Public report — drawio-desktop, published 6 Aug 2026.
Concrete security findings (CVE IDs, secret matches, dependency versions) are hidden in this version;
ask the repo owner for the full report.
50findings with an exact file:lineof 59 — the remainder are repo-wide signals (a dimension-level measurement, not a single line); open any file:line and verify
45/102dimensions across the health lenses — 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.
jgraph/drawio-desktop carries serious gaps (36%). Several issues below can materially affect correctness, security, or the cost of changing it — and propagate to everything that depends on it.
The area that most needs attention is Readiness (20%) — releases are harder to depend on — versioning, release notes and dependency hygiene are thin, so consumers can't easily tell what changed or trust an upgrade. Code Health (49%) is the next concern — changes there are slower and more error-prone.
Leadership focus, highest impact first: ILogger (or Serilog) and log at meaningful points across… (Observability); SAST step (e.g. CodeQL) or a security analyzer package (Security & performance tooling); Automate deployment (Helm/Kubernetes manifests or a pipeline… (Deployment & Rollback).
For scale: — (~0 production lines); rebuilding it from scratch would take roughly — (—). 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.
A full-fidelity diff against the previous run's complete recorded findings — line-move tolerant: a finding that only shifted line counts as unchanged, only genuinely new titles/files surface here.
Top priorities
The highest-leverage moves; the full ranked list is in the Roadmap below.
1
Resolve the 1 No automated tests finding(s) in Code Coverage.
Of everything flagged, the best return on effort is: Adopt ILogger (or Serilog) and log at meaningful points across the projects. The rest can wait behind it.
Evidence: priority ranking: top of 5 ranked by impact/effort
→ Adopt ILogger (or Serilog) and log at meaningful points across the projects.
At a glance — Code Health · 49% · Weak · gated by D2, R1
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
A03:2021 — Injection
20
High / Critical
A06:2021 — Vulnerable & Outdated Components
2
High / Critical
Roadmap
First, implement comprehensive logging using ILogger or Serilog across all projects to establish baseline observability. Next, integrate static application security testing and secret scanning into the build process to identify vulnerabilities early. Then, automate the deployment pipeline using tools like Helm or Kubernetes to ensure releases are repeatable and reversible. Finally, expand test coverage to include all production modules and resolve existing gaps in automated testing.
Ranked by impact ÷ effort. "Helps" is the estimated gain on the 0–100 health score.
Do this
Helps
Effort
Dimension
Resolve the 1 No automated tests finding(s) in Code Coverage.
Documentation Quality: The README mentions releases but does not link to or describe the GitHub Actions workflow that actually builds and publishes binaries.
Methodology & how to trust this report
Watchdog is a deep, periodic assessment — run each sprint, monthly, or quarterly, taking the time to go wider and deeper than a quick check and surfacing in one coherent report what you'd otherwise piece together from a dozen separate tools. It scores deterministically: the same commit yields the same score, every run. 43 of 45 evaluated dimensions are computed purely by tools and static analysis (confidence 1.0); 2 documentation/naming judgement(s) are LLM-assisted and labelled advisory. Overall confidence is 0.7 — 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 — 45 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, 50 of 59 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.
D18 Solution Shape — evaluation did not complete — Dimension evaluation failed — excluded from the score.
D30 Dependency Vulnerabilities — scanner not present in this environment — The backing tool was not installed where this scan ran, so this dimension was not scored. Install the tool (or run in the hosted environment, where it is always present) for a graded result.
D31 IaC & Container Security — scanner not present in this environment — The backing tool was not installed where this scan ran, so this dimension was not scored. Install the tool (or run in the hosted environment, where it is always present) for a graded result.
D32 Data Compliance (PII/GDPR) — scanner not present in this environment — The backing tool was not installed where this scan ran, so this dimension was not scored. Install the tool (or run in the hosted environment, where it is always present) for a graded result.
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.
D8 Code Coverage: Coverage is measured by building and running the suite (`dotnet test --collect`) inside Watchdog's isolated image — the target repo is never modified, and nothing on your systems runs. So coverage exists only when the suite builds and runs within the inline time budget; one that needs external services, can't build, or exceeds the budget yields no coverage (D8 then degrades to not-measured, not a low score). Line coverage also says nothing about assertion quality.
D9 Test Distribution: The test-pyramid shape is inferred from project/folder naming and references, with a single test host bucketed per-file by its path tier and content signals — a suite that names tiers unconventionally and gives no per-file signal can still be mis-bucketed.
D12 Dependency Hygiene: Dependency health reads manifests and lockfiles — a vulnerability in a vendored/copied dependency, or risk from how a dependency is actually used, is outside this view.
D13 Secret Scanning: Secret detection is signature- and entropy-based on the current tree — a secret that does not match a known pattern, or one already rotated, will not be flagged (a clean scan is "nothing matched", not "no secrets exist").
D15 Churn × Complexity Hotspots: Churn hotspots come from git history — a freshly imported or squashed repository has no churn signal, and recent rewrites can mask a historically risky file.
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.
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.
D21 Naming Consistency: Naming quality is an LLM judgement over a bounded sample — it assesses clarity/consistency of the names it sees, not domain-correctness, and is advisory.
D26 Project Cohesion: Project focus is sized from members/namespaces per project — a project that is broad by deliberate design reads the same as one that has sprawled.
D27 Navigability: Indirection/navigability is structural — it measures hops to follow a call, not whether that indirection buys real flexibility or just ceremony.
D28 Secrets (history): Secret-history scanning sweeps the git log for known patterns — a secret that predates the available history, or never matched a signature, is not found (clean means "nothing matched in the history we can see").
D29 Static Analysis (SAST): SAST findings are pattern-based (semgrep) — it finds classes of bug it has rules for; logic flaws, auth/authorization gaps and issues needing runtime context are out of reach (and clean means "no rule matched").
D33 JS/npm Dependency Vulnerabilities: JS/npm CVE matching reads package manifests and lockfiles — risk from how a dependency is used, and advisories not yet published, fall outside this scan.
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.
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 (3): D19, D21, M4 (model: Local LLM). For these, a model reads a bounded sample and sets the numeric score (documentation, ADR quality, naming, comment value, onboarding) — D25 sets the ADR-conformance fraction over sampled code, D22 judges API accuracy over a sample. These are sampled and advisory by design: they vary at the margins between runs and are never a deterministic measurement. Every other score in this report is tool-computed at confidence 1.0.
What it measures: How tangled the control flow is — methods with many branches are hard to test and change.
Method: Cyclomatic complexity per method (1 + decision points), computed exhaustively across production source; test projects separated by convention. Deterministic.
+ 4 more group(s) — more in Appendix A; the complete list is findings.md.
What to do
Resolve the 1 checkFileContent (cyclomatic 156) finding(s) in Cyclomatic Complexity — start with electron.js. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 (anonymous) (cyclomatic 59) finding(s) in Cyclomatic Complexity — start with electron.js. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 readPdfXml (cyclomatic 34) finding(s) in Cyclomatic Complexity — start with electron.js. — One of this dimension's main actionable groups (1 warning-level).
Enforce Cyclomatic Complexity in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Prevented — provenance only; does not change the score.
Detailed fixes: d1_recommendation.md · top locations in Appendix A, every location in findings.md.
What it measures: How hard the code is for a person to follow, beyond raw branching.
Method: Cognitive complexity per method (Sonar-style nesting-penalized score), computed exhaustively over production code, excluding test projects. Deterministic.
+ 9 more group(s) — more in Appendix A; the complete list is findings.md.
What to do
Resolve the 1 checkFileContent (cognitive 197) finding(s) in Cognitive Complexity — start with electron.js. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 (anonymous) (cognitive 108) finding(s) in Cognitive Complexity — start with electron.js. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 readPdfXml (cognitive 93) finding(s) in Cognitive Complexity — start with electron.js. — 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 Classes7.5 / 10Strong✓ Tool-verified
What it measures: Over-large classes that try to do too much ("god classes").
Method: God-class detection by line and method-count thresholds per logical type (partial classes unified), filtered for generated code and registration/contract false positives. Deterministic.
Resolve the 1 FileTooLong finding(s) in God Classes — start with electron.js. — One of this dimension's main actionable groups (1 warning-level).
Enforce God Classes in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Prevented — provenance only; does not change the score.
Detailed fixes: d3_recommendation.md · top locations in Appendix A, every location in findings.md.
What it measures: Copy-pasted code that should be shared instead.
Method: Code duplication via token-stream sliding windows with type-aware normalization (locals masked, type names preserved), density-scored per KLoC of production code. Deterministic.
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.
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.
Do you agree with this assessment?
D8 · Code Coverage0.0 / 10Critical✓ Tool-verified
What it measures: How much of the code is actually exercised by tests.
Method: Coverage from coverlet runs or committed reports (Cobertura/OpenCover/lcov), computed per-file with structured exclusions for generated, trivial, and glue code. When the suite can't be built/run in-image AND no report is committed, coverage is reported NOT-MEASURED (excluded from the score) with the precondition to make it measurable — never a LoC-ratio proxy folded in as if measured. Deterministic.
No automated tests — the solution has no test code.
No automated tests
What to do
Resolve the 1 No automated tests finding(s) in Code Coverage. — One of this dimension's main actionable groups (1 issue-level).
Enforce Code Coverage in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Verified — provenance only; does not change the score.
Detailed fixes: d8_recommendation.md · top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D9 · Test Distribution0.0 / 10Critical✓ Tool-verified
What it measures: Whether the test suite has a healthy mix of unit / integration / end-to-end tests.
Method: Test projects classified (Unit/Integration/BDD/E2E) from compiled metadata; test methods counted exhaustively across projects with placement-agnostic disk fallback. Deterministic.
What it measures: Whether dependencies are current, secure, and not bloated.
Method: Manifest scan via dotnet list package across all projects; worst-signal-per-package deduction (saturating for vulnerabilities, capped-linear for deprecation/outdated) per KLoC. Exhaustive, deterministic.
What it measures: Whether any secrets (keys, tokens, passwords) have leaked into the code.
Method: In-process native secret scanner (entropy plus signature patterns) across all tracked files; no external tool. A clean result is a measured 10, not no-data zero. Deterministic.
What it measures: Files that change often and are also complex — the riskiest hotspots.
Method: Per production file churn times cyclomatic complexity over a rolling window, computed from git and Roslyn/JS/Razor analysis. Exhaustive, deterministic per commit date.
Resolve the 2 Hotspot finding(s) in Churn × Complexity Hotspots — start with args.js, electron.js. — One of this dimension's main actionable groups (2 warning-level).
Detailed fixes: d15_recommendation.md · top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D16 · Bus Factor10.0 / 10Exemplary✓ Tool-verified
What it measures: Whether knowledge is concentrated in too few people (the "bus factor").
Method: Living knowledge per author via time-decayed commit attribution (6-month half-life, focus weighting) across largest source files. Deterministic, avoids blame's mechanical-refactor false positives.
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 documentation is clear and complete for an open-source diagramming desktop app: the README gives a one-paragraph overview plus Windows install notes, license, and security claims; RELEASE_PROCESS.md documents the full release process with tooling versions pinned, roles, and a detailed procedure (prepare-release, pre-release verification, audit, publish) that is clipped mid-sentence; BUILDING_FOR_PERSONAL_USE.md explains how to fork for personal use with an explicit unsigned opt-in plus clone/recursion steps. The three docs together cover the app's purpose, install, security, release process, and build for non-code contributors — a strong set.
The README mentions releases but does not link to or describe the GitHub Actions workflow that actually builds and publishes binaries.README.md
What to do
Resolve the 1 The README mentions releases but does not link to or describe the GitHub… finding(s) in Documentation Quality — start with README.md. — One of this dimension's main actionable groups (1 recommendation-level).
Detailed fixes: d19_recommendation.md · top locations in Appendix A, every location in findings.md.
What it measures: Whether names — types, methods, variables — are clear and consistent.
Method: Judged by language model at low temperature (0.0-0.1) on a deterministic random symbol sample (fixed size, not exhaustive), with disclosed confidence band. Advisory, sampled.
What it measures: 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.
What it measures: Whether any secrets were ever committed — scanned across the full git history, not just now.
Method: Git-history secret scan via gitleaks detect over full history in an isolated checkout; each match flagged High. Exhaustive; degrades cleanly when tool absent.
What it measures: Real static-analysis (SAST) findings — likely security bugs in the code, any language.
Method: Polyglot static analysis via semgrep across the repo using the pinned, image-baked p/security-audit + p/owasp-top-ten rulesets (no scan-time registry fetch); severity rules (ERROR/WARNING/INFO) map to a full-band severity-weighted score. Exhaustive, deterministic; degrades on parse failure.
Coverage: semgrep pattern rules over all files — exhaustive for the rule set, blind to classes of bug without a rule (clean = no rule matched).
High: github-actions-mutable-action-tag · ×20.github/workflows/electron-builder-win.yml:15detected by semgrep finding
What to do
Resolve the 20 High finding(s) in Static Analysis (SAST) — start with prepare-release.yml (9), personal-build.yml (4), electron-builder-win.yml (3). — One of this dimension's main actionable groups (20 issue-level).
Detailed fixes: d29_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.
What it measures: Whether the repository publishes a coordinated-vulnerability-disclosure policy (SECURITY.md or security.txt) with a reporting contact, so finders know how to report a vulnerability. Presence of a policy file with a contact, not whether the policy is adequate or honoured.
Method: Vulnerability-disclosure policy read deterministically from the repo: a SECURITY.md (root/.github/docs) or .well-known/security.txt / security.txt, regex-checked for a reporting contact (email / URL / mailto). Present + contact → 10; present without a contact → 4; NotApplicable when no policy file exists (it may live off-repo). Detects the policy file's presence + contact, not its adequacy.
What it measures: Whether dependencies have known published vulnerabilities (CVEs) per the OSV database — npm and other lockfile ecosystems, parsed natively. Complements D33 (npm via trivy) and D30 (.NET via dotnet).
Method: npm/multi-ecosystem CVE scan via osv-scanner (queries the osv.dev database + parses lockfiles natively: package-lock/yarn/pnpm/bun); severity tally (Critical/High/Medium/Low) to 0-10 tight normalizer (8.0). NotApplicable without a JS lockfile. Additive to D33 (trivy fs); exhaustive + deterministic, DB kept fresh.
High CVE: [GHSA redacted] · ×2package-lock.jsondetected by osv-scanner finding
What to do
Resolve the 2 High CVE finding(s) in OSV Dependency Vulnerabilities — start with package-lock.json (2). — One of this dimension's main actionable groups (2 issue-level).
Detailed fixes: d38_recommendation.md · top locations in Appendix A, every location in findings.md.
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.
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 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.
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.
README advertises a RAG / ML engine, but no ML/RAG code or dependency exists
What to do
Reconcile the README with reality: README advertises a RAG / ML engine, but no ML/RAG code or dependency exists.
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 · Observability0.0 / 10Critical✓ Tool-verified
Readiness · Readiness — Whether the code is diagnosable in production — structured logging, tracing/metrics, health checks.
Readiness · Readiness — Whether SAST, secret/dependency scanning and performance benchmarking are wired in (presence, not runtime).
Method: Filesystem/Roslyn scan: CodeQL, Dependabot, secret-scanning, and BenchmarkDotNet presence in pipelines and projects. Exhaustive, deterministic.
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.
No Helm/Kubernetes/compose manifests or pipeline deploy stage found — releases appear manual, which is slower and riskier to reverse.
What to do
Automate deployment (Helm/Kubernetes manifests or a pipeline deploy stage) so releases are repeatable and reversible.
Do you agree with this assessment?
R1 · Type Safety0.0 / 10Critical✓ Tool-verified
React / JS · Code Health — How much of the frontend is typed TypeScript vs untyped JavaScript.
Method: Frontend file inventory: the share of typed TypeScript vs untyped JavaScript across the source tree. Deterministic, exhaustive over frontend files.
0 typed · 11 plain JS
What to do
Migrate the remaining .js/.jsx files to TypeScript.
React / JS · Code Health — Per-function cyclomatic/cognitive complexity from the token-level function scanner (D-386) — real branching, not a regex heuristic.
Method: Per-function cyclomatic/cognitive complexity from a token-level function scanner (real branching, not a regex heuristic), computed over every frontend function. Deterministic.
Branch-heavy code is where defects cluster — extract decisions into smaller functions. (×8) — electron.js:2974, electron.js:637, electron.js:2359, …
What to do
Break down the listed branch-heavy functions; aim P95 cyclomatic ≤ 5.
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R3 · Large Files5.0 / 10Adequate✓ Tool-verified
React / JS · Code Health — How many components/modules exceed the large-file threshold.
Method: Components/modules exceeding the large-file threshold, counted exhaustively across the frontend source tree. Deterministic.
1 file(s) over 400 lines
What to do
Split the oversized components into smaller, focused ones.
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R4 · Test Coverage2.5 / 10Weak✓ Tool-verified
React / JS · Readiness — Static test reachability (D-386): the share of production files reachable from any test via the import graph — measured without running anything.
Method: Static test reachability: the share of production files reachable from any test via the import graph — measured without running anything. Deterministic.
No test imports this module directly or transitively — its behavior is unverified. (×6) — electron.js, progress-bar.js, electron-preload.js, …
What to do
Add tests that import the unreached modules (directly or through their public entry).
React / JS · Readiness — How outdated the npm dependencies are (a maturity signal). JS/npm CVEs are scored separately in D33 (JS/npm Dependency Vulnerabilities).
Method: npm dependency staleness from manifest/registry metadata (a maturity signal; JS/npm CVEs are scored separately in D33). Deterministic.
What to do
Bump outdated dependencies to current versions to limit upgrade debt.
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R6 · Tooling6.7 / 10Adequate✓ Tool-verified
React / JS · Readiness — Whether the project wires up test, lint and typecheck — detected from each package.json script's COMMAND (eslint / tsc / vitest / jest / playwright), not just its name, and corroborated against CI-workflow invocations so a tool run only in CI still counts.
Method: package.json scanned for test/lint/typecheck script wiring. Deterministic presence check.
test ✓ · lint ✓ · typecheck ✗
What to do
Add the missing tooling (eslint, tsc) as package.json scripts and run them in CI.
Do you agree with this assessment?
R7 · Dead Code9.6 / 10Exemplary✓ Tool-verified
React / JS · Code Health — Files unreachable from every application/tooling/test entry point, and exports nothing imports (module-graph reachability, D-386).
Method: Dead code: files unreachable from every application/tooling/test entry point plus exports nothing imports, via module-graph reachability. Deterministic, exhaustive over the import graph.
Unreachable from the 5 application, 0 tooling and 3 test entry point(s) detected in this repo. Gate removals on your build/type-check — an undetected custom entry would make these reachable.
no import path from any entry point (5 application, 0 tooling, 3 test roots considered) (×2) — electron-preload.js, preload.js
What to do
Delete the dead files and unused exports — every line is maintenance cost and rebuild-estimate inflation with zero runtime value.
React / JS · Readiness — npm dependency truthfulness (D-386): unused dependencies, imports not declared anywhere, and type-/test-only packages shipped as production deps.
Method: npm dependency truthfulness: unused dependencies, imports declared nowhere, and type-/test-only packages shipped as production deps — from the manifest + import graph. Deterministic.
Declared in the root/package.json but never imported anywhere in that package or its workspace members — dead weight and attack surface. Verify against build tooling before removing. (×3)
What to do
Remove unused dependencies, declare unlisted imports explicitly, and demote type-/test-only packages to devDependencies.
React / JS · Architecture — Import cycles in the module graph (D-386) — files that can only be understood and changed together.
Method: Import cycles in the module graph, detected exhaustively over JS/TS imports (the same cycle detection as the .NET coupling dimension). Deterministic.
Other · Code Health — Whether the code avoids sync-over-async (deadlock-prone blocking on tasks) and async void.
Method: Roslyn syntax scan: async methods scanned for .Wait()/.GetAwaiter().GetResult() and async-void outside event handlers. Deterministic, hard fact per invocation.
Other · Code Health — Whether exceptions are handled rather than silently swallowed or rethrown with lost stack traces.
Method: Roslyn syntax scan: every catch clause counted; empty catches and bare rethrows flagged. Population is all catch clauses, not estimated. Deterministic, hard fact.
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.
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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.
Capped at Fair by a Critical contributor — resolve it before relying on this lens.
Not included — 58 check(s) not relevant to this codebase
These checks had nothing to measure here (no tests, no git history, the codebase is small, or the architecture style doesn't apply), so they're omitted above rather than scored low.
AC1 Text alternatives — No web markup found — accessibility is not applicable to this repository.
AC2 Forms & labels — No web markup found — accessibility is not applicable to this repository.
AC3 Page structure — No web markup found — accessibility is not applicable to this repository.
AC4 Keyboard semantics — No web markup found — accessibility is not applicable to this repository.
AC5 ARIA correctness — No web markup found — accessibility is not applicable to this repository.
AC6 Visual & motion safety — No web markup found — accessibility is not applicable to this repository.
AC7 A11y enforcement — No web markup found — accessibility is not applicable to this repository.
AX1 Captive dependencies — no DI registrations detected
AX10 Code composition — no source files detected — code composition not applicable
AX2 Stateful singletons — no singleton implementations detected
AX3 Project dependency cycles — no csproj graph available
AX4 Dependency direction — no csproj graph available
AX6 Interface segregation — no public interfaces
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.
C2 Access Controls — No access-control surface detected in the analyzed source — no web/app surface to authorize (no HTTP API or web-UI project) and no authorization code at all (no [Authorize]/policies, no imperative guard methods). Access control is therefore N/A here — this is a library/CLI, which is authorized by its CALLER, not by itself. If this codebase grows request handlers, the dimension reactivates and a default-deny posture is expected then.
C3 Audit Trail — No personal data detected in the analyzed source — no PII-typed entity/column names (Email, FirstName, DateOfBirth, …), no ASP.NET Identity / user-account model, and no stored user credentials. GDPR data-protection controls are therefore N/A here. If this is intentional, record the no-PII posture in an ADR; if the app does process personal data, name those fields conventionally so this dimension activates.
C4 Data Retention — No personal data detected in the analyzed source — no PII-typed entity/column names (Email, FirstName, DateOfBirth, …), no ASP.NET Identity / user-account model, and no stored user credentials. GDPR data-protection controls are therefore N/A here. If this is intentional, record the no-PII posture in an ADR; if the app does process personal data, name those fields conventionally so this dimension activates.
C5 Data-Subject Rights — No personal data detected in the analyzed source — no PII-typed entity/column names (Email, FirstName, DateOfBirth, …), no ASP.NET Identity / user-account model, and no stored user credentials. GDPR data-protection controls are therefore N/A here. If this is intentional, record the no-PII posture in an ADR; if the app does process personal data, name those fields conventionally so this dimension activates.
D10 Test Quality — No tests in the analyzed solution to assess for quality.
D11 Test Reliability — Test reliability not included
D14 License Compliance — license scan produced no result — the tool ran but its JSON output could not be parsed; the offline NuGet fallback resolved nothing
D17 Explicit Debt — the C# workspace loaded 0 projects, so explicit-debt density could not be measured
D18 Solution Shape — Dimension evaluation failed
D20 ADR Quality — N/A — ADRs are expected on deployable products with a user-facing host, not consumed libraries; no ADR log is required here.
D22 Internal API Consistency — No exposed public API
D23 Boundary Type-Coupling — Zero projects and zero LoC mean the codebase is trivial and has no structure to justify boundaries.
D24 Comment Value — No inline comments to assess — comment value is not applicable here.
D25 ADR Conformance — no ADRs to check
D30 Dependency Vulnerabilities — No .NET solution found; no NuGet dependencies to scan for vulnerabilities.
D31 IaC & Container Security — No Infrastructure-as-Code or container manifests found (Dockerfile, Terraform, Kubernetes/Helm, CloudFormation); nothing to scan.
D32 Data Compliance (PII/GDPR) — No PII/GDPR ruleset is bundled (the public p/gdpr semgrep pack was retired) — data compliance is not assessed in this scan.
D39 IL Efficiency — The target did not build, so no IL was available to measure.
D6 Cohesion (LCOM4) — No production classes were analyzable, so cohesion (LCOM4) was not measured (the solution likely failed to load or has no production code).
D7 Architectural Integrity — no checkable ADRs and no dependency cycles — architectural integrity not assessed
DM1 Domain Modelling — not run — 0/3 markers found
ED1 Event-Driven — not run — 0/3 markers found
ED5 Idempotency — no mutating command handlers or message consumers detected — idempotency check not applicable
ES1 Event Sourcing — not run — 0/3 markers found
GD1 Unfinished & placeholder code — no source files
IC1 Incompleteness & stubs — no C# methods found
P12 CI test-gate honesty — no data
P5 DR & Backup — not evidenced — repo shows no backup/RTO/RPO controls; absence of evidence is not evidence of a working control
P6 Release Hygiene — not evidenced — no changelog, version stamp or semver release tag in the repo
P7 Outbound HTTP resilience — not applicable — this isn't a service/API/worker
P8 Schema migrations — no EF Core usage detected
P9 Domain vs controller coverage — no coverage report found on disk — run tests with `--collect:"XPlat Code Coverage"` (or in CI) to enable this cross-layer check
PF1 Benchmark discipline — Performance is assessed only for perf-relevant repos — a packaged library, one that ships benchmarks, or one already using allocation-aware APIs. This repo isn't one, so the Performance lens is not applicable and is excluded from the score.
PF2 Allocation hygiene — Performance is assessed only for perf-relevant repos — a packaged library, one that ships benchmarks, or one already using allocation-aware APIs. This repo isn't one, so the Performance lens is not applicable and is excluded from the score.
PF3 Async & latency hygiene — Performance is assessed only for perf-relevant repos — a packaged library, one that ships benchmarks, or one already using allocation-aware APIs. This repo isn't one, so the Performance lens is not applicable and is excluded from the score.
R11 Import Boundaries — No recognizable feature-sliced/layered src layout — boundary rules not applicable.
S1 Web-Security Posture — No web surface detected in the analyzed source — no HTTP API or web-UI project (no controllers/minimal-API endpoints, no Razor/Blazor views) and no web middleware (HTTPS redirection, HSTS, security headers, cookies). Transport security, security headers, secure cookies, CSRF/input-validation and middleware-order controls are therefore N/A here — this is a library/CLI/worker, not a web app. Crypto hygiene was still checked and found nothing to flag. If this codebase becomes web-facing, the dimension reactivates automatically.
SC1 Supply-chain hygiene — no data
X2 Cancellation propagation — no async methods found
X5 Nullable reference types — no NRT-eligible projects
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: github-actions-mutable-action-tag .github/workflows/electron-builder-win.yml:15— GitHub Actions step uses a mutable tag or branch reference. Tags and branch names can be silently repointed by the action owner, enabling supply-chain attacks — as seen in the trivy-action and kics-github-action compromises. Pin the reference to a full 40-character commit SHA instead, e.g. `uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608`.
High: github-actions-mutable-action-tag .github/workflows/electron-builder-win.yml:19— GitHub Actions step uses a mutable tag or branch reference. Tags and branch names can be silently repointed by the action owner, enabling supply-chain attacks — as seen in the trivy-action and kics-github-action compromises. Pin the reference to a full 40-character commit SHA instead, e.g. `uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608`.
High: github-actions-mutable-action-tag .github/workflows/electron-builder-win.yml:59— GitHub Actions step uses a mutable tag or branch reference. Tags and branch names can be silently repointed by the action owner, enabling supply-chain attacks — as seen in the trivy-action and kics-github-action compromises. Pin the reference to a full 40-character commit SHA instead, e.g. `uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608`.
High: github-actions-mutable-action-tag .github/workflows/electron-builder.yml:28— GitHub Actions step uses a mutable tag or branch reference. Tags and branch names can be silently repointed by the action owner, enabling supply-chain attacks — as seen in the trivy-action and kics-github-action compromises. Pin the reference to a full 40-character commit SHA instead, e.g. `uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608`.
High: github-actions-mutable-action-tag .github/workflows/electron-builder.yml:32— GitHub Actions step uses a mutable tag or branch reference. Tags and branch names can be silently repointed by the action owner, enabling supply-chain attacks — as seen in the trivy-action and kics-github-action compromises. Pin the reference to a full 40-character commit SHA instead, e.g. `uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608`.
High: github-actions-mutable-action-tag .github/workflows/electron-builder.yml:70— GitHub Actions step uses a mutable tag or branch reference. Tags and branch names can be silently repointed by the action owner, enabling supply-chain attacks — as seen in the trivy-action and kics-github-action compromises. Pin the reference to a full 40-character commit SHA instead, e.g. `uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608`.
High: github-actions-mutable-action-tag .github/workflows/personal-build.yml:38— GitHub Actions step uses a mutable tag or branch reference. Tags and branch names can be silently repointed by the action owner, enabling supply-chain attacks — as seen in the trivy-action and kics-github-action compromises. Pin the reference to a full 40-character commit SHA instead, e.g. `uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608`.
High: github-actions-mutable-action-tag .github/workflows/personal-build.yml:43— GitHub Actions step uses a mutable tag or branch reference. Tags and branch names can be silently repointed by the action owner, enabling supply-chain attacks — as seen in the trivy-action and kics-github-action compromises. Pin the reference to a full 40-character commit SHA instead, e.g. `uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608`.
High: run-shell-injection .github/workflows/personal-build.yml:53— Using variable interpolation `${{...}}` with `github` context data in a `run:` step could allow an attacker to inject their own code into the runner. This would allow them to steal secrets and code. `github` context data can have arbitrary user input and should be treated as untrusted. Instead, use an intermediate environment variable with `env:` to store the data and use the environment variable in the `run:` script. Be sure to use double-quotes the environment variable, like this: "$ENVVAR".
High: github-actions-mutable-action-tag .github/workflows/personal-build.yml:66— GitHub Actions step uses a mutable tag or branch reference. Tags and branch names can be silently repointed by the action owner, enabling supply-chain attacks — as seen in the trivy-action and kics-github-action compromises. Pin the reference to a full 40-character commit SHA instead, e.g. `uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608`.
High: run-shell-injection .github/workflows/prepare-release.yml:42— Using variable interpolation `${{...}}` with `github` context data in a `run:` step could allow an attacker to inject their own code into the runner. This would allow them to steal secrets and code. `github` context data can have arbitrary user input and should be treated as untrusted. Instead, use an intermediate environment variable with `env:` to store the data and use the environment variable in the `run:` script. Be sure to use double-quotes the environment variable, like this: "$ENVVAR".
High: github-actions-mutable-action-tag .github/workflows/prepare-release.yml:50— GitHub Actions step uses a mutable tag or branch reference. Tags and branch names can be silently repointed by the action owner, enabling supply-chain attacks — as seen in the trivy-action and kics-github-action compromises. Pin the reference to a full 40-character commit SHA instead, e.g. `uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608`.
High: github-actions-mutable-action-tag .github/workflows/prepare-release.yml:57— GitHub Actions step uses a mutable tag or branch reference. Tags and branch names can be silently repointed by the action owner, enabling supply-chain attacks — as seen in the trivy-action and kics-github-action compromises. Pin the reference to a full 40-character commit SHA instead, e.g. `uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608`.
High: run-shell-injection .github/workflows/prepare-release.yml:68— Using variable interpolation `${{...}}` with `github` context data in a `run:` step could allow an attacker to inject their own code into the runner. This would allow them to steal secrets and code. `github` context data can have arbitrary user input and should be treated as untrusted. Instead, use an intermediate environment variable with `env:` to store the data and use the environment variable in the `run:` script. Be sure to use double-quotes the environment variable, like this: "$ENVVAR".
High: run-shell-injection .github/workflows/prepare-release.yml:130— Using variable interpolation `${{...}}` with `github` context data in a `run:` step could allow an attacker to inject their own code into the runner. This would allow them to steal secrets and code. `github` context data can have arbitrary user input and should be treated as untrusted. Instead, use an intermediate environment variable with `env:` to store the data and use the environment variable in the `run:` script. Be sure to use double-quotes the environment variable, like this: "$ENVVAR".
High: run-shell-injection .github/workflows/prepare-release.yml:193— Using variable interpolation `${{...}}` with `github` context data in a `run:` step could allow an attacker to inject their own code into the runner. This would allow them to steal secrets and code. `github` context data can have arbitrary user input and should be treated as untrusted. Instead, use an intermediate environment variable with `env:` to store the data and use the environment variable in the `run:` script. Be sure to use double-quotes the environment variable, like this: "$ENVVAR".
High: github-actions-mutable-action-tag .github/workflows/prepare-release.yml:250— GitHub Actions step uses a mutable tag or branch reference. Tags and branch names can be silently repointed by the action owner, enabling supply-chain attacks — as seen in the trivy-action and kics-github-action compromises. Pin the reference to a full 40-character commit SHA instead, e.g. `uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608`.
High: run-shell-injection .github/workflows/prepare-release.yml:270— Using variable interpolation `${{...}}` with `github` context data in a `run:` step could allow an attacker to inject their own code into the runner. This would allow them to steal secrets and code. `github` context data can have arbitrary user input and should be treated as untrusted. Instead, use an intermediate environment variable with `env:` to store the data and use the environment variable in the `run:` script. Be sure to use double-quotes the environment variable, like this: "$ENVVAR".
High: run-shell-injection .github/workflows/prepare-release.yml:363— Using variable interpolation `${{...}}` with `github` context data in a `run:` step could allow an attacker to inject their own code into the runner. This would allow them to steal secrets and code. `github` context data can have arbitrary user input and should be treated as untrusted. Instead, use an intermediate environment variable with `env:` to store the data and use the environment variable in the `run:` script. Be sure to use double-quotes the environment variable, like this: "$ENVVAR".
High: github-actions-mutable-action-tag .github/workflows/stale.yml:21— GitHub Actions step uses a mutable tag or branch reference. Tags and branch names can be silently repointed by the action owner, enabling supply-chain attacks — as seen in the trivy-action and kics-github-action compromises. Pin the reference to a full 40-character commit SHA instead, e.g. `uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608`.
D38 · OSV Dependency Vulnerabilities· High CVE · ×2
High CVE: [GHSA redacted] package-lock.json— brace-expansion 1.1.17: [GHSA redacted] — upgrade to 1.1.18
High CVE: [GHSA redacted] package-lock.json— fast-uri 3.1.4: [GHSA redacted] — upgrade to 3.1.5
Hotspot: src/main/electron.js src/main/electron.js— src/main/electron.js changed 41 times in last 90 days, max complexity 156. 9 of those changes were fix/bug commits — a defect-dense hotspot worth prioritising.
Hotspot: src/main/args.js src/main/args.js— src/main/args.js changed 11 times in last 90 days, max complexity 25.
Change coupling: args.js ↔ electron.js src/main/args.js— `src/main/args.js` and `src/main/electron.js` change together 75% of the time (9 shared commits) with no explicit dependency — a hidden/logical coupling. If they belong together, co-locate them; if not, break the coupling.
Unpinned build actions — CI references GitHub Actions by a floating ref (@main / @tag) rather than a pinned commit SHA, weakening build integrity.
Recommendation — 6 finding(s)
D11 · Test Reliability· Test reliability not included · ×1
Test reliability not included — No test projects found, so reliability couldn't be assessed.
D19 · Documentation Quality· The README mentions releases but does not link to or describe the GitHub Actions workflow that actually builds and publishes binaries. · ×1
The README mentions releases but does not link to or describe the GitHub Actions workflow that actually builds and publishes binaries. README.md— Add a short 'How to Build from Source' section pointing to the prepare-release workflow, so readers can confirm they are building the same thing.
No tests found — No test projects found in the repository.
Info — 1 finding(s)
D22 · Internal API Consistency· No exposed public API · ×1
No exposed public API — No intentionally-exposed types (IsPackable or .Contracts) to evaluate.
Appendix B — Reproduction & audit trail
Every external tool invocation behind a deep-scan dimension — the tool, its captured version, the exact command, how many findings it yielded, and a link to the retained raw output. To reproduce any finding: check out the same commit and run the command shown (repo-relative — never an absolute scratch path). The complete raw scanner output is retained verbatim under artifacts/raw/ (indexed in artifacts/raw/index.json); per-invocation exit codes and wall-clock durations are in sidecar.json — kept out of this table so the rendered report stays byte-identical across runs of the same commit.
trivy: not applicable — No Infrastructure-as-Code or container manifests found (Dockerfile, Terraform, Kubernetes/Helm, CloudFormation); nothing to scan.
Run 019fd862-3fe7-719c-a0d0-3678501fe4f6 · every finding is also locatable in findings.md, and the complete scoring record (with exit codes + durations) in sidecar.json.
Issues: 24 · Warnings: 28 · Recommendations: 6 · Info: 1 — Appendix A · all findings · full markdown report.
Generated by Watchdog — deterministic code-health analysis. 06-08-2026 @ 18:42 UTC.
Downloadable artifacts
Machine-readable and reproducible from this commit + frozen rubric — drop them straight into a contract appendix, a CRA dossier, or a downstream SCA / VEX tool.