Public report — K8s.Eventing, published 29 Jun 2026.
Concrete security findings (CVE IDs, secret matches, dependency versions) are hidden in this version;
ask the repo owner for the full report.
90findings with an exact file:lineof 141 — the remainder are repo-wide signals (a dimension-level measurement, not a single line); open any file:line and verify
59/97dimensions across the health lenses7229 LoC · 16 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.
neuroglia-io/K8s.Eventing carries serious risk (32%). Several issues below can materially affect reliability, security, or the cost of change and warrant near-term attention.
Most urgent: a critical security exposure was detected (see the Security & Compliance lens). Treat it as a priority regardless of the overall grade.
The area that most needs attention is Readiness (18%) — operating, monitoring and recovering the system safely is harder. Security (31%) is the next concern — exposure to security and compliance incidents is elevated.
Leadership focus, highest impact first: 1 No tests found finding(s) in Test Distribution (Test Distribution); CI workflow that builds and runs the test suite on every push/PR (CI/CD gates); Make types internal by default (Library API & versioning).
For scale: Small (~7,229 production lines); rebuilding it from scratch would take roughly ~0.1 person-years (~1 engineer). Approximate, ±~30%.
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 ~€9,100 to rebuild). Its weakest lens is Readiness at 18% — the part of that asset most exposed by the findings below.
How we model this: boilerplate at a scaffolding rate + logic × domain High (×1.5) — service/app, CQRS, 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 tests found finding(s) in Test Distribution.
Value concentrated against a weak lens · High · Value at risk
This is a Small asset (~0.1 person-years to rebuild), and its weakest lens is Readiness at 18%. The operational and business risk on an asset this size concentrates there — that's where remediation buys the most protection.
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.
At a glance — Code Health · 51% · Adequate · gated by X5
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
50
High / Critical
A06:2021 — Vulnerable & Outdated Components
10
High / Critical
Roadmap
Begin by addressing the single missing test case in the test distribution to ensure comprehensive coverage. Next, implement a CI workflow to automatically build and run tests on every push or pull request, establishing a reliable safety net. To improve long-term maintainability, restrict type visibility to internal by default and expose only the necessary public API. Additionally, configure standard resilience handlers for HTTP clients to prevent external failures from impacting the application. Finally, resolve the nine deprecated dependencies to maintain a clean and secure codebase.
Ranked by impact ÷ effort. "Helps" is the estimated gain on the 0–100 health score.
Do this
Helps
Effort
Dimension
Resolve the 1 No tests found finding(s) in Test Distribution.
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. 55 of 59 evaluated dimensions are computed purely by tools and static analysis (confidence 1.0); 4 documentation/naming judgement(s) are LLM-assisted and labelled advisory. Overall confidence is 0.7 — 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 — 59 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, 90 of 141 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.
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.
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.
D16 Bus Factor: Bus-factor is a time-decayed model of commit attribution (who has recently, repeatedly worked a file), not comprehension — pairing, review and reading-without-committing spread knowledge it can't see; bot commits and shared accounts still distort it.
D17 Explicit Debt: Acknowledged-debt signals (TODO/FIXME, suppressions, dead code) are textual — undocumented debt that nobody marked, and debt that lives in design rather than annotations, is invisible. Committed machine-written code (EF migrations, designer files, snapshots) is excluded — it is never the team's dead code to delete.
D18 Solution Shape: Build integrity reflects whether the solution compiled in this environment — a build that needs a private feed, a specific SDK, or a generated file absent from the repo can read as broken when it is merely unreproducible here.
D19 Documentation Quality: Documentation quality is judged by an LLM over a bounded sample of docs — it reads what is written, not whether the docs match the running system, and it is advisory, not a measurement.
D20 ADR Quality: ADR quality is an LLM read of the decision records present — it cannot know about decisions made and never recorded, and its verdict is sampled and advisory.
D21 Naming Consistency: Naming quality is an LLM judgement over a bounded sample — it assesses clarity/consistency of the names it sees, not domain-correctness, and is advisory.
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.
D24 Comment Value: Comment value (WHY vs WHAT) is an LLM judgement over a bounded sample — it is advisory and cannot weigh a comment against the precise code change it was written to explain.
D26 Project Cohesion: Project focus is sized from members/namespaces per project — a project that is broad by deliberate design reads the same as one that has sprawled.
D27 Navigability: Indirection/navigability is structural — it measures hops to follow a call, not whether that indirection buys real flexibility or just ceremony.
D28 Secrets (history): Secret-history scanning sweeps the git log for known patterns — a secret that predates the available history, or never matched a signature, is not found (clean means "nothing matched in the history we can see").
D29 Static Analysis (SAST): SAST findings are pattern-based (semgrep) — it finds classes of bug it has rules for; logic flaws, auth/authorization gaps and issues needing runtime context are out of reach (and clean means "no rule matched").
D30 Dependency Vulnerabilities: CVE matching depends on accurate package/version metadata and 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.
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".
The LLM boundary
LLM-set scores this run (7): D19, D20, D21, D22, D24, ED5, M4 (model: Local LLM). For these, a model reads a bounded sample and sets the numeric score (documentation, ADR quality, naming, comment value, onboarding) — D25 sets the ADR-conformance fraction over sampled code, D22 judges API accuracy over a sample. These are sampled and advisory by design: they vary at the margins between runs and are never a deterministic measurement. Every other score in this report is tool-computed at confidence 1.0.
What it measures: How tangled the control flow is — methods with many branches are hard to test and change.
Method: Cyclomatic complexity per method (1 + decision points), computed exhaustively across production source; test projects separated by convention. Deterministic.
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.
Resolve the 2 HashFile.CreateIndex (cognitive 59) finding(s) in Cognitive Complexity — start with HashFile.cs (2). — One of this dimension's main actionable groups (2 warning-level).
Resolve the 1 ControllerBaseExtensions.Process (cognitive 20) finding(s) in Cognitive Complexity — start with ControllerBaseExtensions.cs. — One of this dimension's main actionable groups (1 warning-level).
Enforce Cognitive Complexity in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Prevented — provenance only; does not change the score.
Detailed fixes: d2_recommendation.md · top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D3 · God 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.
+ 5 more group(s) — more in Appendix A; the complete list is findings.md.
✓ On the Gold path — maintain.
Detailed fixes: d4_recommendation.md · top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D5 · Coupling8.5 / 10Strong✓ Tool-verified
What it measures: Whether volatile projects sit underneath others that depend on them (so their churn ripples upward), and whether project dependencies form cycles. A widely-depended-on but stable shared/kernel project is healthy, not penalised.
Method: Dependency cycles via elementary-DFS over real .csproj references, plus Martin instability (afferent/efferent) per project. Exhaustive over the reference graph, deterministic.
Coverage: Exhaustive · type-level: afferent/efferent coupling + cycles computed over every production type — the population is all types, not a name convention.
Off the main sequence: Neuroglia.K8s.Eventing · ×3
What to do
Resolve the 3 Layer violation finding(s) in Coupling. — One of this dimension's main actionable groups (3 issue-level).
Resolve the 3 Off the main sequence finding(s) in Coupling. — One of this dimension's main actionable groups (3 warning-level).
Enforce Coupling in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Prevented — provenance only; does not change the score.
Detailed fixes: d5_recommendation.md · top locations in Appendix A, every location in findings.md.
What it measures: Whether a class's methods are focused on a single responsibility.
Method: LCOM4 cohesion per production class with at least two methods: connected components of methods sharing state or calls, computed syntactically. Deterministic, not a proxy.
Coverage: Exhaustive · type-level: LCOM4 cohesion computed over every production class — the population is all types, not a name convention.
D9 · Test Distribution0.0 / 10Critical✓ Tool-verified
What it measures: Whether the test suite has a healthy mix of unit / integration / end-to-end tests.
Method: Test projects classified (Unit/Integration/BDD/E2E) from compiled metadata; test methods counted exhaustively across projects with placement-agnostic disk fallback. Deterministic.
What it measures: Whether dependencies are current, secure, and not bloated.
Method: Manifest scan via dotnet list package across all projects; worst-signal-per-package deduction (saturating for vulnerabilities, capped-linear for deprecation/outdated) per KLoC. Exhaustive, deterministic.
Resolve the 9 Deprecated finding(s) in Dependency Hygiene. — One of this dimension's main actionable groups (9 warning-level).
Resolve the 1 Vulnerable finding(s) in Dependency Hygiene. — One of this dimension's main actionable groups (1 issue-level).
Enforce Dependency Hygiene in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Verified — provenance only; does not change the score.
Detailed fixes: d12_recommendation.md · top locations in Appendix A, every location in findings.md.
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: Whether knowledge is concentrated in too few people (the "bus factor").
Method: Living knowledge per author via time-decayed commit attribution (6-month half-life, focus weighting) across largest source files. Deterministic, avoids blame's mechanical-refactor false positives.
No source file's living knowledge is concentrated in a single author.
✓ On the Gold path — maintain.
Detailed fixes: d16_recommendation.md.
Do you agree with this assessment?
D17 · Explicit Debt8.7 / 10Strong✓ Tool-verified
What it measures: Acknowledged debt left in the code — TODOs, dead code, suppressed warnings.
Method: Roslyn syntactic debt markers (suppressions/TODO/FIXME/HACK/empty-catch/commented-code/Obsolete) plus SymbolFinder dead-code analysis; weighted-debt-per-KLoC density deducted 2.0x per unit. Deterministic, exhaustive.
Resolve the 6 EmptyCatchBlock finding(s) in Explicit Debt — start with ResourceController.cs (5), EventChannel.cs. — One of this dimension's main actionable groups (6 issue-level).
Enforce Explicit Debt in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Prevented — provenance only; does not change the score.
Detailed fixes: d17_recommendation.md · top locations in Appendix A, every location in findings.md.
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 the project's documentation is clear, complete, and useful.
Method: Judged by language model at low temperature (0.0-0.1) on a deterministic doc sample (READMEs plus first 25 architecture docs), with two-pass stability filtering. Advisory, sampled.
The single README for Neuroglia.K8s.Eventing states the project is an open source .NET 5.0 cloud-event gateway for Kubernetes and Istio, with a Docker image-registry issue noted and a table of contents listing Motivation, Under the Hood, Usage (CRDs/Deploy/Install channel/NATS Streaming/channel/Create broker/Start using), Contributing, and Examples. The document is well structured and complete per its visible outline; however it contains no architecture or design documentation and only one README file, leaving the reader unable to determine how the gateway routes events through NATSS channels versus event-store backends without reading the linked GitHub files.
Improve Documentation Quality — currently 6.0/10. — The single README for Neuroglia.K8s.Eventing states the project is an open source .NET 5.0 cloud-event gateway for Kubernetes and Istio, with a Docker image-registry issue noted and a table of contents listing Motivation, Under the Hood, Usage (CRDs/Deploy/Install channel/NATS Streaming/channel/Create broker/Start using), Contributing, and Examples. The document is well structured and complete per its visible outline; however it contains no architecture or design documentation and only one README file, leaving the reader unable to determine how the gateway routes events through NATSS channels versus event-store backends without reading the linked GitHub files.
Detailed fixes: d19_recommendation.md · top locations in Appendix A, every location in findings.md.
What it measures: Whether architecture decisions are recorded well (context, decision, consequences).
Method: Per-ADR judgment by language model at low temperature with two-pass stability; confidence is share of ADRs evaluated; enforcement-field presence detected deterministically. Advisory.
What it measures: Whether names — types, methods, variables — are clear and consistent.
Method: Judged by language model at low temperature (0.0-0.1) on a deterministic random symbol sample (fixed size, not exhaustive), with disclosed confidence band. Advisory, sampled.
1 naming inconsistencies across 200 sampled symbols.
Typo in property name: 'IsSuccessfull' (double 'l') is used instead of the standard 'IsSuccess' or 'IsSuccessful'.
✓ On the Gold path — maintain.
Detailed fixes: d21_recommendation.md · top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D22 · Internal API Consistency / 10Weak◐ 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.
Redundant naming for the same operation: 'Pub' vs 'Publish'. Both methods accept a CloudEvent and return IActionResult, indicating they perform the same publish action but with different HTTP route names.
Inconsistent naming for subscription operations: 'Sub'/'Unsub' vs 'Subscribe'/'Unsubscribe'. The first controller uses abbreviated names while others use full descriptive names.
What to do
Resolve the 1 Redundant naming for the same operation finding(s) in Internal API Consistency. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 Inconsistent naming for subscription operations finding(s) in Internal API Consistency. — One of this dimension's main actionable groups (1 warning-level).
Detailed fixes: d22_recommendation.md · top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D24 · Comment Value / 10Weak◐ Sampled · advisory
What it measures: Whether comments are worth it — explaining WHY (valuable) rather than WHAT (redundant).
Method: Judged by language model at low temperature (0.0-0.1) on deterministically sampled inline comments with surrounding code; findings verified back to sampled comments by substring match. Advisory, sampled.
Resolve the 1 misleading comment finding(s) in Comment Value — start with HashFile.cs. — One of this dimension's main actionable groups (1 recommendation-level).
Detailed fixes: d24_recommendation.md · top locations in Appendix A, every location in findings.md.
What it measures: How far you must trace to follow a call — low indirection and co-located slices read easier.
Method: Call indirection (interface hops, cross-namespace calls, slice-locality scaled) over a sampled set of method invocations, size-aware baseline. Sampled; confidence discounted by symbol-resolution gaps.
Coverage: Slice locality from the first namespace segments, SAMPLED (≤400 methods) — not exhaustive.
87 % of calls cross a namespace and 10 % go through an interface, but 97 % of collaborators are co-located — so a call's collaborators sit together and tracing stays easy. Baseline: small — navigation cost is tolerated.
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: KSV-0014 · ×13deployment/kubernetes/eventing-core.yamldetected by trivy finding
Medium IaC: KSV-0001 · ×14deployment/kubernetes/eventing-core.yamldetected by trivy finding
Low IaC: KSV-0003 · ×23deployment/kubernetes/eventing-core.yamldetected by trivy finding
What to do
Resolve the 23 Low IaC finding(s) in IaC & Container Security — start with eventing-core.yaml (10), eventstore.yaml (10), eventing-test.yaml (2). — One of this dimension's main actionable groups (23 recommendation-level).
Resolve the 13 High IaC finding(s) in IaC & Container Security — start with Dockerfile (4), eventing-core.yaml (3), eventing-test.yaml (3). — One of this dimension's main actionable groups (13 issue-level).
Resolve the 14 Medium IaC finding(s) in IaC & Container Security — start with eventing-core.yaml (5), eventing-test.yaml (5), eventstore.yaml (4). — One of this dimension's main actionable groups (14 warning-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.
5 of 5 significant source file(s) are orphaned — their living knowledge has decayed to nothing, so no one currently understands them. The largest is src/Gateway/Neuroglia.K8s.Eventing.Gateway.Infrastructure/Services/EventRegistry.cs.
Further orphaned files (smaller)
What to do
Resolve the 1 Further orphaned files (smaller) finding(s) in Knowledge Freshness. — One of this dimension's main actionable groups (1 recommendation-level).
Detailed fixes: d34_recommendation.md · top locations in Appendix A, every location in findings.md.
What it measures: Whether files that change together actually belong together — pairs that repeatedly co-change in git history despite having no explicit code dependency, surfacing the hidden/logical coupling (and boundaries in the wrong place) a static scan can't see.
Method: Pairwise co-occurrence over the per-commit file sets in git history (production source only — tests and generated dropped): Degree-of-Coupling = shared ÷ min individual revisions, reported above noise floors (each file ≥10 revisions, ≥5 shared commits, ≥50% strength); sweeping commits excluded. Deterministic over fixed history.
Coverage: Population: PRODUCTION source files only — test and generated files are dropped before pairing, so a class co-changing with its own test (trivially ~100%) can't drown the real production↔production coupling. Pairs ranked by Degree-of-Coupling; coupling through a build step, config, or non-source file isn't seen.
Other · Architecture — 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.
What to do
The domain core is a small share of production code — check that business logic isn't leaking into the application/infrastructure layers (a thin domain is the anemic-domain smell).
Other · Architecture — Whether 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.
`ChannelManager` is a singleton (one shared instance) but mutates instance state outside any lock (_Disposed; e.g. `_Disposed` at line 88). — ChannelManager.cs:13
`ResourceController` is a singleton (one shared instance) but mutates instance state outside any lock (_Disposed; e.g. `_Disposed` at line 667). — ResourceController.cs:23
`EventChannel` is a singleton (one shared instance) but mutates instance state outside any lock (_Disposed; e.g. `_Disposed` at line 191). — EventChannel.cs:24
`EventChannel` is a singleton (one shared instance) but mutates instance state outside any lock (_Disposed; e.g. `_Disposed` at line 431). — EventChannel.cs:27
What to do
Keep singletons stateless or back their state with thread-safe types (Concurrent*/Immutable*); otherwise concurrent callers race.
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 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.
`ISubscription` declares 19 members. A wide interface forces every implementer and caller to depend on methods they don't use (the Interface-Segregation 'I' in SOLID). Split it into focused role-interfaces. — ISubscription.cs:11
What to do
Split fat interfaces into focused role-interfaces so clients depend only on what they use.
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.
No [Authorize]/policies and no imperative guard methods (throw-on-violation) were found — endpoints may be unprotected.
What to do
Protect endpoints by default-deny: [Authorize] + role/policy authorization, or imperative guard methods (throw-on-violation) called from every handler.
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 commands have a single handler (one owner of the decision) and fan-out is modelled with events.
Method: Roslyn scan (event-driven gated): command-shaped messages identified by convention; handler count per command checked for the exactly-one rule. Deterministic, hard fact.
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.
`PublishCloudEventToChannelCommandHandler.Handle` writes to the database AND publishes to the message bus in the same flow, with no outbox referenced in this path. These two writes aren't atomic — a crash between them either loses the message (DB committed, publish failed) or emits a phantom event (publish succeeded, DB rolled back). Use the transactional outbox pattern (e.g. MassTransit's EF/Marten outbox) so the message is committed in the same transaction as the state change and dispatched afterwards. — PublishCloudEventToChannelCommandHandler.cs:48
What to do
Adopt the transactional outbox pattern so DB writes and message publishes commit atomically — no lost or phantom events on a crash.
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.
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.
`Configure` takes parameters but its body is empty — it accepts inputs and does nothing. Either implement it or remove it. — CreateSubscriptionCommandMappingConfiguration.cs:12
What to do
Finish or delete the unfinished stubs (NotImplementedException / empty / constant-returning bodies) — they are dead surface that looks live.
Maturity · Maturity — Whether the repo and its projects have a README, and whether it's substantive and current.
Method: Filesystem scan: README presence, word count, and headings for depth; git history for staleness. Exhaustive across root and project dirs, deterministic.
What to do
Add an 'Architecture' / 'How it works' section to the root README — the high-level shape.
Add a README to the 16 of 16 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.
Do you agree with this assessment?
P1 · CI/CD gates0.0 / 10Critical✓ Tool-verified
Readiness · Readiness — Whether an automated pipeline builds and tests every change.
Method: Filesystem scan: CI workflow files (.github/workflows, .gitlab-ci.yml, etc.) for build and test stages. Exhaustive, deterministic.
No CI workflow found (.github/workflows, azure-pipelines.yml, .gitlab-ci.yml, …) — changes aren't gated by an automated build/test.
What to do
Add a CI workflow that builds and runs the test suite on every push/PR.
Do you agree with this assessment?
P10 · Library API & versioning2.0 / 10Critical✓ Tool-verified
Readiness · Readiness — For a library: a deliberate (small) public API surface and explicit semantic versioning so consumers can depend on it safely.
Method: Roslyn scan: public API surface area and semantic-versioning markers (SemVer attributes, changelog entries) for libraries. Exhaustive, deterministic.
126/127 types (99%) are public. For a library, every public type is a stability contract — make internal-by-default and expose only the intended API.
No <Version>/<VersionPrefix>/GitVersion/MinVer detected. A published library needs explicit semantic versioning so consumers can reason about breaking changes.
What to do
Make types internal by default; expose only the deliberate public API so internals can change without breaking consumers.
Stamp a semantic version (csproj <Version> or GitVersion/MinVer) and follow semver for breaking changes.
Do you agree with this assessment?
P2 · Observability7.5 / 10Strong✓ 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.
What to do
Add an approval/environment gate (required reviewers / protection rules) before production promotion.
Readiness · Readiness — Whether outbound HTTP calls are wrapped in resilience (retry/timeout/circuit-breaker) so a failing dependency doesn't cascade.
Method: Roslyn scan: Polly resilience markers (Retry, CircuitBreaker, Timeout) on outbound HTTP invocations. Computed per type, deterministic.
The app makes outbound HTTP calls but no resilience handler was detected (Polly / AddStandardResilienceHandler / circuit-breaker). A slow or failing dependency will cascade — add timeouts, retries with back-off, and a circuit breaker.
What to do
Add `AddStandardResilienceHandler()` (or Polly policies) to your HttpClient registrations so a flaky dependency can't take the app down.
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.
No Span/Memory, pooling (ArrayPool/ObjectPool), stackalloc, ValueTask or buffer-writer usage was found. If this library sits on a hot path, these reduce the GC pressure it puts on its host — a bonus, not a requirement.
What to do
On hot paths, prefer Span<T>/ReadOnlySpan<T>, ArrayPool<T>, stackalloc and ValueTask to cut allocations a consumer would otherwise inherit.
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.
1 blocking call(s) on async work (.Wait()/.GetAwaiter().GetResult()) — these waste a thread and can deadlock in a consumer with a synchronization context.
Only 0/103 awaits use ConfigureAwait(false). A library that captures the caller's context can stall or deadlock its host — the classic way a dependency drags an app down.
What to do
Make the call chain async end-to-end and await it — never block on a Task with .Wait()/.GetAwaiter().GetResult() in library code.
In library code, append .ConfigureAwait(false) to every await (or set <ConfigureAwait>false</ConfigureAwait> / use the analyzer CA2007) so the library never captures the host's context.
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 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.
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.
`async void` can't be awaited and its exceptions crash the process instead of propagating. Return `Task` unless this is a top-level event handler. (×3) — ResourceController.cs:140, ResourceController.cs:347, ResourceController.cs:447
Blocking on a Task with `.Wait()`/`.GetAwaiter().GetResult()` can deadlock (and wastes a thread). Make the caller `async` and `await` instead. — EventChannel.cs:354
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 33/63 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. (×25) — ResourceController.cs:140, ResourceController.cs:170, ResourceController.cs:189, …
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.
An empty catch block silently discards the error — failures vanish with no log and no rethrow. Log it, handle it, or don't catch it. (×6) — ResourceController.cs:178, ResourceController.cs:283, ResourceController.cs:484, …
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.
Logging an interpolated string (`$"..."`) collapses the event to plain text — you lose the named, queryable properties structured logging exists for. Use a message template with placeholders: `LogInformation("User {UserId} did {Action}", id, action)`. (×25) — Channel.cs:63, Channel.cs:76, Channel.cs:89, …
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.
0/15 projects enable <Nullable>enable</Nullable>. NRTs catch a whole class of null-deref bugs at compile time.
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.
AX4 Dependency direction — not applicable to a CQRS architecture (the inward-dependency rule is for layered/clean styles)
AX7 Slice cohesion — not applicable — not a vertical-slice architecture
AX8 Test isolation — no test/production split to check
AX9 CQS / query purity — no CQRS query handlers detected — query purity is not applicable to this codebase
AXB2 Runtime readiness — no data
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.
D10 Test Quality — ~114 lines of test code exist on disk but weren't loaded from the analyzed solution (excluded from the .sln, or co-located/using a test attribute not loaded here), so test quality couldn't be assessed. Include the tests in the analyzed solution to enable this check.
D11 Test Reliability — No tests discovered
D23 Boundary Type-Coupling — Bounded contexts not declared
D25 ADR Conformance — no ADRs to check
D32 Data Compliance (PII/GDPR) — No PII/GDPR-handling patterns detected (p/gdpr ruleset) — no data-compliance surface to assess.
D33 JS/npm Dependency Vulnerabilities — No JS/npm manifest or lockfile found outside bin/obj (package.json, package-lock.json, yarn.lock, pnpm-lock.yaml, bun.lockb); no JS dependencies to scan.
D36 Supply-chain Provenance & Signing — No CI/build pipeline found (.github/workflows, .gitlab-ci.yml, azure-pipelines.yml, Jenkinsfile, .circleci); there is no build to attest provenance for.
D37 Vulnerability-disclosure Policy — No vulnerability-disclosure policy file found (SECURITY.md, .github/SECURITY.md, docs/SECURITY.md, .well-known/security.txt). A coordinated-disclosure policy may live off-repo, so this is not evidenced rather than failed.
D38 OSV Dependency Vulnerabilities — No JS/npm lockfile found outside bin/obj (package-lock.json, yarn.lock, pnpm-lock.yaml, bun.lockb); nothing for OSV to scan.
D39 IL Efficiency — The target did not build, so no IL was available to measure.
D7 Architectural Integrity — no checkable ADRs and no dependency cycles — architectural integrity not assessed
D8 Code Coverage — Coverage not measured
DM1 Domain Modelling — not run — 0/3 markers found
ED3 Event naming — no domain or integration events detected — event-naming check not applicable
ES1 Event Sourcing — not run — only 1/3 markers (an event-store package (Marten/EventStore))
P12 CI test-gate honesty — no CI workflow found
P5 DR & Backup — not evidenced — repo shows no backup/RTO/RPO controls; absence of evidence is not evidence of a working control
P6 Release Hygiene — not evidenced — no changelog, version stamp or semver release tag in the repo
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
SC1 Supply-chain hygiene — no data
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.
High CVE: AutoMapper 9.0.0 — AutoMapper 9.0.0 (transitive) has a High advisory; affects 4 projects — one upgrade fixes all. https://github.com/advisories/[GHSA redacted]
High CVE: Newtonsoft.Json 12.0.2 — Newtonsoft.Json 12.0.2 (transitive) has a High advisory; affects 6 projects — one upgrade fixes all. https://github.com/advisories/[GHSA redacted]
High CVE: System.Net.Http 4.3.0 — System.Net.Http 4.3.0 (transitive) has a High advisory; affects 8 projects — one upgrade fixes all. https://github.com/advisories/[GHSA redacted]
High CVE: System.Text.RegularExpressions 4.3.0 — System.Text.RegularExpressions 4.3.0 (transitive) has a High advisory; affects 9 projects — one upgrade fixes all. https://github.com/advisories/[GHSA redacted]
High CVE: AutoMapper 10.1.1 — AutoMapper 10.1.1 (transitive) has a High advisory; affects 3 projects — one upgrade fixes all. https://github.com/advisories/[GHSA redacted]
High CVE: Microsoft.AspNetCore.Http 2.1.1 — Microsoft.AspNetCore.Http 2.1.1 (transitive) has a High advisory; affects 4 projects — one upgrade fixes all. https://github.com/advisories/[GHSA redacted]
High CVE: Newtonsoft.Json 11.0.2 — Newtonsoft.Json 11.0.2 (transitive) has a High advisory; affects 5 projects — one upgrade fixes all. https://github.com/advisories/[GHSA redacted]
Off the main sequence: Neuroglia.K8s.Eventing — Neuroglia.K8s.Eventing: abstractness 0.00, instability 0.00, distance 1.00 — zone of pain — concrete and heavily depended-on, so it's rigid to change.
Off the main sequence: Neuroglia.K8s.Eventing.Gateway.Integration — Neuroglia.K8s.Eventing.Gateway.Integration: abstractness 0.25, instability 0.00, distance 0.75 — zone of pain — concrete and heavily depended-on, so it's rigid to change.
Off the main sequence: Neuroglia.Mediation.AspNetCore — Neuroglia.Mediation.AspNetCore: abstractness 0.00, instability 0.25, distance 0.75 — zone of pain — concrete and heavily depended-on, so it's rigid to change.
Medium CVE: KubernetesClient 2.0.33 — KubernetesClient 2.0.33 (transitive) has a Medium advisory; affects 6 projects — one upgrade fixes all. https://github.com/advisories/[GHSA redacted]
Medium CVE: Microsoft.Rest.ClientRuntime 2.3.10 — Microsoft.Rest.ClientRuntime 2.3.10 (transitive) has a Medium advisory; affects 6 projects — one upgrade fixes all. https://github.com/advisories/[GHSA redacted]
D22 · Internal API Consistency· Redundant naming for the same operation · ×1
Redundant naming for the same operation: 'Pub' vs 'Publish'. Both methods accept a CloudEvent and return IActionResult, indicating they perform the same publish action but with different HTTP route names. — Unify to 'Publish' for clarity and consistency across all controllers. (signatures: EventsController.Pub(CloudEvent cloudEvent) | EventsController.Publish(CloudEvent e))
D22 · Internal API Consistency· Inconsistent naming for subscription operations · ×1
Inconsistent naming for subscription operations: 'Sub'/'Unsub' vs 'Subscribe'/'Unsubscribe'. The first controller uses abbreviated names while others use full descriptive names. — Standardize on full descriptive names: 'Subscribe' and 'Unsubscribe' across all controllers. (signatures: EventsController.Sub(CreateSubscriptionCommandDto command) | EventsController.Subscribe(SubscriptionOptionsDto subscription) | EventsController.Unsub(string subscriptionId) | EventsController.Unsubscribe(string subscriptionId))
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.
Shell project: kubernetes deployment/kubernetes/kubernetes.csproj— `kubernetes` contributes only 0 significant line(s) — an empty/placeholder project is structural noise. Remove it or fold its contents into a real project.
Thin analysable surface across projects — 2 project(s) carry only a thin slice of real code (e.g. `Neuroglia.Mediation.AspNetCore` with 37 significant line(s)). The mean analysable-surface weight is 90 %, lowering Solution Shape by about 0.8 point(s). Consolidate thin projects or grow them into substantial, well-scoped assemblies.
No ADRs found — No ADRs found at common paths; consider documenting architectural decisions in Docs/ADL/ or similar.
D21 · Naming Consistency· Typo in property name · ×1
Typo in property name: 'IsSuccessfull' (double 'l') is used instead of the standard 'IsSuccess' or 'IsSuccessful'. — Rename to 'IsSuccess' or 'IsSuccessful' to fix the typo and align with common C# conventions. (symbols: Neuroglia.Mediation.OperationResult.IsSuccessfull, Neuroglia.Mediation.IOperationResult.IsSuccessfull)
D23 · Boundary Type-Coupling· Bounded contexts not declared · ×1
Bounded contexts not declared — At 7115 LoC across 16 projects the codebase is large and multi-module, so explicit bounded contexts are needed. Declare architecture.contexts (≥2) in config to assess cross-boundary type coupling.
misleading comment src/Channels/EventStore/Neuroglia.K8s.Eventing.Channels.EventStore.Infrastructure/HashFile.cs:201— "In GetDif, above `int`: "If all a[n] == b[n] then return zero"" — Fix - this is the 'equal' branch; the comment labels it as 'zero', which is wrong. Correct the label or remove the comment.
D34 · Knowledge Freshness· Further orphaned files (smaller) · ×1
Further orphaned files (smaller) — 5 smaller file(s) also have no living knowledge — folded into the freshness score and metrics rather than listed individually (5 orphaned of 5 analysed files in total).
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.
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
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Run 019f155a-4378-7357-a298-59d96557a4ce · every finding is also locatable in findings.md, and the complete scoring record (with exit codes + durations) in sidecar.json.
Issues: 31 · Warnings: 47 · Recommendations: 32 · Info: 31 — Appendix A · all findings · full markdown report.
Generated by Watchdog — deterministic code-health analysis. 29-06-2026 @ 21:47 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.