-on-violation guard methods detected via syntax. Deterministic.
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.
`UrlVisitedEvent.UrlId` is a raw `Guid` — give it a strongly-typed id (`readonly record struct UrlId { Guid Value }`). — Events.cs:5
What to do
Adopt strongly-typed ids across the domain — finish the migration or document the boundary; primitive ids invite transposed-argument bugs.
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.
Other · Event-Driven — Whether event handlers stay asynchronous (no blocking remote HTTP/gRPC calls awaited inside a handler).
Method: Roslyn semantic scan (event-driven gated): event-handler bodies scanned for HTTP/gRPC invocations by resolved symbol type, not substring. Deterministic, semantic-resolved.
Other · Event-Driven — Whether state changes and message publishes are atomic (a transactional outbox) rather than a crash-unsafe dual write.
Method: Roslyn semantic scan (event-driven gated): event-handler methods scanned for DB-save plus bus-publish without a transactional outbox reference. Deterministic, semantic-resolved.
`CreateUrlCommandHandler` writes to the database while `GetUrlByAliasQueryHandler` publishes to the message bus in the same command-handling flow, with no outbox referenced on either path. Splitting the persist and the publish across sibling methods (or two collaborating actors) doesn't make them atomic — a crash between the two either loses the message or emits a phantom event. Use the transactional outbox pattern so the message is committed in the same transaction as the state change and dispatched afterwards. — CreateUrlCommandHandler.cs:11
What to do
Adopt the transactional outbox pattern so DB writes and message publishes commit atomically — no lost or phantom events on a crash.
Do you agree with this assessment?
ED5 · Idempotency3.0 / 10Weak◐ 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.
`CreateUrl.CreateUrlCommandHandler.Handle` 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.) — CreateUrlCommandHandler.cs:18
`BackgroundServices.RabbitMqPublisherBackgroundService.ExecuteAsync` mutates persistent state (an event publish) 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.) — RabbitMqPublisherBackgroundService.cs:15
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.
The root README is 18 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 8 of 8 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.
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.
Do you agree with this assessment?
P1 · CI/CD gates8.5 / 10Strong✓ 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.
A CI pipeline exists and the word "test" appears, but no explicit test-runner invocation (dotnet test / npm test / pytest / a test job) was matched — the gate may be running tests, or "test" may be incidental (a path, "latest", a reporter). Make the test step explicit so the gate is unambiguous.
What to do
Run the test suite in CI via an explicit runner step (e.g. `dotnet test`) and gate merges on it.
Do you agree with this assessment?
P2 · Observability5.5 / 10Adequate✓ 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.
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.
Do you agree with this assessment?
P9 · Domain vs controller coverage5.7 / 10Adequate✓ Tool-verified
Readiness · Readiness — Whether test coverage concentrates on the domain (business rules) rather than the trivial web/controller layer — a focus check a generic tool can't make.
Method: Roslyn plus test-execution analysis: domain-layer versus trivial web/controller coverage ratio. Computed metric, deterministic.
What to do
Raise domain coverage toward 100% — cover the remaining aggregates / value objects / domain services where the business invariants and costly bugs live.
Readiness · Performance — Whether the library protects its performance with benchmarks — a BenchmarkDotNet suite, an allocation MemoryDiagnoser, and (ideally) a CI gate. Presence is credited as a bonus, never a deduction.
Method: Repo + source scan: BenchmarkDotNet referenced (csproj/source), [Benchmark]/[MemoryDiagnoser] attribute counts, and a benchmark step in CI — scored as a bonus ladder (absence is neutral, never a deduction). Deterministic, presence detection.
No BenchmarkDotNet suite was found. For a performance-sensitive library, a benchmark guards against silent regressions — but it's a bonus here, not a deduction.
What to do
Add a BenchmarkDotNet project for the hot paths (with [MemoryDiagnoser] to track allocations), and run it in CI to catch regressions.
Readiness · Performance — Whether the code is written to minimise allocations so it doesn't pressure its host's GC — Span/Memory, pooling (ArrayPool/ObjectPool), stackalloc, ValueTask, value-type structs and buffer writers. Reward-only: credited where present, never penalised where a simpler style is fine.
Raise allocation-aware density on the hot paths — currently 8 use(s) across 1,165 production line(s) (~6.9/1k). More Span/Memory, pooling (ArrayPool/ObjectPool), stackalloc and ValueTask on the allocation-heavy paths climbs this toward 10.
Readiness · Performance — Whether asynchronous code keeps its host responsive — a library awaits with ConfigureAwait(false) (so it never captures and stalls the host's context) and avoids sync-over-async blocking (.Wait()/.GetAwaiter().GetResult()) that wastes threads and risks deadlock.
Method: Production-source scan: sync-over-async blocking (.Wait()/.GetAwaiter().GetResult()) counted everywhere, and — for a library with ≥5 awaits — the share of awaits using ConfigureAwait(false). Deterministic, syntax/text detection.
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 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.
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.
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 14/18 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. (×4) — RabbitMqChannelPool.cs:43, RabbitMqChannelPool.cs:62, RabbitMqConnectionManager.cs:25, …
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.
Other · Code Health — Whether nullable reference types are enabled and not undermined by heavy `!` suppression.
Method: Roslyn compiler-options scan: NullableContextOptions per project; null-forgiving (!) suppression density per 1k syntax nodes. Deterministic, adoption plus suppression penalty.
~2.2 `!` suppressions per 1k syntax nodes — each one tells the compiler to trust you about null, suppressing the very safety NRTs provide.
What to do
Enable <Nullable>enable</Nullable> across all projects and resolve warnings rather than suppressing with `!`.
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 — 39 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.
AX7 Slice cohesion — vertical-slice architecture detected, but individual slices could not be resolved from namespaces or project layout
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.
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.
D16 Bus Factor — single-maintainer — knowledge-concentration (bus factor) risk
D19 Documentation Quality — LLM dimension skipped
D21 Naming Consistency — LLM dimension skipped
D22 Internal API Consistency — LLM dimension skipped
D23 Boundary Type-Coupling — small single-context codebase (1,055 production LoC) — bounded contexts are not needed at this size
D24 Comment Value — LLM dimension skipped
D25 ADR Conformance — no ADRs to check
D27 Navigability — Navigability unmeasured — symbol resolution incomplete
D32 Data Compliance (PII/GDPR) — Not applicable
D33 JS/npm Dependency Vulnerabilities — Not applicable
D37 Vulnerability-disclosure Policy — Not applicable
D38 OSV Dependency Vulnerabilities — Not applicable
D39 IL Efficiency — IL metrics not applicable
D7 Architectural Integrity — No checkable ADRs to assess
DM1 Aggregate boundaries — no aggregates detected — aggregate-boundary check not applicable
DM3 Integration-event coupling — no integration events detected — coupling check not applicable
DM4 Rich vs anemic model — no entities detected — rich-vs-anemic model not assessable
DM7 Repository granularity — no repository abstraction detected (e.g. uses a document session)
ED2 Event/command shape — no command-shaped messages detected — single-handler-per-command check not applicable
ES1 Event Sourcing — not run — 0/3 markers found
M4 Documentation accuracy — LLM not available — accuracy is the Tier-2 layer and needs a reachable model.
P12 CI test-gate honesty — no data
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
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.
Monorepo: only 1 of 2 solutions was scored — This repository contains 2 .NET solutions, but a scan analyzes ONE. Every score, lens, and finding here reflects only `Lynx.IdentityService/Lynx.IdentityService.slnx` — the other 1 (`Lynx.RedirectionService/Lynx.RedirectionService.slnx`) 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.
D18 · Solution Shape· Analyzed solution does not cover the bulk of the repository · ×1
Analyzed solution does not cover the bulk of the repository — The scored solution `Lynx.IdentityService/Lynx.IdentityService.slnx` is not representative of this repository — it references only 0 of 239 discovered C# files (0 %). Lenses that need the product's source (domain modelling, event-driven, event sourcing) abstain because the aggregates, EF configs, and domain events under the product tree were not loaded. Point the scan at the product solution (or scan its directory directly) so the whole codebase is analyzed, not a build-tooling sub-solution.
Medium CVE: SharpCompress 0.30.1 — SharpCompress 0.30.1 (transitive) has a Medium advisory; affects 3 projects — one upgrade fixes all. https://github.com/advisories/[GHSA redacted]
LLM dimension skipped — This dimension requires a reachable LLM provider; configure/start one to evaluate it.
D22 · Internal API Consistency· LLM dimension skipped · ×1
LLM dimension skipped — This dimension requires a reachable LLM provider; configure/start one to evaluate it.
D23 · Boundary Type-Coupling· small single-context codebase (1,055 production LoC) · ×1
small single-context codebase (1,055 production LoC) — bounded contexts are not needed at this size — small single-context codebase (1,055 production LoC) — bounded contexts are not needed at this size Declare architecture.contexts (≥2) in config to assess cross-boundary type coupling.
Navigability unmeasured — symbol resolution incomplete — 68 % 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.
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.
No artifact signing — No artifact signing found in CI (e.g. cosign / sigstore / gitsign).
D36 · Supply-chain Provenance & Signing· No SBOM · ×1
No SBOM — No SBOM generation or committed SBOM found (e.g. syft / anchore/sbom-action / *.spdx.json / *.cdx.json).
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.
D39 · IL Efficiency· IL metrics not applicable · ×1
IL metrics not applicable — The target did not build, so no IL was available to measure.
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.
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.
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 019eebea-e32d-7902-880d-970764f20b11 · every finding is also locatable in findings.md, and the complete scoring record (with exit codes + durations) in sidecar.json.
Issues: 5 · Warnings: 8 · Recommendations: 19 · Info: 13 — Appendix A · all findings · full markdown report.
Generated by Watchdog — deterministic code-health analysis. 21-06-2026 @ 20:41 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.