Public report — flock, published 5 Aug 2026.
Concrete security findings (CVE IDs, secret matches, dependency versions) are hidden in this version;
ask the repo owner for the full report.
182findings with an exact file:lineof 196 — the remainder are repo-wide signals (a dimension-level measurement, not a single line); open any file:line and verify
42/106dimensions across the health lenses60074 LoC — wide & deep
Executive summary
Read through the Preview lens: this repo is pre-1.0 / in development, so the colour bands are relaxed to what a preview needs — *green* means good enough for a preview, not yet production-stable. Code correctness and security stay near-strict even here; the score itself is absolute and comparable across repos.
whiteducksoftware/flock is sound in substance but carries real gaps (57%). It is not in crisis, but the issues below raise the cost of changing it — friction its consumers ultimately inherit.
It is strongest in Architecture (90%) — the structure is clean and changes stay contained.
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 (51%) — 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. Accessibility (56%) is the next concern — it raises ongoing delivery and operational cost.
Leadership focus, highest impact first: tests that import the unreached modules (directly or through… (Test Coverage); Enable purge protection / soft-delete (and prevent_destroy… (DR & Backup); Nothing pauses a release for a human (Deployment & Rollback).
For scale: Medium (~60,074 production lines); rebuilding it from scratch would take roughly ~0.8 person-years (~1–2 engineers). Approximate, ±~30%.
It builds on a genuinely strong Architecture foundation (90%); the priorities above are the highest-leverage way to bring the rest up to that level.
How the score is built — each lens's share of the headlineWidth is the lens's weight in the worst-heaviest fold (the weakest area pulls hardest); colour is that lens's own band. A lens fixes the score in proportion to its width.
186 finding(s) are new versus the previous scan (2026-07-29) — surfaced by this scheduled scan itself, no pull request required. Showing the first 100; the full set is in the report.
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.
0.8× (at 57% quality) — the last 20% of quality is most of the work
Size & shape
Medium · effort split not classified (source measured from disk; the effort-tier breakdown is a C#-only syntax walk)
Dead frontend code
~279 LoC unreachable (4 file(s)) — that slice of this estimate buys code with zero runtime value; deleting it is the cheapest win in this report (the R7 card lists every file)
This codebase represents roughly ~0.8 person-years of build effort (about ~€120,000 to rebuild). Its weakest lens is Readiness at 51% — the part of that asset most exposed by the findings below.
How we model this: boilerplate at a scaffolding rate + logic × domain Standard (×1.0) — standard service × a 0.8× quality factor, at €60–95/h; indicative, ±~30% · size measured directly from source · effort from total production LoC as straight-line logic (the tier split is a C#-only syntax walk), a conservative lower bound. Indicative only — most sensitive to the hourly rate and the domain tier (both tunable in config).
Top priorities
The highest-leverage moves; the full ranked list is in the Roadmap below.
1
Add tests that import the unreached modules (directly or through their public entry).
Nothing pauses a release for a human: publish as a draft release (or gate the release job on a protected tag/manual dispatch) so a bad build can be stopped before users can download it.
Value concentrated against a weak lens · Medium · Value at risk
This is a Medium asset (~0.8 person-years to rebuild), and its weakest lens is Readiness at 51%. The operational and business risk on an asset this size concentrates there — that's where remediation buys the most protection.
→ Direct remediation budget at Readiness first — highest risk-reduction per euro on an asset this size.
Highest-leverage move · Medium · Leverage
Of everything flagged, the best return on effort is: Add tests that import the unreached modules (directly or through their public entry). The rest can wait behind it.
Evidence: priority ranking: top of 5 ranked by impact/effort
→ Add tests that import the unreached modules (directly or through their public entry).
Architecture — module dependency matrix
368 modules, 12 dependencies — every dependency points down the layering, so there are no cycles. Rows and columns are the same modules, ordered so that a module only depends on ones above it. A cell means the row depends on the column, and its number is how many type pairs create that dependency. Read one thing: is anything above the diagonal? A mark there is a dependency cycle. (A cycle is all this shows — an unusual but cycle-free dependency sits below the diagonal like any other.)
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
A06:2021 — Vulnerable & Outdated Components
40
High / Critical
A02:2021 — Cryptographic Failures
2
High / Critical
Roadmap
First, expand test coverage by adding tests for all unreached modules to ensure code is properly validated. Second, enable purge protection and soft-delete on critical resources to prevent accidental or malicious data loss. Third, implement an approval gate or draft release process to prevent bad builds from reaching users. Fourth, clean up the dependency tree by removing unused packages and explicitly declaring imports. Finally, update outdated dependencies to reduce upgrade debt and security risks.
Ranked by impact ÷ effort. "Helps" is the estimated gain on the 0–100 health score.
Do this
Helps
Effort
Dimension
Add tests that import the unreached modules (directly or through their public entry).
Nothing pauses a release for a human: publish as a draft release (or gate the release job on a protected tag/manual dispatch) so a bad build can be stopped before users can download it.
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. 40 of 42 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 0.6 — the weighted average across measured dimensions; it falls as more of the score leans on LLM-assisted judgement and rises when it's fully tool-backed.
Every figure here is one of three kinds, and we label which: ✓ Measured — a deterministic fact (LoC, complexity, coverage); ~ Modeled — an estimate from a stated model (cost, effort, value-at-risk), always a range with its assumptions, never a precise fact; ◐ Advisory — an LLM prose judgement. We never present a modelled estimate as if it were measured. Perfect or absent scores carry their provenance too (ADR-0011): ✓ Tool-verified means the property itself was measured across the surface; ○ Nothing flagged means the probes came back clean — a claim bounded by what a repository can show; ⊘ Not evidenced means a working control (a tested restore, an automated rollback) showed no positive evidence — absence of evidence is not evidence of a control, so it's excluded from the score rather than awarded a spurious 10; ◐ Sampled · advisory marks an LLM verdict over a bounded sample — advisory, never a deterministic measurement.
What we checked — 42 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, 182 of 196 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.
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.
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 (scaffolded migrations, designer/codegen output, protobuf/OpenAPI stubs, model snapshots) is EXCLUDED — its repetition is the tool's, not the team's — so the score reflects hand-written duplication only.
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.
D28 Secrets (history): Secret-history scanning sweeps the git log for known patterns — a secret that predates the available history, or never matched a signature, is not found (clean means "nothing matched in the history we can see").
D29 Static Analysis (SAST): SAST findings are pattern-based (semgrep) — it finds classes of bug it has rules for; logic flaws, auth/authorization gaps and issues needing runtime context are out of reach (and clean means "no rule matched").
D31 IaC & Container Security: IaC scanning checks Dockerfiles/Terraform/Kubernetes against best-practice rules — it cannot see the live cloud account, runtime configuration, or drift between the committed config and what is actually deployed.
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.
AC2 Forms & labels: Label association is read from static markup — a label wired up at runtime (JS-set aria-labelledby, framework-injected ids) reads as missing, a present label says nothing about whether its text is correct. A known UI-library field component (e.g. a JSX <TextField>) is now checked conservatively — flagged only when it carries NO label/aria-label/aria-labelledby/id/name — but wrapper/context-labelled libraries (Chakra/Radix FormControl+FormLabel) aren't statically visible (possible false positive) and non-JSX lowercased components are still skipped. A clean result is "no unlabelled native control found", not a labelling proof.
AC3 Page structure: Page structure is read from the static markup tree — landmarks, headings and lang injected at runtime aren't seen, heading ORDER is checked structurally (not against the rendered visual hierarchy), and lang/title/main fire only on full documents, never partials, and the data-table check sees header-cell presence (a <th> exists), not whether each header correctly associates with its cells. Static readiness, not conformance.
AC4 Keyboard semantics: Keyboard semantics are inferred from markup attributes — interactivity wired purely in script, focus managed at runtime, and component-level handlers are invisible. A clean result means "no static keyboard-trap shape", not a keyboard-operability proof.
AC5 ARIA correctness: ARIA correctness is checked against the static role/attribute shape — roles/attributes set dynamically aren't seen, a valid role says nothing about whether it matches the element's real behaviour, and required-state checks are suppressed when a JSX spread could supply them.
AC6 Visual & motion safety: Contrast and motion safety are PARTIAL by construction — literal colours (hex/rgb/hsl/named) in inline styles, in-repo <style> blocks, in-repo .css files, var() tokens, Tailwind neutral utilities and CSS-in-JS top-level declarations are read (same-rule/same-element colour+background pairs only); computed/runtime/theme colour, external-CDN stylesheets, CSS-in-JS dynamic (${…}) and nested-selector colours, cross-element pairs and image contrast stay out of reach, so a clean result is bounded by what the static CSS itself shows.
AC7 A11y enforcement: Enforcement is scored from in-repo config/CI evidence only — an a11y gate enforced in external tooling with no in-repo trace can't be credited, and a configured linter is presence, not proof the rules actually run or block a merge.
M4 Documentation accuracy: Onboarding quality is an LLM read of the docs/setup present — it cannot run the onboarding or measure how long a real new joiner takes; the verdict is sampled and advisory.
P4 Deployment & Rollback: Approval/branch-protection rules live in repository settings the scan cannot see — only their in-repo evidence (config files, workflows) is checked, so a control enforced purely in the host's settings reads as "not evidenced".
P5 DR & Backup: Backup/restore and disaster-recovery readiness is judged from in-repo evidence — a config that exists is not a tested restore, so the absence of positive evidence is reported as "not evidenced", never scored as present.
P6 Release Hygiene: Rollback/observability controls are inferred from repo artefacts (pipelines, dashboards-as-code) — controls configured in external tooling, with no in-repo trace, cannot be credited.
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.
+ 12 more group(s) — more in Appendix A; the complete list is findings.md.
What to do
Resolve the 1 GraphAssembler._build_agent_nodes (cyclomatic 36) finding(s) in Cyclomatic Complexity — start with graph_builder.py. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 OpenClawEngine.evaluate (cyclomatic 33) finding(s) in Cyclomatic Complexity — start with engine.py. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 OpenClawEngine._build_responses_payload (cyclomatic 27) finding(s) in Cyclomatic Complexity — start with engine.py. — 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.
+ 52 more group(s) — more in Appendix A; the complete list is findings.md.
What to do
Resolve the 1 GraphAssembler._build_agent_nodes (cognitive 76) finding(s) in Cognitive Complexity — start with graph_builder.py. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 OpenClawEngine.evaluate (cognitive 70) finding(s) in Cognitive Complexity — start with engine.py. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 OutputProcessor.make_outputs_for_group (cognitive 67) finding(s) in Cognitive Complexity — start with output_processor.py. — 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 Classes9.4 / 10Exemplary✓ Tool-verified
What it measures: Over-large classes that try to do too much ("god classes").
Method: God-class detection by line and method-count thresholds per logical type (partial classes unified), filtered for generated code and registration/contract false positives. Deterministic.
What it measures: Copy-pasted code that should be shared instead.
Method: Code duplication via token-stream sliding windows with type-aware normalization (locals masked, type names preserved), density-scored per KLoC of production code. Deterministic.
What it measures: Whether 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.
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.
59 source file(s) have their living knowledge concentrated in one author (≥90% of recent, decayed contribution). The largest is src/flock/frontend/src/components/modules/TraceModuleJaeger.tsx.
Off-boarding risk: anonymized user #1 · ×2
What to do
Resolve the 2 Off-boarding risk finding(s) in Bus Factor. — One of this dimension's main actionable groups (2 recommendation-level).
Detailed fixes: d16_recommendation.md · top locations in Appendix A, every location in findings.md.
What it measures: Whether the project's documentation is clear, complete, and useful.
Method: Judged by language model at low temperature (0.0-0.1) on a deterministic doc sample (READMEs plus first 25 architecture docs), with two-pass stability filtering. Advisory, sampled.
The documentation is clear and complete for a dual-repository project: the READMEs are well designed with rich branding badges, an OpenClaw integration banner, and a strong Flock architecture outline (the Declarative Blackboard Agent Orchestration section is visible), while Beads has a thorough What-is-Beads, Quick Start, Why-Beads, and Get-Started guide plus clipped but fully outlined sections. The e2e tests doc is also present and well written for its subject matter.
The README lacks an overview of the project's main features (Flock vs Beads) so a reader can tell which repo serves which purpose.README.md
✓ On the Gold path — maintain.
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: 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.
4 finding(s): 0 critical, 4 high, 0 medium, 0 low. Remediation for historically-committed secrets is credential rotation — they remain in history regardless of later deletion.
Secret: generic-api-keyexamples/11-openclaw/01_pizza_with_openclaw.py:56detected by gitleaks finding
Rotate the exposed credentials — git history can't be un-committed
What to do
Resolve the 1 Secret finding(s) in Secrets (history) — start with 01_pizza_with_openclaw.py. — One of this dimension's main actionable groups (1 issue-level).
Resolve the 1 Rotate the exposed credentials finding(s) in Secrets (history). — One of this dimension's main actionable groups (1 recommendation-level).
Detailed fixes: d28_recommendation.md · top locations in Appendix A, every location in findings.md.
What it measures: Real static-analysis (SAST) findings — likely security bugs in the code, any language.
Method: Polyglot static analysis via semgrep across the repo using the pinned, image-baked p/security-audit + p/owasp-top-ten rulesets (no scan-time registry fetch); severity rules (ERROR/WARNING/INFO) map to a full-band severity-weighted score. Exhaustive, deterministic; degrades on parse failure.
Coverage: semgrep pattern rules over all files — exhaustive for the rule set, blind to classes of bug without a rule (clean = no rule matched).
What it measures: Whether 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.
1 of 175 significant source file(s) are orphaned — their living knowledge has decayed to nothing, so no one currently understands them. The largest is src/flock/engines/auth/azure.py.
Further orphaned files (smaller)
✓ On the Gold path — maintain.
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.
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.
+ 1 more group(s) — more in Appendix A; the complete list is findings.md.
What to do
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 PR-triggered workflow without a permissions block finding(s) in Supply-chain Provenance & Signing. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 Secret passed as a command-line argument finding(s) in Supply-chain Provenance & Signing. — One of this dimension's main actionable groups (1 warning-level).
Detailed fixes: d36_recommendation.md · top locations in Appendix A, every location in findings.md.
What it measures: Whether dependencies have known published vulnerabilities (CVEs) per the OSV database — read natively from whatever lockfile the repository ships (Cargo, npm, Go, Python, Maven, RubyGems, …). D33 and D30 add ecosystem-specific scanners on top for npm and .NET.
Method: Multi-ecosystem dependency-CVE scan via osv-scanner --recursive (queries the osv.dev database + parses lockfiles natively across ecosystems: npm package-lock/yarn/pnpm/bun, Go go.mod, Rust Cargo.lock, Maven/Gradle pom.xml/gradle.lockfile, PyPI requirements.txt/poetry.lock/Pipfile.lock, Composer composer.lock, RubyGems Gemfile.lock, Hex mix.lock, pub pubspec.lock, Swift Package.resolved); severity tally (Critical/High/Medium/Low) to 0-10 tight normalizer (8.0). NotApplicable only when the repo declares no supported non-.NET dependency lockfile (a NuGet-only repo stays NotApplicable — .NET CVEs are D30's domain); coverage needs a resolved lockfile. Additive to D33 (trivy fs); exhaustive + deterministic, DB kept fresh.
High CVE: [GHSA redacted] · ×18requirements.txtdetected by osv-scanner finding
High vulnerability: [GHSA redacted] · ×5uv.lockdetected by osv-scanner finding
Critical CVE: [GHSA redacted] · ×3uv.lockdetected by osv-scanner finding
Medium CVE: PYSEC-2026-2132 · ×11requirements.txtdetected by osv-scanner finding
Medium vulnerability: [GHSA redacted]uv.lockdetected by osv-scanner finding
+ 2 more group(s) — more in Appendix A; the complete list is findings.md.
What to do
Resolve the 18 High CVE finding(s) in OSV Dependency Vulnerabilities — start with uv.lock (10), requirements.txt (5), package-lock.json (3). — One of this dimension's main actionable groups (18 issue-level).
Resolve the 5 High vulnerability finding(s) in OSV Dependency Vulnerabilities — start with uv.lock (2), requirements.txt (2), package-lock.json. — One of this dimension's main actionable groups (5 issue-level).
Resolve the 3 Critical CVE finding(s) in OSV Dependency Vulnerabilities — start with uv.lock, requirements.txt, package-lock.json. — One of this dimension's main actionable groups (3 issue-level).
Detailed fixes: d38_recommendation.md · top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
Frontend & cross-cutting dimensions
R = React/JS · M = Maturity · P = Readiness.
AC2 · Forms & labels6.1 / 10Adequate✓ Tool-verified
Other · Accessibility — Whether form controls have a programmatic label (an associated label, aria-label or aria-labelledby), buttons have text, links have an accessible name, fieldsets have a non-empty legend, known UI-library field components carry a label prop, and a placeholder isn't used as the only label. Static markup readiness, not a WCAG conformance claim.
Method: Static markup-model scan: inputs/selects/textareas checked for an associated label[for]/wrapping label/aria-label/aria-labelledby (per document), buttons for accessible text, fieldsets for a legend; placeholder-only labelling flagged. Deterministic, hard fact per control.
This control has only a placeholder — a placeholder is not a label (it vanishes on input and many AT ignore it). Add a <label htmlFor>, a wrapping <label>, or aria-label. (×7) — CorrelationIDFilter.tsx:73, TraceModuleJaeger.tsx:951, TraceModuleJaeger.tsx:1615, …
What to do
Give every control a programmatic label (a <label for> / wrapping <label> / aria-label) and every button text — a placeholder is not a label.
Other · Accessibility — Whether pages declare a language (well-formed BCP-47) and a non-empty title, expose exactly one main landmark and a sane heading order with non-empty headings, keep zoom enabled, title their iframes, give data tables header cells, and avoid meta-refresh. Static markup readiness, not a WCAG conformance claim.
Method: Static markup-model scan: html lang, document <title>, a main landmark and heading order on full documents only, plus zoom-disabling viewports, untitled iframes and meta-refresh anywhere. Deterministic, per structural checkpoint.
Other · Accessibility — Whether interactive behaviour is keyboard-reachable — no click handler on a non-interactive element lacking a role, tabindex and key handler, no positive tabindex, no href-less anchor, no placeholder-href (#/javascript) link acting as a button. Static markup readiness, not a WCAG conformance claim.
Method: Static markup-model scan: click handlers on non-interactive elements lacking role+tabindex+key handler, positive tabindex values, and href-less anchors. Components skipped, spreads suppressed. Deterministic, hard fact per element.
A click handler on a plain element isn't keyboard-operable. Use a <button>, or add role + tabIndex={0} + a key handler. (×3) — MessageHistoryTab.tsx:279, CorrelationIDFilter.tsx:101, LogicOperationsDisplay.tsx:177
A click handler on a plain element with no role and no tabindex: even where another element's key handler can reach it, assistive tech can neither focus it nor announce what it is. Use a <button>, or add role + tabIndex={0}. (×6) — TraceModuleJaeger.tsx:579, TraceModuleJaeger.tsx:605, TraceModuleJaeger.tsx:647, …
What to do
Make custom controls keyboard-operable (role + tabindex + key handler), drop positive tabindex, and give anchors a real href.
Other · Accessibility — Whether ARIA is used correctly — valid non-abstract roles, the ARIA state a role requires, valid (non-misspelled) aria-* attribute names, in-enum values for token-typed aria-* attributes, and no aria-hidden on (or wrapping) a focusable element. Static markup readiness, not a WCAG conformance claim.
Method: Static markup-model scan: role values checked against the WAI-ARIA role set (abstract/invalid flagged), required ARIA state for a role, and aria-hidden on a focusable element. Deterministic, role/attribute level.
Other · Accessibility — Whether focus outlines aren't removed without a replacement, motion respects prefers-reduced-motion, and literal CSS colour pairs meet contrast — PARTIAL: inline styles, in-repo <style> blocks, in-repo .css files, var() tokens, Tailwind neutral utilities and CSS-in-JS literals are read (hex/rgb/hsl/named), never computed/runtime/external-CDN colour. Static markup readiness, not a WCAG conformance claim.
Method: Static markup/CSS scan: inline outline:none/0, literal inline colour/background contrast against the 4.5:1 AA floor, and <style>-block animation without a prefers-reduced-motion guard. Deterministic but PARTIAL — only inline styles and in-repo CSS literals are visible.
Do you agree with this assessment?
AC7 · A11y enforcement4.0 / 10Weak✓ Tool-verified
Other · Accessibility — Whether accessibility is ENFORCED in the toolchain — an accessibility checker configured over the markup (an a11y lint rule set, e.g. eslint-plugin-jsx-a11y or vuejs-accessibility where the project lints JavaScript) and an automated accessibility assertion wired into tests or CI (axe/pa11y/Lighthouse or an equivalent) — on the Documented→Verified→Prevented ladder.
Method: Repo config/CI scan: an accessibility checker configured over the markup (an a11y lint rule set such as eslint-plugin-jsx-a11y / vuejs-accessibility where JavaScript is linted) and an automated accessibility assertion in tests or CI (axe/pa11y/Lighthouse or equivalent), graded on the Documented→Verified→Prevented rungs. Deterministic, presence/rung detection.
No accessibility enforcement found — no a11y linter (eslint-plugin-jsx-a11y) and no axe/pa11y/Lighthouse in tests or CI. Start with the linter to catch issues at author time.
What to do
Enforce accessibility in the toolchain: add eslint-plugin-jsx-a11y, then assert with vitest-axe in tests, then gate axe/pa11y/Lighthouse in CI.
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.
Maturity · Maturity — Whether key decisions (ADRs) and the high-level shape (C4/diagrams) are written down.
Method: Filesystem scan: ADR folder/naming conventions or content, plus Mermaid/PlantUML/C4/architecture.md discovery. Exhaustive, deterministic.
No Architecture Decision Records found — no conventional ADR directory, no `NNNN-title.md` documents and nothing ADR-shaped by content. Design rationale recorded elsewhere (a design-notes tree, a mailing list, pull-request discussion) is not visible to this check and is not re-findable per decision, so a future maintainer cannot ask why one choice was made and get an answer.
What to do
Record significant decisions one document per decision — dated, stating the context, the decision and its consequences — and keep them together wherever your design docs already live (a conventional `docs/adr/` tree with `NNNN-title.md` names is the most discoverable form).
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 Kubernetes, but no Kubernetes manifest or chart exists
README advertises a microservices architecture, but the repo is a single project with no service manifests
What to do
Reconcile the README with reality: README advertises Kubernetes, but no Kubernetes manifest or chart exists; README advertises a microservices architecture, but the repo is a single project with no service manifests.
Readiness · Readiness — Whether SAST, secret/dependency scanning and performance benchmarking are wired in (presence, not runtime).
Method: Filesystem scan: SAST configuration, dependency-update automation, secret scanning, and a benchmark harness or benchmark step — in this repository's own ecosystem. Exhaustive, deterministic.
No static application security testing detected. For this repository's stack, add bandit, `semgrep --config=p/python`, or CodeQL's python pack as a CI step.
What to do
Add a SAST step to CI running what this repository's stack ships: bandit, `semgrep --config=p/python`, or CodeQL's python pack — so a security regression fails the build instead of landing.
Enable Dependabot/Renovate or a dependency-review gate.
Add gitleaks/trufflehog in CI to block PRs that introduce committed secrets.
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
Nothing pauses a release for a human: publish as a draft release (or gate the release job on a protected tag/manual dispatch) so a bad build can be stopped before users can download it.
Do you agree with this assessment?
P5 · DR & Backup7.0 / 10Strong✓ Tool-verified
Readiness · Readiness — Whether disaster recovery is planned and codified — backups, geo-recovery, RTO/RPO, persistence guarantees — from IaC + container manifests + docs, never the live cloud.
Method: Filesystem scan: disaster recovery, backup, geo-recovery, RTO/RPO, persistence guarantees from IaC, manifests, and docs. Exhaustive, deterministic, never a live environment.
What to do
Enable purge protection / soft-delete (and prevent_destroy on critical resources) so data stores can't be lost to an accidental or malicious delete.
Readiness · Readiness — Whether releases are traceable — a maintained changelog and explicit version stamping.
Method: Filesystem scan: changelog file presence and version tags in csproj or git tags. Exhaustive, deterministic.
Do you agree with this assessment?
R1 · Type Safety10.0 / 10Exemplary✓ 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.
React / JS · Code Health — Copy-pasted token-identical blocks across the frontend (the D4 clone algorithm over JS/TS tokens, D-386).
Method: Copy-pasted token-identical blocks across the frontend (the D4 clone algorithm run over JS/TS tokens). Deterministic.
src/flock/frontend/src/components/details/MessageDetailWindow.tsx:75 · src/flock/frontend/src/components/details/NodeDetailWindow.tsx:46 — the 2 copies sit in sibling files in one directory, so check first whether one of them (or an existing module there) already owns this behaviour and the others should call it; otherwise extract it into one module in that directory and have each site call it. — MessageDetailWindow.tsx:75
src/flock/frontend/src/components/details/MessageHistoryTab.tsx:206 · src/flock/frontend/src/components/details/RunStatusTab.tsx:174 — the 2 copies are spread across 2 files, and what repeats is a LIST OF ENTRIES rather than behaviour — the same names written out more than once. Extract them into one shared, exported constant and spread that constant into each site, rather than into a function the sites call: a list like this often lives in declarative metadata (a decorator's options object, a static configuration table) that a build step must be able to read statically, where a function call is not allowed. Adding an entry to one copy and not the other is the failure this prevents. — MessageHistoryTab.tsx:206
src/flock/frontend/src/components/graph/MessageFlowEdge.tsx:29 · src/flock/frontend/src/components/graph/PendingBatchEdge.tsx:34 · src/flock/frontend/src/components/graph/PendingJoinEdge.tsx:34 — the 3 copies are spread across 3 files, and the CITED SPAN is not a self-contained block — it runs from inside one construct into the next (the tail of a branch plus the head of the following one, a run of switch arms, the end of a declaration plus the list that follows it) rather than covering a whole unit. So do not lift these lines literally: no call can be substituted for a half-open construct. Extract the enclosing repeated UNIT instead — the whole function, component or branch these lines sit in — and where the repetition IS the construct (a run of switch arms, a stack of near-identical declarations) replace it with one table or registry looked up by key rather than a helper each arm calls. The copies still drift apart the first time only one of them is edited, which is why this is reported. — MessageFlowEdge.tsx:29
src/flock/frontend/src/components/details/MessageDetailWindow.tsx:176 · src/flock/frontend/src/components/details/NodeDetailWindow.tsx:137 — the 2 copies are spread across 2 files, and the CITED SPAN is not a self-contained block — it runs from inside one construct into the next (the tail of a branch plus the head of the following one, a run of switch arms, the end of a declaration plus the list that follows it) rather than covering a whole unit. So do not lift these lines literally: no call can be substituted for a half-open construct. Extract the enclosing repeated UNIT instead — the whole function, component or branch these lines sit in — and where the repetition IS the construct (a run of switch arms, a stack of near-identical declarations) replace it with one table or registry looked up by key rather than a helper each arm calls. The copies still drift apart the first time only one of them is edited, which is why this is reported. — MessageDetailWindow.tsx:176
src/flock/frontend/src/components/details/MessageHistoryTab.tsx:151 · src/flock/frontend/src/components/details/RunStatusTab.tsx:112 — the 2 copies sit in sibling files in one directory, so check first whether one of them (or an existing module there) already owns this behaviour and the others should call it; otherwise extract it into one module in that directory and have each site call it. — MessageHistoryTab.tsx:151
src/flock/frontend/src/components/details/MessageHistoryTab.tsx:255 · src/flock/frontend/src/components/details/RunStatusTab.tsx:223 — the 2 copies are spread across 2 files, and the CITED SPAN is not a self-contained block — it runs from inside one construct into the next (the tail of a branch plus the head of the following one, a run of switch arms, the end of a declaration plus the list that follows it) rather than covering a whole unit. So do not lift these lines literally: no call can be substituted for a half-open construct. Extract the enclosing repeated UNIT instead — the whole function, component or branch these lines sit in — and where the repetition IS the construct (a run of switch arms, a stack of near-identical declarations) replace it with one table or registry looked up by key rather than a helper each arm calls. The copies still drift apart the first time only one of them is edited, which is why this is reported. — MessageHistoryTab.tsx:255
src/flock/frontend/src/components/details/MessageDetailWindow.tsx:309 · src/flock/frontend/src/components/details/MessageDetailWindow.tsx:342 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. — MessageDetailWindow.tsx:309
src/flock/frontend/src/components/graph/AgentNode.tsx:282 · src/flock/frontend/src/components/graph/AgentNode.tsx:345 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. — AgentNode.tsx:282
What to do
Extract the duplicated blocks into shared functions/components.
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) — PublishControl.tsx:258, TraceModuleJaeger.tsx:73, useKeyboardShortcuts.ts:28, …
What to do
Break down the listed branch-heavy functions; aim P95 cyclomatic ≤ 5.
Do you agree with this assessment?
R3 · Large Files4.7 / 10Adequate✓ Tool-verified
React / JS · Code Health — How many source files exceed the large-file threshold.
Method: Components/modules exceeding the large-file threshold, counted exhaustively across the frontend source tree. Deterministic.
10 file(s) over 400 lines (counted as significant lines — blank lines excluded — over production source only, tests excluded), largest first: src/flock/frontend/src/components/modules/TraceModuleJaeger.tsx (1840), src/flock/frontend/src/services/indexeddb.ts (738), src/flock/frontend/src/components/graph/GraphCanvas.tsx (732), src/flock/frontend/src/services/websocket.ts (648), src/flock/frontend/src/services/layout.ts (519), src/flock/frontend/src/components/controls/PublishControl.tsx (517) (+4 more).
What to do
Split each oversized file along the responsibilities already in it, into smaller focused modules in the same package.
Do you agree with this assessment?
R4 · Test Coverage3.1 / 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. Import reachability cannot see a test that executes a file by path instead of importing it, nor one that drives it through a running browser by navigating to a URL — if neither does, no test reaches this one. (×8) — TraceModuleJaeger.tsx, GraphCanvas.tsx, websocket.ts, …
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.
Do you agree with this assessment?
R6 · Tooling10.0 / 10Exemplary✓ 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.
Do you agree with this assessment?
R7 · Dead Code9.4 / 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 3 application, 4 tooling and 25 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 (3 application, 4 tooling, 25 test roots considered) (×4) — EmptyState.tsx, mockData.ts, LoadingSpinner.tsx, …
Nothing imports this binding — it is safe to review for removal. (×3) — layout.ts:598, themeApplicator.ts:129, performance.ts:12
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 src/flock/frontend/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.
Break each cycle by extracting the shared piece into a module both sides can import.
Do you agree with this assessment?
WCAG coverage — what static analysis assessed
Statically assessed 12 of 55 WCAG 2.2 Level A/AA success criteria (22%; ≈24% of the 50 WCAG 2.1 AA criteria for EN 301 549). The other 43 require runtime or manual evaluation. Partial signal only (a clean result is necessary, not sufficient; static analysis fully verifies none). This is accessibility readiness, not a conformance claim — a WCAG conformance claim requires manual evaluation (WCAG-EM 1.0).
The score is the rank-weighted fold of these lenses (worst-heaviest), each including its meta-dimensions; a lens with a Critical contributor is capped at Fair (its band reads "gated by …") and is never the strongest area however high its average.
Capped at Fair by a Critical contributor — resolve it before relying on this lens.
Not included — 64 check(s) not relevant to this codebase
These checks had nothing to measure here (no tests, no git history, the codebase is small, or the architecture style doesn't apply), so they're omitted above rather than scored low.
AC1 Text alternatives — No image/media element found in the parsed markup — AC1 not applicable here.
AX1 Captive dependencies — no DI registrations detected
AX10 Code composition — not assessed — code composition is computed by ROLE over a document set that was not loaded for this repository, because the repository is written in a language this check does not yet model, or because its projects failed to load. This is a gap in the analyzer, not a finding about this repository
AX2 Stateful singletons — no singleton implementations detected
AX3 Project dependency cycles — not assessed — project cycles and dependency direction are computed over a project-reference graph that was not loaded for this repository, because the repository is written in a language this check does not yet model, or because its projects failed to load. This is a gap in the analyzer, not a finding about this repository
AX4 Dependency direction — not assessed — project cycles and dependency direction are computed over a project-reference graph that was not loaded for this repository, because the repository is written in a language this check does not yet model, or because its projects failed to load. This is a gap in the analyzer, not a finding about this repository
AX5 Architecture & structure — not assessed — architecture style/structure is computed from a project graph (projects, types, module namespaces) that was not loaded for this repository, because the repository is written in a language this check does not yet model, or because its projects failed to load. This is a gap in the analyzer, not a finding about this repository
AX6 Interface segregation — not assessed — interface segregation is computed over a type surface that was not loaded for this repository, because the repository is written in a language this check does not yet model, or because its projects failed to load. This is a gap in the analyzer, not a finding about this repository
AX7 Slice cohesion — not applicable — not a vertical-slice architecture
AX8 Test isolation — not assessed — test isolation is computed from a project graph (which projects are test projects, and what they reference) that was not loaded for this repository, because the repository is written in a language this check does not yet model, or because its projects failed to load. This is a gap in the analyzer, not a finding about this repository
AX9 CQS / query purity — no CQRS query handlers detected — query purity is not applicable to this codebase
AXB2 Runtime readiness — Advisory — this card reports evidence and never carries a score, so there is nothing missing here.
C1 Data Protection — Not assessed: these personal data controls are read from a source model (declarative annotations, request middleware, entity/column names, guard methods) that was not loaded for this repository — because the repository is written in a language this check does not yet model, or because its projects failed to load. Absence of an idiom this check recognises is NOT evidence that this repository lacks personal data controls: it may implement them entirely in its own ecosystem. This is a gap in the analyzer's language coverage, not a finding about this repository.
C2 Access Controls — Not assessed: these authorization controls are read from a source model (declarative annotations, request middleware, entity/column names, guard methods) that was not loaded for this repository — because the repository is written in a language this check does not yet model, or because its projects failed to load. Absence of an idiom this check recognises is NOT evidence that this repository lacks authorization controls: it may implement them entirely in its own ecosystem. This is a gap in the analyzer's language coverage, not a finding about this repository.
C3 Audit Trail — Not assessed: these audit controls are read from a source model (declarative annotations, request middleware, entity/column names, guard methods) that was not loaded for this repository — because the repository is written in a language this check does not yet model, or because its projects failed to load. Absence of an idiom this check recognises is NOT evidence that this repository lacks audit controls: it may implement them entirely in its own ecosystem. This is a gap in the analyzer's language coverage, not a finding about this repository.
C4 Data Retention — Not assessed: these retention controls are read from a source model (declarative annotations, request middleware, entity/column names, guard methods) that was not loaded for this repository — because the repository is written in a language this check does not yet model, or because its projects failed to load. Absence of an idiom this check recognises is NOT evidence that this repository lacks retention controls: it may implement them entirely in its own ecosystem. This is a gap in the analyzer's language coverage, not a finding about this repository.
C5 Data-Subject Rights — Not assessed: these data-subject rights controls are read from a source model (declarative annotations, request middleware, entity/column names, guard methods) that was not loaded for this repository — because the repository is written in a language this check does not yet model, or because its projects failed to load. Absence of an idiom this check recognises is NOT evidence that this repository lacks data-subject rights controls: it may implement them entirely in its own ecosystem. This is a gap in the analyzer's language coverage, not a finding about this repository.
D10 Test Quality — ~57481 lines of test source are present (.py, .tsx, .ts) but the test-quality collector reads C# only, so skipped/assertion-free tests couldn't be counted. Not scored — this is a gap in the analyzer, not a finding about this repository.
D11 Test Reliability — Test reliability not included
D12 Dependency Hygiene — Dependency hygiene not measured — dependency manifest found but not parsed for hygiene
D14 License Compliance — Not scored — this repository's package manifest is not parsed for licence data yet. A gap in the analyzer's language coverage, NOT a finding that the repository's licenses are compliant (a Python pyproject.toml/requirements.txt (pip/uv/Poetry)), which this pass does not parse yet — so this dimension asserts nothing about this repository's licensing in either direction.
D17 Explicit Debt — explicit-debt markers are read through a C# workspace today, so they were not read for this repository's language — this asserts nothing about how many markers the code carries. Not scored — this is a gap in the analyzer, not a finding about this repository
D18 Solution Shape — D18 scores the shape of a .NET solution; this repository has no .NET solution or project files, so the dimension does not apply.
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 — Production source is present (.py, .ts, .tsx) but bounded contexts are resolved over the C#/VB project set, which exposed none, so context scope could not be assessed. Not scored — this is a gap in the analyzer, not a verdict about this repository. Declaring the codebase's bounded contexts (≥2) would let cross-boundary type coupling be assessed — see the recommendation on this dimension for where. Declare them in `.codehealth/config.yaml` at the repository root (create it if absent), mapping each context name to the module-path or namespace prefixes that belong to it — e.g. `architecture:` → `contexts:` → `Billing: ["src/billing", "Acme.Billing"]`, `Catalog: ["src/catalog", "Acme.Catalog"]`.
D24 Comment Value — No inline comments to assess — comment value is not applicable here.
D25 ADR Conformance — no ADRs to check
D26 Project Cohesion — Project cohesion is assessed over the .NET project set; this target exposed no projects, so project size and spread could not be assessed. Not scored — this is a gap in the analyzer's reach, not a verdict about this repository.
D27 Navigability — No calls could be sampled, so navigability was not assessed — tracing effort is measured over resolved call sites and this target exposed none. Not scored — this is a gap in the analyzer's reach, not a verdict about this repository.
D30 Dependency Vulnerabilities — Not scored — no dependency manifest in a supported ecosystem was read for this repository. A gap in the analyzer's language coverage, NOT a finding that the repository is free of vulnerable dependencies (a Python pyproject.toml/requirements.txt (pip/uv/Poetry) — not scanned yet) — where an OSV-supported manifest exists, dependency vulnerabilities for this repository are reported under D38 instead.
D32 Data Compliance (PII/GDPR) — No PII/GDPR-handling patterns detected (p/gdpr ruleset) — no data-compliance surface to assess.
D37 Vulnerability-disclosure Policy — No vulnerability-disclosure policy file found (SECURITY.md/.markdown/.rst/.txt at root or under .github/.forgejo/.gitea/docs, .well-known/security.txt). A coordinated-disclosure policy may live off-repo, so this is not evidenced rather than failed.
D39 IL Efficiency — D39 measures the IL emitted by a .NET build; this repository has no .NET solution or project files, so the dimension does not apply.
D40 Network Egress Confinement — No Kubernetes/orchestration workloads found in the repository manifests; network egress policy is a cluster-native control that may live at the platform/firewall layer, so there is nothing to assess here.
D41 Kernel & Syscall Confinement — No Kubernetes/orchestration workloads found in the repository manifests; seccomp/AppArmor/SELinux confinement is a workload-level control, so there is nothing to assess here.
D42 Runtime Threat Enforcement — No Kubernetes/orchestration workloads found in the repository manifests; runtime threat-detection and admission-control policy are cluster-level controls, so there is nothing to assess here.
D5 Coupling — Inter-project coupling could not be assessed — no analyzable project graph was found for this repository. Not scored: a gap in the analyzer's reach, not a verdict about this repository. (Coupling here is Martin afferent/efferent/instability plus reference cycles across a project-reference graph, read today from .NET project files; other ecosystems' module graphs are not read yet.)
D6 Cohesion (LCOM4) — Cohesion (LCOM4) is measured over a C#/VB class graph, and this repository's production source is .py, .ts, .tsx, which this pass does not read — so no class could be assessed. Not scored — this is a gap in the analyzer, not a finding about this repository.
D7 Architectural Integrity — no checkable ADRs, and no project-reference graph for the cycle pass to read — so this dimension makes no claim about dependency cycles in either direction (where this repository's language has an import-cycle lens, cycles are reported there). Architectural integrity not assessed
D8 Code Coverage — Coverage not included — suite not readable by the collector
D9 Test Distribution — Test source is present (.py, .tsx, .ts) but the test-pyramid classifier reads C# only, so its unit/integration/BDD/E2E split couldn't be counted. Not scored — this is a gap in the analyzer, not a finding about this repository.
DM1 Domain Modelling — applicable but not scored (2 of 3 signals for this style — below the bar we score at): 539 value object(s); 7 domain event(s)
ED1 Event-Driven — not scored — this repository shows none of the 3 signals this check looks for
ED5 Idempotency — no mutating command handlers or message consumers detected — idempotency check not applicable
ES1 Event Sourcing — not scored — this repository shows none of the 3 signals this check looks for
GD1 Unfinished & placeholder code — no source files
IC1 Incompleteness & stubs — not analysed — these correctness checks read a source model that was not loaded for this repository, because the repository is written in a language this check does not yet model, or because its projects failed to load. This is a gap in the analyzer, not a finding about this repository
P12 CI test-gate honesty — Reported, not scored — this card publishes what the CI gate does with the test inventory rather than grading it. The findings above are its output.
P2 Observability — Observability was not assessed: this check reads a source model that does not carry this repository's product — because the repository is written in a language this check does not yet model, or because its projects failed to load. Absence of a logging idiom this check recognises is NOT evidence that this repo lacks structured logging (it may log through its own ecosystem's logger). This is a gap in the analyzer, not a finding about this repository.
P7 Outbound HTTP resilience — not measured — the application kind could not be determined for this repo
P8 Schema migrations — not assessed — schema-migration practice is read from a source model that was not loaded for this repository, because the repository is written in a language this check does not yet model or because its projects failed to load. This is a gap in the analyzer, not a finding about this repository
P9 Domain vs controller coverage — no coverage report found on disk — produce a coverage report in a standard format (`coverage run -m pytest` then `coverage xml`) into the repo working tree before the scan — a CI step is the usual place, since the artefact is commonly gitignored, or wire coverage collection into CI, to enable this cross-layer check
PF1 Benchmark discipline — Performance was not assessed: this lens reads a source model that was not loaded for this repository, because the repository is written in a language this lens does not yet model or because its projects failed to load. This is a gap in the analyzer, not a finding about this repository — in particular it is NOT a statement that this repo is unpackaged or performance-careless.
PF2 Allocation hygiene — Performance was not assessed: this lens reads a source model that was not loaded for this repository, because the repository is written in a language this lens does not yet model or because its projects failed to load. This is a gap in the analyzer, not a finding about this repository — in particular it is NOT a statement that this repo is unpackaged or performance-careless.
PF3 Async & latency hygiene — Performance was not assessed: this lens reads a source model that was not loaded for this repository, because the repository is written in a language this lens does not yet model or because its projects failed to load. This is a gap in the analyzer, not a finding about this repository — in particular it is NOT a statement that this repo is unpackaged or performance-careless.
R11 Import Boundaries — No recognizable feature-sliced/layered src layout — boundary rules not applicable.
S1 Web-Security Posture — Not assessed: these web-security controls are read from a source model (declarative annotations, request middleware, entity/column names, guard methods) that was not loaded for this repository — because the repository is written in a language this check does not yet model, or because its projects failed to load. Absence of an idiom this check recognises is NOT evidence that this repository lacks web-security controls: it may implement them entirely in its own ecosystem. This is a gap in the analyzer's language coverage, not a finding about this repository.
SC1 Supply-chain hygiene — Advisory — this card reports evidence and never carries a score, so there is nothing missing here.
X1 Async correctness — not analysed — these correctness checks read a source model that was not loaded for this repository, because the repository is written in a language this check does not yet model, or because its projects failed to load. This is a gap in the analyzer, not a finding about this repository
X2 Cancellation propagation — not analysed — these correctness checks read a source model that was not loaded for this repository, because the repository is written in a language this check does not yet model, or because its projects failed to load. This is a gap in the analyzer, not a finding about this repository
X3 Exception handling — not analysed — these correctness checks read a source model that was not loaded for this repository, because the repository is written in a language this check does not yet model, or because its projects failed to load. This is a gap in the analyzer, not a finding about this repository
X4 Structured logging — not analysed — these correctness checks read a source model that was not loaded for this repository, because the repository is written in a language this check does not yet model, or because its projects failed to load. This is a gap in the analyzer, not a finding about this repository
X5 Nullable reference types — not analysed — these correctness checks read a source model that was not loaded for this repository, because the repository is written in a language this check does not yet model, or because its projects failed to load. This is a gap in the analyzer, not a finding about this repository
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.
Issue — 27 finding(s)
D38 · OSV Dependency Vulnerabilities· High CVE · ×18
High CVE: [GHSA redacted] requirements.txt— aiohttp 3.13.4: [GHSA redacted] — upgrade to 3.14.3. This is 1 of 14 advisories with a published fix this scan raises against aiohttp 3.13.4, and their fixed versions do not agree — anything below 3.14.3 still leaves at least one of them open. Take this package to 3.14.3 or later: that is the floor for the package, not this row's target alone. (in 2 dependency files: requirements.txt, uv.lock) This one row stands for the 14 advisories this scan raises against aiohttp 3.13.4: [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted], PYSEC-2026-2106, PYSEC-2026-2112, PYSEC-2026-2113, PYSEC-2026-237.
High CVE: [GHSA redacted] src/flock/frontend/package-lock.json— brace-expansion 2.0.2: [GHSA redacted] — brace-expansion is not declared in this repo's manifests: it is pulled in transitively, so upgrade the dependency that requires it (or pin brace-expansion to 2.1.2 with an `overrides` entry). This is 1 of 4 advisories with a published fix this scan raises against brace-expansion 2.0.2, and their fixed versions do not agree — anything below 2.1.4 still leaves at least one of them open. Take this package to 2.1.4 or later: that is the floor for the package, not this row's target alone. This one row stands for the 4 advisories this scan raises against brace-expansion 2.0.2: [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted].
High CVE: [GHSA redacted] uv.lock— gitpython 3.1.50: [GHSA redacted] — gitpython is not declared in this repo's manifests: it is pulled in transitively, so upgrade the dependency that requires it (or constrain gitpython to >=3.1.51 in your constraints/requirements file). This is 1 of 12 advisories with a published fix this scan raises against gitpython 3.1.50, and their fixed versions do not agree — anything below 3.1.57 still leaves at least one of them open. Take this package to 3.1.57 or later: that is the floor for the package, not this row's target alone. This one row stands for the 12 advisories this scan raises against gitpython 3.1.50: [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted].
High CVE: [GHSA redacted] requirements.txt— mcp 1.23.0: [GHSA redacted] — upgrade to 1.27.2. This is 1 of 3 advisories with a published fix this scan raises against mcp 1.23.0, and their fixed versions do not agree — anything below 1.28.1 still leaves at least one of them open. Take this package to 1.28.1 or later: that is the floor for the package, not this row's target alone. (in 2 dependency files: requirements.txt, uv.lock) This one row stands for the 3 advisories this scan raises against mcp 1.23.0: [GHSA redacted], [GHSA redacted], [GHSA redacted].
High CVE: [GHSA redacted] uv.lock— mistune 3.2.1: [GHSA redacted] — mistune is not declared in this repo's manifests: it is pulled in transitively, so upgrade the dependency that requires it (or constrain mistune to >=3.3.0 in your constraints/requirements file). This one row stands for the 10 advisories this scan raises against mistune 3.2.1: [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted].
High CVE: [GHSA redacted] uv.lock— orjson 3.11.4: [GHSA redacted] — this repo already declares orjson 3.11.9 directly, at or above the fixed 3.11.6; the vulnerable 3.11.4 is a second copy resolved for a dependency that requires an older range. Upgrade those dependents, or pin orjson in your constraints file so only one copy resolves.
High CVE: [GHSA redacted] uv.lock— protobuf 5.29.5: [GHSA redacted] — this repo already declares protobuf 5.29.6 directly, at or above the fixed 5.29.6; the vulnerable 5.29.5 is a second copy resolved for a dependency that requires an older range. Upgrade those dependents, or pin protobuf in your constraints file so only one copy resolves.
High CVE: [GHSA redacted] uv.lock— pyjwt 2.10.1: [GHSA redacted] — this repo already declares pyjwt 2.12.1 directly, at or above the fixed 2.12.0; the vulnerable 2.10.1 is a second copy resolved for a dependency that requires an older range. Upgrade those dependents, or pin pyjwt in your constraints file so only one copy resolves. This is 1 of 6 advisories with a published fix this scan raises against pyjwt 2.10.1, and their fixed versions do not agree — anything below 2.13.0 still leaves at least one of them open. Take this package to 2.13.0 or later: that is the floor for the package, not this row's target alone. This one row stands for the 7 advisories this scan raises against pyjwt 2.10.1: [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted], PYSEC-2025-183, PYSEC-2026-177.
High CVE: [GHSA redacted] requirements.txt— pyjwt 2.12.1: [GHSA redacted] — upgrade to 2.13.0. This one row stands for the 5 advisories this scan raises against pyjwt 2.12.1: [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted], PYSEC-2026-177.
High CVE: [GHSA redacted] uv.lock— python-multipart 0.0.20: [GHSA redacted] — upgrade to 0.0.30. This is 1 of 7 advisories with a published fix this scan raises against python-multipart 0.0.20, and their fixed versions do not agree — anything below 0.0.31 still leaves at least one of them open. Take this package to 0.0.31 or later: that is the floor for the package, not this row's target alone. This one row stands for the 7 advisories this scan raises against python-multipart 0.0.20: [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted], PYSEC-2026-3037, PYSEC-2026-3040, PYSEC-2026-3041.
High CVE: [GHSA redacted] requirements.txt— python-multipart 0.0.28: [GHSA redacted] — upgrade to 0.0.30. This is 1 of 4 advisories with a published fix this scan raises against python-multipart 0.0.28, and their fixed versions do not agree — anything below 0.0.31 still leaves at least one of them open. Take this package to 0.0.31 or later: that is the floor for the package, not this row's target alone. This one row stands for the 4 advisories this scan raises against python-multipart 0.0.28: [GHSA redacted], PYSEC-2026-3037, PYSEC-2026-3040, PYSEC-2026-3041.
High CVE: [GHSA redacted] uv.lock— soupsieve 2.8: [GHSA redacted] — soupsieve is not declared in this repo's manifests: it is pulled in transitively, so upgrade the dependency that requires it (or constrain soupsieve to >=2.8.4 in your constraints/requirements file). This one row stands for the 2 advisories this scan raises against soupsieve 2.8: [GHSA redacted], [GHSA redacted].
High CVE: [GHSA redacted] requirements.txt— starlette 0.49.3: [GHSA redacted] — upgrade to 1.3.1. This is 1 of 5 advisories with a published fix this scan raises against starlette 0.49.3, and their fixed versions do not agree — anything below 1.3.1 still leaves at least one of them open. Take this package to 1.3.1 or later: that is the floor for the package, not this row's target alone. (in 2 dependency files: requirements.txt, uv.lock) This one row stands for the 5 advisories this scan raises against starlette 0.49.3: [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted], PYSEC-2026-248.
High CVE: [GHSA redacted] uv.lock— tornado 6.5.5: [GHSA redacted] — tornado is not declared in this repo's manifests: it is pulled in transitively, so upgrade the dependency that requires it (or constrain tornado to >=6.5.6 in your constraints/requirements file). This is 1 of 4 advisories with a published fix this scan raises against tornado 6.5.5, and their fixed versions do not agree — anything below 6.5.7 still leaves at least one of them open. Take this package to 6.5.7 or later: that is the floor for the package, not this row's target alone. This one row stands for the 4 advisories this scan raises against tornado 6.5.5: [GHSA redacted], [GHSA redacted], [GHSA redacted], PYSEC-2026-3388.
High CVE: [GHSA redacted] uv.lock— transformers 5.0.0rc3: [GHSA redacted] — upgrade to 5.3.0. This is 1 of 3 advisories with a published fix this scan raises against transformers 5.0.0rc3, and their fixed versions do not agree — anything below 5.5.0 still leaves at least one of them open. Take this package to 5.5.0 or later: that is the floor for the package, not this row's target alone. This one row stands for the 3 advisories this scan raises against transformers 5.0.0rc3: [GHSA redacted], [GHSA redacted], PYSEC-2026-2288.
High CVE: [GHSA redacted] uv.lock— urllib3 2.6.3: [GHSA redacted] — this repo already declares urllib3 2.7.0 directly, at or above the fixed 2.7.0; the vulnerable 2.6.3 is a second copy resolved for a dependency that requires an older range. Upgrade those dependents, or pin urllib3 in your constraints file so only one copy resolves. This one row stands for the 2 advisories this scan raises against urllib3 2.6.3: [GHSA redacted], [GHSA redacted].
High CVE: [GHSA redacted] src/flock/frontend/package-lock.json— vite 7.3.3: [GHSA redacted] — this repo declares vite ^7.3.3, a range that ALREADY admits the fixed 7.3.5, so there is no manifest edit to make here. Re-resolve the lock so vite moves onto 7.3.5 or later; if the flagged 7.3.3 comes back, a dependency is pinning it — upgrade that dependent, or pin vite with an `overrides` entry so only one copy resolves. This one row stands for the 2 advisories this scan raises against vite 7.3.3: [GHSA redacted], [GHSA redacted].
High CVE: [GHSA redacted] src/flock/frontend/package-lock.json— ws 8.18.3: [GHSA redacted] — ws is not declared in this repo's manifests: it is pulled in transitively, so upgrade the dependency that requires it (or pin ws to 8.21.0 with an `overrides` entry). This is 1 of 2 advisories with a published fix this scan raises against ws 8.18.3, and their fixed versions do not agree — anything below 8.21.0 still leaves at least one of them open. Take this package to 8.21.0 or later: that is the floor for the package, not this row's target alone. This one row stands for the 2 advisories this scan raises against ws 8.18.3: [GHSA redacted], [GHSA redacted].
D38 · OSV Dependency Vulnerabilities· High vulnerability · ×5
High vulnerability: [GHSA redacted] uv.lock— cryptography 46.0.3: [GHSA redacted] — this repo declares cryptography 48.0.0, but the vulnerable 46.0.3 is a SEPARATE copy on another release line, so editing your own cryptography entry cannot move it: upgrade the dependency that pulls it in (or constrain cryptography to >=48.0.1 in your constraints/requirements file). This is 1 of 7 advisories with a published fix this scan raises against cryptography 46.0.3, and their fixed versions do not agree — anything below 46.0.7 still leaves at least one of them open. Take this package to 46.0.7 or later: that is the floor for the package, not this row's target alone. This one row stands for the 7 advisories this scan raises against cryptography 46.0.3: [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted], PYSEC-2026-35.
High vulnerability: [GHSA redacted] requirements.txt— cryptography 48.0.0: [GHSA redacted] — upgrade to 48.0.1. This one row stands for the 4 advisories this scan raises against cryptography 48.0.0: [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted].
High vulnerability: [GHSA redacted] requirements.txt— json-repair 0.59.6: [GHSA redacted] — upgrade to 0.60.1 (in 2 dependency files: requirements.txt, uv.lock)
High vulnerability: [GHSA redacted] uv.lock— jupyterlab 4.5.7: [GHSA redacted] — upgrade to 4.5.10. This is 1 of 6 advisories with a published fix this scan raises against jupyterlab 4.5.7, and their fixed versions do not agree — anything below 4.5.10 still leaves at least one of them open. Take this package to 4.5.10 or later: that is the floor for the package, not this row's target alone. This one row stands for the 6 advisories this scan raises against jupyterlab 4.5.7: [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted], [GHSA redacted].
High vulnerability: [GHSA redacted] src/flock/frontend/package-lock.json— postcss 8.5.14: [GHSA redacted] — postcss is not declared in this repo's manifests: it is pulled in transitively, so upgrade the dependency that requires it (or pin postcss to 8.5.18 with an `overrides` entry). This is 1 of 2 advisories with a published fix this scan raises against postcss 8.5.14, and their fixed versions do not agree — anything below 8.5.23 still leaves at least one of them open. Take this package to 8.5.23 or later: that is the floor for the package, not this row's target alone. This one row stands for the 2 advisories this scan raises against postcss 8.5.14: [GHSA redacted], [GHSA redacted].
Critical CVE: [GHSA redacted] uv.lock— jupyter-server 2.18.0: [GHSA redacted] — jupyter-server is not declared in this repo's manifests: it is pulled in transitively, so upgrade the dependency that requires it (or constrain jupyter-server to >=2.20.0 in your constraints/requirements file). This is 1 of 2 advisories with a published fix this scan raises against jupyter-server 2.18.0, and their fixed versions do not agree — anything below 2.20.0 still leaves at least one of them open. Take this package to 2.20.0 or later: that is the floor for the package, not this row's target alone. This one row stands for the 2 advisories this scan raises against jupyter-server 2.18.0: [GHSA redacted], PYSEC-2026-2532.
Critical CVE: [GHSA redacted] requirements.txt— litellm 1.83.14: [GHSA redacted] — upgrade to 1.84.0 (in 2 dependency files: requirements.txt, uv.lock) This one row stands for the 2 advisories this scan raises against litellm 1.83.14: [GHSA redacted], [GHSA redacted].
Critical CVE: [GHSA redacted] src/flock/frontend/package-lock.json— vitest 3.2.4: [GHSA redacted] — this repo declares vitest ^3.2.4, a range that ALREADY admits the fixed 3.2.6, so there is no manifest edit to make here. Re-resolve the lock so vitest moves onto 3.2.6 or later; if the flagged 3.2.4 comes back, a dependency is pinning it — upgrade that dependent, or pin vitest with an `overrides` entry so only one copy resolves.
D38 · OSV Dependency Vulnerabilities· Medium CVE · ×11
Medium CVE: PYSEC-2026-2132 requirements.txt— click 8.1.8: PYSEC-2026-2132 — upgrade to 8.3.3 (in 2 dependency files: requirements.txt, uv.lock)
Medium CVE: [GHSA redacted] requirements.txt— diskcache 5.6.3: [GHSA redacted] — no fixed version has been published yet. Track the advisory, and remove or replace diskcache if the exposure is not acceptable until one lands. (in 2 dependency files: requirements.txt, uv.lock)
Medium CVE: PYSEC-2025-112 requirements.txt— duckdb 1.4.1: PYSEC-2025-112 — upgrade to 1.4.2 (in 2 dependency files: requirements.txt, uv.lock)
Medium CVE: [GHSA redacted] uv.lock— idna 3.11: [GHSA redacted] — upgrade to 3.15
Medium CVE: [GHSA redacted] requirements.txt— idna 3.14: [GHSA redacted] — upgrade to 3.15
Medium CVE: [GHSA redacted] requirements.txt— pydantic-settings 2.14.1: [GHSA redacted] — upgrade to 2.14.2
Medium CVE: PYSEC-2026-2987 uv.lock— pygments 2.19.2: PYSEC-2026-2987 — this repo already declares pygments 2.20.0 directly, at or above the fixed 2.20.0; the vulnerable 2.19.2 is a second copy resolved for a dependency that requires an older range. Upgrade those dependents, or pin pygments in your constraints file so only one copy resolves.
Medium CVE: [GHSA redacted] uv.lock— pymdown-extensions 10.16.1: [GHSA redacted] — pymdown-extensions is not declared in this repo's manifests: it is pulled in transitively, so upgrade the dependency that requires it (or constrain pymdown-extensions to >=10.21.3 in your constraints/requirements file). This one row stands for the 2 advisories this scan raises against pymdown-extensions 10.16.1: [GHSA redacted], [GHSA redacted].
Medium CVE: [GHSA redacted] uv.lock— requests 2.32.5: [GHSA redacted] — this repo already declares requests 2.33.1 directly, at or above the fixed 2.33.0; the vulnerable 2.32.5 is a second copy resolved for a dependency that requires an older range. Upgrade those dependents, or pin requests in your constraints file so only one copy resolves.
Medium CVE: [GHSA redacted] uv.lock— setuptools 80.9.0: [GHSA redacted] — setuptools is not declared in this repo's manifests: it is pulled in transitively, so upgrade the dependency that requires it (or constrain setuptools to >=83.0.0 in your constraints/requirements file).
Medium CVE: [GHSA redacted] uv.lock— torch 2.9.0: [GHSA redacted] — torch is not declared in this repo's manifests: it is pulled in transitively, so upgrade the dependency that requires it (or constrain torch to >=2.9.1 in your constraints/requirements file). This is 1 of 4 advisories with a published fix this scan raises against torch 2.9.0, and their fixed versions do not agree — anything below 2.13.0 still leaves at least one of them open. Take this package to 2.13.0 or later: that is the floor for the package, not this row's target alone. This one row stands for the 5 advisories this scan raises against torch 2.9.0: [GHSA redacted], [GHSA redacted], [GHSA redacted], PYSEC-2026-139, PYSEC-2026-2286.
FileTooLong: openclaw/engine.py src/flock/integrations/openclaw/engine.py:0— FileTooLong — 992 significant lines (blank, comment-only and punctuation-only lines excluded). To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
FileTooLong: dapr/dapr_state_blackboard_store.py src/flock/storage/dapr/dapr_state_blackboard_store.py:0— FileTooLong — 846 significant lines (blank, comment-only and punctuation-only lines excluded). To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
FileTooLong: api/graph_builder.py src/flock/api/graph_builder.py:0— FileTooLong — 756 significant lines (blank, comment-only and punctuation-only lines excluded). To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
FileTooLong: core/orchestrator.py src/flock/core/orchestrator.py:0— FileTooLong — 674 significant lines (blank, comment-only and punctuation-only lines excluded). To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
FileTooLong: dspy/streaming_executor.py src/flock/engines/dspy/streaming_executor.py:0— FileTooLong — 563 significant lines (blank, comment-only and punctuation-only lines excluded). To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
FileTooLong: core/store.py src/flock/core/store.py:0— FileTooLong — 535 significant lines (blank, comment-only and punctuation-only lines excluded). To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
FileTooLong: core/agent.py src/flock/core/agent.py:0— FileTooLong — 523 significant lines (blank, comment-only and punctuation-only lines excluded). To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
Duplicated block (12 lines × 2) examples/02-patterns/visibility/01_basic_visibility.py:76— examples/02-patterns/visibility/01_basic_visibility.py:76-87 | examples/02-patterns/visibility/01_basic_visibility.py:92-104 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `examples/02-patterns/visibility/01_basic_visibility.py:76` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (12 lines × 2) examples/05-engines/potion_batch_engine.py:142— examples/05-engines/potion_batch_engine.py:142-153 | examples/06-agent-components/cheer_meter_component.py:102-114 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice. Read the line range as the matched WINDOW rather than a finished unit: at `examples/05-engines/potion_batch_engine.py:142` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. The matched lines also transfer control out of the body holding them, which cannot survive a move into a called unit unchanged: have the extracted unit return that decision and let each site act on it.
Duplicated block (12 lines × 2) src/flock/api/service.py:336— src/flock/api/service.py:336-347 | src/flock/components/server/artifacts/artifacts_component.py:152-163 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice. Read the line range as the matched WINDOW rather than a finished unit: at `src/flock/api/service.py:336` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. Note that the copies do not run to the end of the range shown: their LAST lines are different code, not the same code under different names — the matched region ends inside that line. Extract the lines above it, and read the last line of each site separately.
Duplicated block (12 lines × 2) src/flock/engines/dspy/signature_builder.py:272— src/flock/engines/dspy/signature_builder.py:272-283 | src/flock/engines/dspy/signature_builder.py:438-449 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited.
Duplicated block (12 lines × 2) src/flock/logging/trace_and_logged.py:236— src/flock/logging/trace_and_logged.py:236-247 | src/flock/logging/trace_and_logged.py:285-296 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited.
Duplicated block (12 lines × 2) src/flock/mcp/types/types.py:182— src/flock/mcp/types/types.py:182-193 | src/flock/mcp/types/types.py:269-280 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited.
Duplicated block (11 lines × 2) examples/05-engines/01_adapter_comparison.py:122— examples/05-engines/01_adapter_comparison.py:122-132 | examples/05-engines/01_adapter_comparison.py:138-148 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited.
Duplicated block (11 lines × 2) src/flock/core/store.py:269— src/flock/core/store.py:269-279 | src/flock/storage/dapr/dapr_state_blackboard_store.py:1087-1097 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice.
Duplicated block (11 lines × 2) src/flock/engines/dspy/streaming_executor.py:397— src/flock/engines/dspy/streaming_executor.py:397-407 | src/flock/integrations/openclaw/engine.py:564-574 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice. Read the line range as the matched WINDOW rather than a finished unit: at `src/flock/engines/dspy/streaming_executor.py:397` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. The matched lines also transfer control out of the body holding them, which cannot survive a move into a called unit unchanged: have the extracted unit return that decision and let each site act on it.
Duplicated block (11 lines × 2) src/flock/logging/formatters/theme_builder.py:206— src/flock/logging/formatters/theme_builder.py:206-216 | src/flock/logging/formatters/themed_formatter.py:210-225 — the copies sit in sibling files of one directory: extract the block into a single shared function in that directory and call it from each site, so a change lands once.
Duplicated block (11 lines × 2) src/flock/storage/dapr/dapr_state_blackboard_store.py:738— src/flock/storage/dapr/dapr_state_blackboard_store.py:738-748 | src/flock/storage/dapr/dapr_state_blackboard_store.py:781-791 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `src/flock/storage/dapr/dapr_state_blackboard_store.py:738` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. Note that the copies do not run to the end of the range shown: their LAST lines are different code, not the same code under different names — the matched region ends inside that line. Extract the lines above it, and read the last line of each site separately.
Duplicated block (11 lines × 2) src/flock/storage/dapr/dapr_state_blackboard_store.py:980— src/flock/storage/dapr/dapr_state_blackboard_store.py:980-990 | src/flock/storage/dapr/dapr_state_blackboard_store.py:1008-1018 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. The matched lines also transfer control out of the body holding them, which cannot survive a move into a called unit unchanged: have the extracted unit return that decision and let each site act on it.
Duplicated block (18 lines × 2) src/flock/api/graph_builder.py:880— src/flock/api/graph_builder.py:880-897 | src/flock/components/server/control/helpers.py:277-294 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice. Read the line range as the matched WINDOW rather than a finished unit: at `src/flock/api/graph_builder.py:880` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. The matched lines also transfer control out of the body holding them, which cannot survive a move into a called unit unchanged: have the extracted unit return that decision and let each site act on it.
Duplicated block (18 lines × 2) src/flock/core/orchestrator.py:684— src/flock/core/orchestrator.py:684-716 | src/flock/core/orchestrator.py:807-824 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. The matched lines also transfer control out of the body holding them, which cannot survive a move into a called unit unchanged: have the extracted unit return that decision and let each site act on it.
Duplicated block (18 lines × 2) src/flock/integrations/openclaw/engine.py:171— src/flock/integrations/openclaw/engine.py:171-188 | src/flock/integrations/openclaw/engine.py:220-237 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `src/flock/integrations/openclaw/engine.py:171` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. Note that the copies do not run to the end of the range shown: their LAST lines are different code, not the same code under different names — the matched region ends inside that line. Extract the lines above it, and read the last line of each site separately.
Duplicated block (18 lines × 2) src/flock/integrations/openclaw/streaming.py:95— src/flock/integrations/openclaw/streaming.py:95-114 | src/flock/integrations/openclaw/streaming.py:470-487 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. The matched lines also transfer control out of the body holding them, which cannot survive a move into a called unit unchanged: have the extracted unit return that decision and let each site act on it.
Duplicated block (13 lines × 2) examples/01-getting-started/15_iot_sensor_batching.py:118— examples/01-getting-started/15_iot_sensor_batching.py:118-133 | examples/01-getting-started/15_iot_sensor_batching.py:141-153 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited.
Duplicated block (13 lines × 2) examples/09-server-components/01_authentication_component.py:145— examples/09-server-components/01_authentication_component.py:145-161 | examples/09-server-components/01_authentication_component.py:302-314 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `examples/09-server-components/01_authentication_component.py:145` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. The matched lines also transfer control out of the body holding them, which cannot survive a move into a called unit unchanged: have the extracted unit return that decision and let each site act on it. Note that the copies do not run to the end of the range shown: their LAST lines are different code, not the same code under different names — the matched region ends inside that line. Extract the lines above it, and read the last line of each site separately.
Duplicated block (13 lines × 2) src/flock/api/collector.py:320— src/flock/api/collector.py:320-332 | src/flock/api/collector.py:376-388 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `src/flock/api/collector.py:320` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (13 lines × 2) src/flock/engines/dspy/streaming_executor.py:275— src/flock/engines/dspy/streaming_executor.py:275-287 | src/flock/engines/dspy/streaming_executor.py:528-540 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited.
TooManyMethods: Flock src/flock/core/orchestrator.py:69— TooManyMethods — 45 methods. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
TooManyMethods: OpenClawEngine src/flock/integrations/openclaw/engine.py:33— TooManyMethods — 36 methods. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
TooManyMethods: DaprStateBlackboardStore src/flock/storage/dapr/dapr_state_blackboard_store.py:260— TooManyMethods — 34 methods. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
Duplicated block (17 lines × 2) examples/12-dapr/postgresql_unencrypted/flock_dapr_postgresql.py:133— examples/12-dapr/postgresql_unencrypted/flock_dapr_postgresql.py:133-149 | examples/12-dapr/redis_encrypted/flock_dapr_redis.py:133-149 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice. Read the line range as the matched WINDOW rather than a finished unit: at `examples/12-dapr/postgresql_unencrypted/flock_dapr_postgresql.py:133` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (17 lines × 2) src/flock/integrations/openclaw/streaming.py:62— src/flock/integrations/openclaw/streaming.py:62-78 | src/flock/integrations/openclaw/streaming.py:439-455 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. The matched lines also transfer control out of the body holding them, which cannot survive a move into a called unit unchanged: have the extracted unit return that decision and let each site act on it.
Duplicated block (17 lines × 2) src/flock/mcp/servers/sse/flock_sse_server.py:83— src/flock/mcp/servers/sse/flock_sse_server.py:83-99 | src/flock/mcp/servers/streamable_http/flock_streamable_http_server.py:97-113 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice. Read the line range as the matched WINDOW rather than a finished unit: at `src/flock/mcp/servers/sse/flock_sse_server.py:83` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. Note that the copies do not run to the end of the range shown: their LAST lines are different code, not the same code under different names — the matched region ends inside that line. Extract the lines above it, and read the last line of each site separately.
Duplicated block (16 lines × 2) examples/03-hackathon/07_joinspec_correlation.py:151— examples/03-hackathon/07_joinspec_correlation.py:151-166 | examples/03-hackathon/07_joinspec_correlation.py:189-204 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `examples/03-hackathon/07_joinspec_correlation.py:151` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (16 lines × 2) examples/09-server-components/01_authentication_component.py:28— examples/09-server-components/01_authentication_component.py:28-45 | examples/09-server-components/01_authentication_component.py:187-202 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `examples/09-server-components/01_authentication_component.py:28` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (16 lines × 2) src/flock/logging/formatters/theme_builder.py:233— src/flock/logging/formatters/theme_builder.py:233-248 | src/flock/logging/formatters/themed_formatter.py:245-264 — the copies sit in sibling files of one directory: extract the block into a single shared function in that directory and call it from each site, so a change lands once. Read the line range as the matched WINDOW rather than a finished unit: at `src/flock/logging/formatters/theme_builder.py:233` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (10 lines × 2) examples/01-getting-started/05_mcp_and_tools.py:30— examples/01-getting-started/05_mcp_and_tools.py:30-39 | examples/01-getting-started/07_web_detective.py:28-37 — the copies sit in sibling files of one directory: extract the block into a single shared function in that directory and call it from each site, so a change lands once.
Duplicated block (10 lines × 2) src/flock/components/server/traces/trace_component.py:442— src/flock/components/server/traces/trace_component.py:442-451 | src/flock/components/server/traces/trace_component.py:541-550 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `src/flock/components/server/traces/trace_component.py:442` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (10 lines × 2) src/flock/engines/dspy/signature_builder.py:241— src/flock/engines/dspy/signature_builder.py:241-250 | src/flock/engines/dspy/signature_builder.py:385-394 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited.
Duplicated block (7 lines × 2) src/flock/api/service.py:314— src/flock/api/service.py:314-320 | src/flock/api/service.py:359-365 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `src/flock/api/service.py:314` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (7 lines × 2) src/flock/components/server/agents/agents_component.py:74— src/flock/components/server/agents/agents_component.py:74-80 | src/flock/components/server/artifacts/artifacts_component.py:98-104 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice. Read the line range as the matched WINDOW rather than a finished unit: at `src/flock/components/server/agents/agents_component.py:74` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. The matched lines also transfer control out of the body holding them, which cannot survive a move into a called unit unchanged: have the extracted unit return that decision and let each site act on it.
Duplicated block (7 lines × 2) src/flock/components/server/artifacts/artifacts_component.py:130— src/flock/components/server/artifacts/artifacts_component.py:130-136 | src/flock/components/server/artifacts/artifacts_component.py:177-183 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `src/flock/components/server/artifacts/artifacts_component.py:130` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (23 lines × 2) src/flock/api/graph_builder.py:911— src/flock/api/graph_builder.py:911-933 | src/flock/components/server/control/helpers.py:306-328 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice. Read the line range as the matched WINDOW rather than a finished unit: at `src/flock/api/graph_builder.py:911` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (23 lines × 2) src/flock/mcp/types/types.py:220— src/flock/mcp/types/types.py:220-242 | src/flock/mcp/types/types.py:307-329 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. The matched lines also transfer control out of the body holding them, which cannot survive a move into a called unit unchanged: have the extracted unit return that decision and let each site act on it.
Duplicated block (22 lines × 2) examples/09-server-components/07_agents_component.py:117— examples/09-server-components/07_agents_component.py:117-138 | examples/09-server-components/08_control_routes_component.py:68-89 — the copies sit in sibling files of one directory: extract the block into a single shared function in that directory and call it from each site, so a change lands once. Read the line range as the matched WINDOW rather than a finished unit: at `examples/09-server-components/07_agents_component.py:117` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (22 lines × 2) src/flock/agent/component_lifecycle.py:133— src/flock/agent/component_lifecycle.py:133-154 | src/flock/agent/component_lifecycle.py:173-195 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited.
Duplicated block (20 lines × 3) examples/09-server-components/04_health_component.py:103— examples/09-server-components/04_health_component.py:103-122 | examples/09-server-components/06_artifacts_component.py:80-99 | examples/09-server-components/11_tracing_component.py:107-126 — before extracting anything, compare `examples/09-server-components/06_artifacts_component.py` and `examples/09-server-components/11_tracing_component.py` as WHOLE FILES: this scan already matched 3 separate duplicated blocks between them, totalling at least 96 lines, which is the signature of one file having been copied from the other rather than of a helper waiting to be extracted. If that is what happened, the fix is to keep one copy and have the other call it (or delete it), which resolves this row and its siblings together — extracting one helper per block leaves the fork in place.
Duplicated block (20 lines × 3) examples/12-dapr/inmemory/flock_dapr_inmemory.py:109— examples/12-dapr/inmemory/flock_dapr_inmemory.py:109-129 | examples/12-dapr/postgresql_unencrypted/flock_dapr_postgresql.py:110-129 | examples/12-dapr/redis_encrypted/flock_dapr_redis.py:110-129 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere all 3 call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made 3 times. Read the line range as the matched WINDOW rather than a finished unit: at `examples/12-dapr/inmemory/flock_dapr_inmemory.py:109` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (19 lines × 2) src/flock/engines/providers/transformers_provider.py:243— src/flock/engines/providers/transformers_provider.py:243-261 | src/flock/engines/providers/transformers_provider.py:379-397 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited.
Duplicated block (19 lines × 2) src/flock/orchestrator/batch_accumulator.py:113— src/flock/orchestrator/batch_accumulator.py:113-131 | src/flock/orchestrator/batch_accumulator.py:145-169 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited.
Duplicated block (15 lines × 3) examples/12-dapr/inmemory/flock_dapr_inmemory.py:138— examples/12-dapr/inmemory/flock_dapr_inmemory.py:138-152 | examples/12-dapr/postgresql_unencrypted/flock_dapr_postgresql.py:139-153 | examples/12-dapr/redis_encrypted/flock_dapr_redis.py:139-153 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere all 3 call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made 3 times. Read the line range as the matched WINDOW rather than a finished unit: at `examples/12-dapr/inmemory/flock_dapr_inmemory.py:138` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (15 lines × 3) src/flock/engines/providers/transformers_provider.py:162— src/flock/engines/providers/transformers_provider.py:162-176 | src/flock/engines/providers/transformers_provider.py:250-264 | src/flock/engines/providers/transformers_provider.py:386-400 — all 3 copies are in the same file, so extract the block into one function there and call it from every one of those sites — resolving only two of them leaves the rest to drift apart the first time one is edited. Read the line range as the matched WINDOW rather than a finished unit: at `src/flock/engines/providers/transformers_provider.py:162` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (14 lines × 2) src/flock/api/service.py:434— src/flock/api/service.py:434-447 | src/flock/components/server/agents/agents_component.py:141-154 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice. Read the line range as the matched WINDOW rather than a finished unit: at `src/flock/api/service.py:434` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. Note that the copies do not run to the end of the range shown: their LAST lines are different code, not the same code under different names — the matched region ends inside that line. Extract the lines above it, and read the last line of each site separately.
Duplicated block (14 lines × 2) src/flock/logging/formatters/theme_builder.py:26— src/flock/logging/formatters/theme_builder.py:26-39 | src/flock/logging/formatters/themed_formatter.py:26-43 — the copies sit in sibling files of one directory: extract the block into a single shared function in that directory and call it from each site, so a change lands once.
GraphAssembler._build_agent_nodes (cyclomatic 36) src/flock/api/graph_builder.py:180— GraphAssembler._build_agent_nodes has cyclomatic complexity 36 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.
OpenClawEngine.evaluate (cyclomatic 33) src/flock/integrations/openclaw/engine.py:105— OpenClawEngine.evaluate has cyclomatic complexity 33 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.
OpenClawEngine._build_responses_payload (cyclomatic 27) src/flock/integrations/openclaw/engine.py:578— OpenClawEngine._build_responses_payload has cyclomatic complexity 27 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.
OutputProcessor.make_outputs_for_group (cyclomatic 25) src/flock/agent/output_processor.py:46— OutputProcessor.make_outputs_for_group has cyclomatic complexity 25 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.
DSPyEngine._evaluate_internal (cyclomatic 25) src/flock/engines/dspy_engine.py:240— DSPyEngine._evaluate_internal has cyclomatic complexity 25 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.
OutputUtilityComponent.on_post_evaluate (cyclomatic 24) src/flock/components/agent/output_utility.py:174— OutputUtilityComponent.on_post_evaluate has cyclomatic complexity 24 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.
DSPySignatureBuilder.prepare_signature_for_output_group (cyclomatic 24) src/flock/engines/dspy/signature_builder.py:170— DSPySignatureBuilder.prepare_signature_for_output_group has cyclomatic complexity 24 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.
TimerComponent._timer_loop (cyclomatic 20) src/flock/components/orchestrator/scheduling/timer.py:113— TimerComponent._timer_loop has cyclomatic complexity 20 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.
DSPyArtifactMaterializer.normalize_output_payload (cyclomatic 18) src/flock/engines/dspy/artifact_materializer.py:35— DSPyArtifactMaterializer.normalize_output_payload has cyclomatic complexity 18 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.
DSPyArtifactMaterializer.materialize_artifacts (cyclomatic 18) src/flock/engines/dspy/artifact_materializer.py:98— DSPyArtifactMaterializer.materialize_artifacts has cyclomatic complexity 18 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.
trace_and_logged._extract_span_attributes (cyclomatic 18) src/flock/logging/trace_and_logged.py:133— trace_and_logged._extract_span_attributes has cyclomatic complexity 18 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.
TelemetryConfig.setup_tracing (cyclomatic 17) src/flock/logging/telemetry.py:107— TelemetryConfig.setup_tracing has cyclomatic complexity 17 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.
GraphAssembler._build_logic_config_for_subscription (cyclomatic 16) src/flock/api/graph_builder.py:877— GraphAssembler._build_logic_config_for_subscription has cyclomatic complexity 16 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.
BuiltinCollectionComponent.on_collect_artifacts (cyclomatic 16) src/flock/components/orchestrator/collection.py:31— BuiltinCollectionComponent.on_collect_artifacts has cyclomatic complexity 16 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.
helpers._build_logic_config (cyclomatic 16) src/flock/components/server/control/helpers.py:249— helpers._build_logic_config has cyclomatic complexity 16 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.
Flock.get_correlation_status (cyclomatic 16) src/flock/core/orchestrator.py:312— Flock.get_correlation_status has cyclomatic complexity 16 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.
FlockMCPClient.__init__ (cyclomatic 16) src/flock/mcp/client.py:231— FlockMCPClient.__init__ has cyclomatic complexity 16 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.
GraphAssembler._build_agent_nodes (cognitive 76) src/flock/api/graph_builder.py:180— GraphAssembler._build_agent_nodes has cognitive complexity 76 (threshold 15). Drivers by points: ternaries 44, if/else 24, loops 5, boolean chains 3 (nesting depth added 41). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
OpenClawEngine.evaluate (cognitive 70) src/flock/integrations/openclaw/engine.py:105— OpenClawEngine.evaluate has cognitive complexity 70 (threshold 15). Drivers by points: if/else 53, error handling 10, boolean chains 5, loops 1, ternaries 1 (nesting depth added 35). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
OutputProcessor.make_outputs_for_group (cognitive 67) src/flock/agent/output_processor.py:46— OutputProcessor.make_outputs_for_group has cognitive complexity 67 (threshold 15). Drivers by points: if/else 45, loops 21, boolean chains 1 (nesting depth added 44). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
DSPySignatureBuilder.prepare_signature_for_output_group (cognitive 46) src/flock/engines/dspy/signature_builder.py:170— DSPySignatureBuilder.prepare_signature_for_output_group has cognitive complexity 46 (threshold 15). Drivers by points: if/else 37, loops 5, boolean chains 4 (nesting depth added 20). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
DSPyArtifactMaterializer.materialize_artifacts (cognitive 40) src/flock/engines/dspy/artifact_materializer.py:98— DSPyArtifactMaterializer.materialize_artifacts has cognitive complexity 40 (threshold 15). Drivers by points: if/else 21, error handling 11, loops 7, boolean chains 1 (nesting depth added 25). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
OpenClawEngine._build_responses_payload (cognitive 40) src/flock/integrations/openclaw/engine.py:578— OpenClawEngine._build_responses_payload has cognitive complexity 40 (threshold 15). Drivers by points: if/else 29, boolean chains 5, loops 3, ternaries 3 (nesting depth added 8). To reduce it, split the body: most of this score is breadth rather than depth — checks laid out side by side rather than stacked — so group the statements between the checks into named steps and move each step into its own function. Some of it IS depth: where a check sits inside another whose only job is to reach it, merge the two into one condition, and where an else follows a branch that already returns, drop the trailing else and let the rest of the body continue at one level.
OutputUtilityComponent.on_post_evaluate (cognitive 36) src/flock/components/agent/output_utility.py:174— OutputUtilityComponent.on_post_evaluate has cognitive complexity 36 (threshold 15). Drivers by points: if/else 21, loops 6, boolean chains 5, error handling 2, ternaries 2 (nesting depth added 11). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
DSPyEngine._evaluate_internal (cognitive 36) src/flock/engines/dspy_engine.py:240— DSPyEngine._evaluate_internal has cognitive complexity 36 (threshold 15). Drivers by points: if/else 21, boolean chains 8, ternaries 4, error handling 3 (nesting depth added 8). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
DSPyArtifactMaterializer.normalize_output_payload (cognitive 35) src/flock/engines/dspy/artifact_materializer.py:35— DSPyArtifactMaterializer.normalize_output_payload has cognitive complexity 35 (threshold 15). Drivers by points: if/else 25, loops 4, boolean chains 3, error handling 3 (nesting depth added 18). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
BuiltinCollectionComponent.on_collect_artifacts (cognitive 33) src/flock/components/orchestrator/collection.py:31— BuiltinCollectionComponent.on_collect_artifacts has cognitive complexity 33 (threshold 15). Drivers by points: if/else 28, loops 3, boolean chains 2 (nesting depth added 16). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
Flock.run_until_idle (cognitive 32) src/flock/core/orchestrator.py:599— Flock.run_until_idle has cognitive complexity 32 (threshold 15). Drivers by points: if/else 27, loops 5 (nesting depth added 18). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
trace_and_logged._extract_span_attributes (cognitive 31) src/flock/logging/trace_and_logged.py:133— trace_and_logged._extract_span_attributes has cognitive complexity 31 (threshold 15). Drivers by points: if/else 23, error handling 3, loops 3, boolean chains 2 (nesting depth added 14). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
AgentScheduler.schedule_artifact (cognitive 30) src/flock/orchestrator/scheduler.py:44— AgentScheduler.schedule_artifact has cognitive complexity 30 (threshold 15). Drivers by points: if/else 26, loops 3, boolean chains 1 (nesting depth added 17). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
TimerComponent._timer_loop (cognitive 29) src/flock/components/orchestrator/scheduling/timer.py:113— TimerComponent._timer_loop has cognitive complexity 29 (threshold 15). Drivers by points: if/else 21, boolean chains 4, error handling 2, loops 1, ternaries 1 (nesting depth added 10). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
OpenClawEngine._extract_responses_output_text (cognitive 29) src/flock/integrations/openclaw/engine.py:1195— OpenClawEngine._extract_responses_output_text has cognitive complexity 29 (threshold 15). Drivers by points: if/else 23, loops 4, boolean chains 2 (nesting depth added 16). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
Flock.run_until (cognitive 27) src/flock/core/orchestrator.py:740— Flock.run_until has cognitive complexity 27 (threshold 15). Drivers by points: if/else 26, loops 1 (nesting depth added 14). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
GraphAssembler._build_logic_config_for_subscription (cognitive 26) src/flock/api/graph_builder.py:877— GraphAssembler._build_logic_config_for_subscription has cognitive complexity 26 (threshold 15). Drivers by points: if/else 14, ternaries 10, boolean chains 2 (nesting depth added 11). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
helpers._build_logic_config (cognitive 26) src/flock/components/server/control/helpers.py:249— helpers._build_logic_config has cognitive complexity 26 (threshold 15). Drivers by points: if/else 14, ternaries 10, boolean chains 2 (nesting depth added 11). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
dapr_state_blackboard_store._build_dapr_query (cognitive 26) src/flock/storage/dapr/dapr_state_blackboard_store.py:106— dapr_state_blackboard_store._build_dapr_query has cognitive complexity 26 (threshold 15). Drivers by points: if/else 26 (nesting depth added 12). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
01_fan_out_selection.main_cli (cognitive 25) examples/02-patterns/complex-patterns/01_fan_out_selection.py:201— 01_fan_out_selection.main_cli has cognitive complexity 25 (threshold 15). Drivers by points: if/else 12, loops 7, ternaries 6 (nesting depth added 12). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
OpenClawEngine._materialize_artifacts_for_output_group (cognitive 24) src/flock/integrations/openclaw/engine.py:965— OpenClawEngine._materialize_artifacts_for_output_group has cognitive complexity 24 (threshold 15). Drivers by points: if/else 17, loops 7 (nesting depth added 12). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
Flock.get_correlation_status (cognitive 23) src/flock/core/orchestrator.py:312— Flock.get_correlation_status has cognitive complexity 23 (threshold 15). Drivers by points: if/else 14, loops 6, boolean chains 3 (nesting depth added 9). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
FlockMCPClient.__init__ (cognitive 23) src/flock/mcp/client.py:231— FlockMCPClient.__init__ has cognitive complexity 23 (threshold 15). Drivers by points: if/else 21, boolean chains 2 (nesting depth added 4). To reduce it, split the body: most of this score is breadth rather than depth — checks laid out side by side rather than stacked — so group the statements between the checks into named steps and move each step into its own function. Some of it IS depth: where a check sits inside another whose only job is to reach it, merge the two into one condition, and where an else follows a branch that already returns, drop the trailing else and let the rest of the body continue at one level.
MockStore.query_artifacts (cognitive 23) tests/test_context_provider.py:35— MockStore.query_artifacts has cognitive complexity 23 (threshold 15). Drivers by points: if/else 22, boolean chains 1 (nesting depth added 12). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
DSPySignatureBuilder.prepare_execution_payload_for_output_group (cognitive 22) src/flock/engines/dspy/signature_builder.py:345— DSPySignatureBuilder.prepare_execution_payload_for_output_group has cognitive complexity 22 (threshold 15). Drivers by points: if/else 13, loops 4, ternaries 4, boolean chains 1 (nesting depth added 12). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
trace_and_logged._serialize_value (cognitive 22) src/flock/logging/trace_and_logged.py:54— trace_and_logged._serialize_value has cognitive complexity 22 (threshold 15). Drivers by points: if/else 14, error handling 6, loops 2 (nesting depth added 8). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
SemanticContextProvider.get_context (cognitive 21) src/flock/semantic/context_provider.py:81— SemanticContextProvider.get_context has cognitive complexity 21 (threshold 15). Drivers by points: if/else 14, error handling 5, boolean chains 1, loops 1 (nesting depth added 6). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
MCPIntegration.configure_servers (cognitive 20) src/flock/agent/mcp_integration.py:109— MCPIntegration.configure_servers has cognitive complexity 20 (threshold 15). Drivers by points: if/else 14, boolean chains 2, loops 2, ternaries 2 (nesting depth added 10). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
GraphAssembler._derive_blackboard_edges (cognitive 20) src/flock/api/graph_builder.py:683— GraphAssembler._derive_blackboard_edges has cognitive complexity 20 (threshold 15). Drivers by points: if/else 12, loops 7, boolean chains 1 (nesting depth added 10). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
helpers._compute_agent_status (cognitive 20) src/flock/components/server/control/helpers.py:215— helpers._compute_agent_status has cognitive complexity 20 (threshold 15). Drivers by points: if/else 18, boolean chains 1, loops 1 (nesting depth added 12). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
themed_formatter.create_rich_renderable (cognitive 20) src/flock/logging/formatters/themed_formatter.py:238— themed_formatter.create_rich_renderable has cognitive complexity 20 (threshold 15). Drivers by points: if/else 9, loops 5, ternaries 4, boolean chains 2 (nesting depth added 7). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
VersionBumper.bump_versions (cognitive 19) scripts/bump_version.py:201— VersionBumper.bump_versions has cognitive complexity 19 (threshold 15). Drivers by points: if/else 16, boolean chains 2, ternaries 1 (nesting depth added 1). To reduce it, split the body: this score is breadth rather than depth — many checks laid out side by side rather than nested inside one another, so inverting conditions into early returns has nothing left to flatten. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.
GraphAssembler._apply_pending_label_offsets (cognitive 19) src/flock/api/graph_builder.py:504— GraphAssembler._apply_pending_label_offsets has cognitive complexity 19 (threshold 15). Drivers by points: if/else 11, loops 8 (nesting depth added 9). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
DaprStateBlackboardStore._query_via_dapr_api (cognitive 19) src/flock/storage/dapr/dapr_state_blackboard_store.py:469— DaprStateBlackboardStore._query_via_dapr_api has cognitive complexity 19 (threshold 15). Drivers by points: if/else 12, error handling 3, loops 3, boolean chains 1 (nesting depth added 8). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
helpers._get_correlation_groups (cognitive 18) src/flock/components/server/control/helpers.py:16— helpers._get_correlation_groups has cognitive complexity 18 (threshold 15). Drivers by points: if/else 13, ternaries 4, loops 1 (nesting depth added 8). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
theme_builder.create_rich_renderable (cognitive 18) src/flock/logging/formatters/theme_builder.py:227— theme_builder.create_rich_renderable has cognitive complexity 18 (threshold 15). Drivers by points: if/else 8, loops 5, ternaries 4, boolean chains 1 (nesting depth added 7). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
TelemetryConfig.setup_tracing (cognitive 18) src/flock/logging/telemetry.py:107— TelemetryConfig.setup_tracing has cognitive complexity 18 (threshold 15). Drivers by points: if/else 13, boolean chains 4, loops 1 (nesting depth added 2). To reduce it, split the body: most of this score is breadth rather than depth — checks laid out side by side rather than stacked — so group the statements between the checks into named steps and move each step into its own function. Some of it IS depth: where a check sits inside another whose only job is to reach it, merge the two into one condition, and where an else follows a branch that already returns, drop the trailing else and let the rest of the body continue at one level.
FlockStreamableHttpClient.create_transport (cognitive 18) src/flock/mcp/servers/streamable_http/flock_streamable_http_server.py:67— FlockStreamableHttpClient.create_transport has cognitive complexity 18 (threshold 15). Drivers by points: if/else 17, boolean chains 1 (nesting depth added 8). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
LoggingUtility._consume_stream (cognitive 18) src/flock/utils/utilities.py:263— LoggingUtility._consume_stream has cognitive complexity 18 (threshold 15). Drivers by points: if/else 10, boolean chains 4, ternaries 3, loops 1 (nesting depth added 6). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
check_version_bump.main (cognitive 17) scripts/check_version_bump.py:103— check_version_bump.main has cognitive complexity 17 (threshold 15). Drivers by points: if/else 11, boolean chains 3, loops 3 (nesting depth added 4). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
GuardComponent._extract_context_documents (cognitive 17) src/flock/components/agent/guard.py:185— GuardComponent._extract_context_documents has cognitive complexity 17 (threshold 15). Drivers by points: if/else 10, loops 7 (nesting depth added 11). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
TimerComponent._wait_for_next_fire (cognitive 17) src/flock/components/orchestrator/scheduling/timer.py:305— TimerComponent._wait_for_next_fire has cognitive complexity 17 (threshold 15). Drivers by points: if/else 14, ternaries 3 (nesting depth added 10). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
DSPyArtifactMaterializer.select_output_payload (cognitive 17) src/flock/engines/dspy/artifact_materializer.py:223— DSPyArtifactMaterializer.select_output_payload has cognitive complexity 17 (threshold 15). Drivers by points: if/else 12, ternaries 4, loops 1 (nesting depth added 10). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
OpenClawEngine._extract_error_message (cognitive 17) src/flock/integrations/openclaw/engine.py:1298— OpenClawEngine._extract_error_message has cognitive complexity 17 (threshold 15). Drivers by points: if/else 10, loops 5, boolean chains 1, error handling 1 (nesting depth added 9). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
OpenClawSSEDispatcher._extract_completed_text (cognitive 17) src/flock/integrations/openclaw/streaming.py:246— OpenClawSSEDispatcher._extract_completed_text has cognitive complexity 17 (threshold 15). Drivers by points: if/else 14, loops 3 (nesting depth added 9). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
ArtifactManager.publish (cognitive 17) src/flock/orchestrator/artifact_manager.py:47— ArtifactManager.publish has cognitive complexity 17 (threshold 15). Drivers by points: if/else 12, boolean chains 5 (nesting depth added 4). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
DaprStateBlackboardStore._query_via_index_scan (cognitive 17) src/flock/storage/dapr/dapr_state_blackboard_store.py:518— DaprStateBlackboardStore._query_via_index_scan has cognitive complexity 17 (threshold 15). Drivers by points: if/else 8, loops 5, boolean chains 2, error handling 2 (nesting depth added 4). To reduce it, split the body: this score is breadth rather than depth — many checks laid out side by side rather than nested inside one another, so inverting conditions into early returns has nothing left to flatten. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.
GraphAssembler._build_pending_join_edges (cognitive 16) src/flock/api/graph_builder.py:543— GraphAssembler._build_pending_join_edges has cognitive complexity 16 (threshold 15). Drivers by points: if/else 9, loops 6, boolean chains 1 (nesting depth added 8). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
TimerComponent._calculate_next_fire_time (cognitive 16) src/flock/components/orchestrator/scheduling/timer.py:260— TimerComponent._calculate_next_fire_time has cognitive complexity 16 (threshold 15). Drivers by points: if/else 9, ternaries 7 (nesting depth added 8). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
helpers._get_batch_state (cognitive 16) src/flock/components/server/control/helpers.py:113— helpers._get_batch_state has cognitive complexity 16 (threshold 15). Drivers by points: if/else 10, ternaries 4, boolean chains 2 (nesting depth added 3). To reduce it, split the body: most of this score is breadth rather than depth — checks laid out side by side rather than stacked — so group the statements between the checks into named steps and move each step into its own function. Some of it IS depth: where a check sits inside another whose only job is to reach it, merge the two into one condition, and where an else follows a branch that already returns, drop the trailing else and let the rest of the body continue at one level.
Flock._run_initialize (cognitive 16) src/flock/core/orchestrator.py:1135— Flock._run_initialize has cognitive complexity 16 (threshold 15). Drivers by points: if/else 10, boolean chains 4, loops 2 (nesting depth added 7). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
Subscription._matches_text_predicates (cognitive 16) src/flock/core/subscription.py:302— Subscription._matches_text_predicates has cognitive complexity 16 (threshold 15). Drivers by points: if/else 9, error handling 4, boolean chains 2, loops 1 (nesting depth added 4). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
OpenClawSSEConsumer._iter_frames (cognitive 16) src/flock/integrations/openclaw/streaming.py:431— OpenClawSSEConsumer._iter_frames has cognitive complexity 16 (threshold 15). Drivers by points: if/else 12, error handling 3, loops 1 (nesting depth added 8). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
streaming.parse_sse_lines (cognitive 16) src/flock/integrations/openclaw/streaming.py:49— streaming.parse_sse_lines has cognitive complexity 16 (threshold 15). Drivers by points: if/else 12, error handling 3, loops 1 (nesting depth added 8). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
auto_trace._parse_trace_filters (cognitive 16) src/flock/logging/auto_trace.py:21— auto_trace._parse_trace_filters has cognitive complexity 16 (threshold 15). Drivers by points: if/else 12, error handling 4 (nesting depth added 8). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
FlockMCPConfiguration.from_dict (cognitive 16) src/flock/mcp/config.py:371— FlockMCPConfiguration.from_dict has cognitive complexity 16 (threshold 15). Drivers by points: error handling 8, if/else 8 (nesting depth added 4). To reduce it, split the body: this score is breadth rather than depth — many checks laid out side by side rather than nested inside one another, so inverting conditions into early returns has nothing left to flatten. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.
FlockSSEClient.create_transport (cognitive 16) src/flock/mcp/servers/sse/flock_sse_server.py:60— FlockSSEClient.create_transport has cognitive complexity 16 (threshold 15). Drivers by points: if/else 15, boolean chains 1 (nesting depth added 7). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
Unpinned build actions — CI references GitHub Actions by a floating ref (@main / @tag) rather than a pinned commit SHA, weakening build integrity. 11 floating ref(s) across 3 workflow file(s). Each floating ref is itemized at file:line by the SAST (D29) lens.
D36 · Supply-chain Provenance & Signing· PR-triggered workflow without a permissions block · ×1
PR-triggered workflow without a permissions block — 1 workflow(s) triggered by pull_request declare no `permissions:` block (quality.yml) and so run with the repository's default GITHUB_TOKEN scope, while 2 sibling workflows in the same repository are already scoped. Pull-request runs build the least-trusted code in the repository; give each of these workflows its own least-privilege block — `permissions: {contents: read}` at the top of the workflow, widened per job only where a job genuinely writes.
D36 · Supply-chain Provenance & Signing· Secret passed as a command-line argument · ×1
Secret passed as a command-line argument — 1 CI command(s) pass a credential as a bare command-line argument, where it is visible in the runner's process table to any other process on the host (and to anything that logs a command line): deploy-whiteduck-pypi.yml: uv publish --token ${{ secrets.PYPI_API_TOKEN }}. Pass the credential through the environment instead (an `env:` mapping on the step, read by the tool from its own variable) or on stdin, so it never appears in an argument vector.
D38 · OSV Dependency Vulnerabilities· Medium vulnerability · ×1
Medium vulnerability: [GHSA redacted] uv.lock— bleach 6.3.0: [GHSA redacted] — no fixed version has been published yet. Track the advisory; bleach is not declared in this repo's manifests: it is pulled in transitively, so the action is on the dependency that requires it — upgrade or replace that dependent. This one row stands for the 3 advisories this scan raises against bleach 6.3.0: [GHSA redacted], [GHSA redacted], [GHSA redacted].
Duplicated block (88 lines × 2) src/flock/logging/formatters/theme_builder.py:101— src/flock/logging/formatters/theme_builder.py:101-188 | src/flock/logging/formatters/themed_formatter.py:94-185 — the copies sit in sibling files of one directory: extract the block into a single shared function in that directory and call it from each site, so a change lands once. The matched lines also transfer control out of the body holding them, which cannot survive a move into a called unit unchanged: have the extracted unit return that decision and let each site act on it.
Duplicated block (26 lines × 3) examples/09-server-components/05_websocket_component.py:83— examples/09-server-components/05_websocket_component.py:83-123 | examples/09-server-components/06_artifacts_component.py:87-113 | examples/09-server-components/11_tracing_component.py:114-139 — before extracting anything, compare `examples/09-server-components/06_artifacts_component.py` and `examples/09-server-components/11_tracing_component.py` as WHOLE FILES: this scan already matched 3 separate duplicated blocks between them, totalling at least 96 lines, which is the signature of one file having been copied from the other rather than of a helper waiting to be extracted. If that is what happened, the fix is to keep one copy and have the other call it (or delete it), which resolves this row and its siblings together — extracting one helper per block leaves the fork in place.
Duplicated block (22 lines × 4) examples/09-server-components/06_artifacts_component.py:124— examples/09-server-components/06_artifacts_component.py:124-145 | examples/09-server-components/08_control_routes_component.py:101-122 | examples/09-server-components/10_themes_component.py:102-136 | examples/09-server-components/11_tracing_component.py:150-184 — before extracting anything, compare `examples/09-server-components/06_artifacts_component.py` and `examples/09-server-components/11_tracing_component.py` as WHOLE FILES: this scan already matched 3 separate duplicated blocks between them, totalling at least 96 lines, which is the signature of one file having been copied from the other rather than of a helper waiting to be extracted. If that is what happened, the fix is to keep one copy and have the other call it (or delete it), which resolves this row and its siblings together — extracting one helper per block leaves the fork in place. Read the line range as the matched WINDOW rather than a finished unit: at `examples/09-server-components/08_control_routes_component.py:101` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (21 lines × 2) src/flock/engines/providers/transformers_provider.py:292— src/flock/engines/providers/transformers_provider.py:292-313 | src/flock/engines/providers/transformers_provider.py:453-473 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited.
Duplicated block (15 lines × 2) src/flock/orchestrator/server_manager.py:256— src/flock/orchestrator/server_manager.py:256-273 | src/flock/orchestrator/server_manager.py:372-386 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `src/flock/orchestrator/server_manager.py:256` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (9 lines × 2) src/flock/components/agent/guard.py:172— src/flock/components/agent/guard.py:172-180 | src/flock/components/agent/guard.py:203-211 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited.
Duplicated block (8 lines × 2) src/flock/api/graph_builder.py:431— src/flock/api/graph_builder.py:431-438 | src/flock/api/graph_builder.py:719-726 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `src/flock/api/graph_builder.py:431` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (6 lines × 3) src/flock/logging/formatters/theme_builder.py:272— src/flock/logging/formatters/theme_builder.py:272-277 | src/flock/logging/formatters/themed_formatter.py:288-293 | src/flock/logging/formatters/themed_formatter.py:453-460 — there are 3 copies across 2 file(s) — more copies than files, so at least one file holds the block twice. Extract it once into a single shared function every call site can reach and call it from all 3 sites; resolving a subset leaves the remainder to drift apart. Read the line range as the matched WINDOW rather than a finished unit: at `src/flock/logging/formatters/theme_builder.py:272` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. Note that the copies do not run to the end of the range shown: their LAST lines are different code, not the same code under different names — the matched region ends inside that line. Extract the lines above it, and read the last line of each site separately.
Duplicated block (6 lines × 2) src/flock/logging/formatters/theme_builder.py:281— src/flock/logging/formatters/theme_builder.py:281-286 | src/flock/logging/formatters/themed_formatter.py:301-307 — the copies sit in sibling files of one directory: extract the block into a single shared function in that directory and call it from each site, so a change lands once. Read the line range as the matched WINDOW rather than a finished unit: at `src/flock/logging/formatters/theme_builder.py:281` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. Note that the copies do not run to the end of the range shown: their LAST lines are different code, not the same code under different names — the matched region ends inside that line. Extract the lines above it, and read the last line of each site separately.
Duplicated block (5 lines × 4) src/flock/api/service.py:365— src/flock/api/service.py:365-369 | src/flock/api/service.py:453-457 | src/flock/components/server/agents/agents_component.py:163-167 | src/flock/components/server/artifacts/artifacts_component.py:183-187 — there are 4 copies across 3 file(s) — more copies than files, so at least one file holds the block twice. Extract it once into a single shared function every call site can reach and call it from all 4 sites; resolving a subset leaves the remainder to drift apart. Read the line range as the matched WINDOW rather than a finished unit: at `src/flock/api/service.py:365` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. Note that the copies do not run to the end of the range shown: their LAST lines are different code, not the same code under different names — the matched region ends inside that line. Extract the lines above it, and read the last line of each site separately.
Duplicated block (5 lines × 3) src/flock/components/server/agents/agents_component.py:160— src/flock/components/server/agents/agents_component.py:160-164 | src/flock/components/server/artifacts/artifacts_component.py:133-137 | src/flock/components/server/artifacts/artifacts_component.py:180-184 — there are 3 copies across 2 file(s) — more copies than files, so at least one file holds the block twice. Extract it once into a single shared function every call site can reach and call it from all 3 sites; resolving a subset leaves the remainder to drift apart.
Duplicated block (5 lines × 2) examples/11-openclaw/05_competitive_intelligence.py:582— examples/11-openclaw/05_competitive_intelligence.py:582-586 | examples/11-openclaw/06_fast_orchestration_smoke.py:187-191 — the copies sit in sibling files of one directory: extract the block into a single shared function in that directory and call it from each site, so a change lands once.
Off-boarding risk: anonymized user #1 — If anonymized user #1 becomes unavailable, 43 significant file(s) lose their only recent owner: src/flock/frontend/src/components/modules/TraceModuleJaeger.tsx, src/flock/integrations/openclaw/engine.py, src/flock/frontend/src/components/graph/GraphCanvas.tsx, src/flock/core/conditions.py, src/flock/frontend/src/services/websocket.ts, src/flock/logging/logging.py, src/flock/logging/formatters/themed_formatter.py, src/flock/frontend/src/components/controls/PublishControl.tsx (+35 more). Pair on, review, or document these before any departure.
Off-boarding risk: anonymized user #2 — If anonymized user #2 becomes unavailable, 16 significant file(s) lose their only recent owner: src/flock/components/server/traces/trace_component.py, src/flock/api/collector.py, src/flock/api/websocket.py, src/flock/components/server/middleware/middleware_component.py, src/flock/components/server/cors/cors_component.py, src/flock/components/server/agents/agents_component.py, src/flock/api/base_service.py, src/flock/components/server/base.py (+8 more). Pair on, review, or document these before any departure.
D11 · Test Reliability· Test reliability not included · ×1
Test reliability not included — Test source is present (.py, .tsx, .ts) but the built-in reliability runner does not support this repository's ecosystem, so flakiness couldn't be assessed. Not scored — this is a gap in the analyzer's language coverage, not a finding about this repository.
D19 · Documentation Quality· The README lacks an overview of the project's main features (Flock vs Beads) so a reader can tell which repo serves which purpose. · ×1
The README lacks an overview of the project's main features (Flock vs Beads) so a reader can tell which repo serves which purpose. README.md— Add a one-line summary stating that Flock is AI-native orchestration and Beads is Git-native issue tracking, so readers know where to find each.
D28 · Secrets (history)· Rotate the exposed credentials · ×1
Rotate the exposed credentials — git history can't be un-committed — Some of these secrets are in git HISTORY: deleting the file does not remove them (the commit persists on every clone, fork and backup). The remediation is to ROTATE each historically-exposed credential and treat it as compromised — not to delete the file. Rewriting history is disruptive and unreliable across existing forks. (Working-tree-only secrets — no commit — can instead be removed from the file and moved to a secret store.) Every location above sits inside a test/fixture/sample tree, so there may be no live credential to revoke — in that case the performable actions are different ones: confirm each value was never reused outside the tests (a fixture key shared with a staging or demo environment IS a live credential and must be rotated), generate this material at test time instead of committing it so the next one cannot be mistaken for a real leak, and record the deliberate exposure where a reader of the file will see it. Rotate anything that fails the first check.
D34 · Knowledge Freshness· Further orphaned files (smaller) · ×1
Further orphaned files (smaller) — 1 of 175 analysed file(s) have no living knowledge left — their last meaningful change has decayed away, so if one breaks, no one currently understands it (counted over production source files of roughly 100 lines or more, excluding tests, vendored, generated and example/demo trees, largest first). None is large enough to earn a read-through of its own, so this row stands in for the per-file rows rather than raising one each — largest first: src/flock/engines/auth/azure.py. Attach the read to the next change that touches one of them: have a second person review that change, and leave behind a short comment or test recording what the file is for, so the knowledge comes back at the cost of a change you were making anyway.
No build provenance — No SLSA provenance generation or build attestation found in CI — nothing binds a released artifact to the build that produced it, so a consumer cannot tell your artifact from a substituted one. On GitHub Actions, `actions/attest-build-provenance` (or slsa-github-generator) emits one from the job's own OIDC identity; elsewhere, run `cosign attest` over the released artifact from the release pipeline and publish the attestation beside it.
No artifact signing — No artifact signing found in CI — sign your released artifacts with whatever your ecosystem ships (a GPG/minisign detached signature — or `cosign sign-blob` — over the release archives, or over a checksum file published alongside them, PEP 740 attestations via `pypa/gh-action-pypi-publish` under PyPI Trusted Publishing (OIDC) for wheels/sdists) so consumers can verify what you built.
D36 · Supply-chain Provenance & Signing· No SBOM · ×1
No SBOM — No SBOM generation or committed SBOM found — produce one with what your ecosystem ships (`cyclonedx-py` over the resolved Python environment/lockfile, `syft` (or `anchore/sbom-action` in CI) over the source tree or released image). Publish it as a release asset (`*.spdx.json` / `*.cdx.json`) so consumers can see what they are installing.
Low CVE: [GHSA redacted] src/flock/frontend/package-lock.json— @babel/core 7.28.4: [GHSA redacted] — @babel/core is not declared in this repo's manifests: it is pulled in transitively, so upgrade the dependency that requires it (or pin @babel/core to 7.29.6 with an `overrides` entry).
Low vulnerability: [GHSA redacted] src/flock/frontend/package-lock.json— esbuild 0.27.7: [GHSA redacted] — esbuild is not declared in this repo's manifests: it is pulled in transitively, so upgrade the dependency that requires it (or pin esbuild to 0.28.1 with an `overrides` entry).
Coverage not included — suite not readable by the collector — Coverage NOT READ here — but this repository measures it: a coverage step in CI (`pytest --cov=src/flock --cov-branch --cov-report=xml --cov-r…`) shows that coverage is collected and tracked in your own CI. The built-in collector has no runner for this ecosystem (.py, .tsx, .ts), so the analyzer could not read the number — a gap in the analyzer's language coverage, not an unmeasured repo. Not scored. To have the real number read, produce a coverage report in a standard format (`coverage run -m pytest` then `coverage xml`, or lcov — `vitest --coverage`, `jest --coverage`, `bun test --coverage --coverage-reporter=lcov`, or `nyc`) into the repo working tree before the scan — a CI step is the usual place, since the artefact is commonly gitignored.
Info — 2 finding(s)
D12 · Dependency Hygiene· Dependency hygiene not measured · ×1
Dependency hygiene not measured — dependency manifest found but not parsed for hygiene — This repository's dependency manifest (a Python pyproject.toml/requirements.txt (pip/uv/Poetry)) was found, but this pass cannot parse it for hygiene, so no package was assessed. Zero packages read is NOT a clean dependency tree, so this is NOT SCORED — a gap in the analyzer, not a verdict about this repository. This row is about dependency HYGIENE — outdated, deprecated or unmaintained direct dependencies; known CVEs in the same dependency graph are a separate question, reported under D38 wherever the manifest is OSV-readable.
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.
disclosure: not applicable — No vulnerability-disclosure policy file found (SECURITY.md/.markdown/.rst/.txt at root or under .github/.forgejo/.gitea/docs, .well-known/security.txt). A coordinated-disclosure policy may live off-repo, so this is not evidenced rather than failed.
runtime-hardening: not applicable — No Kubernetes/orchestration workloads found in the repository manifests; network egress policy is a cluster-native control that may live at the platform/firewall layer, so there is nothing to assess here.
runtime-hardening: not applicable — No Kubernetes/orchestration workloads found in the repository manifests; seccomp/AppArmor/SELinux confinement is a workload-level control, so there is nothing to assess here.
runtime-hardening: not applicable — No Kubernetes/orchestration workloads found in the repository manifests; runtime threat-detection and admission-control policy are cluster-level controls, so there is nothing to assess here.
0
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Run 019fcf3e-1973-7892-ae38-7386d1fab3c5 · every finding is also locatable in findings.md, and the complete scoring record (with exit codes + durations) in sidecar.json.
Issues: 27 · Warnings: 155 · Recommendations: 12 · Info: 2 — Appendix A · all findings · full markdown report.
Generated by Watchdog — deterministic code-health analysis. 05-08-2026 @ 00:06 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.