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Ztein/figmark

https://github.com/Ztein/figmark · scanned 2026-06-16 01:13 UTC (2 months, 1 week ago)

25 raw signals (0 security + 25 graph)

UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 2 months, 1 week ago · v1 · 21 actionable findings from 1 signal source. 4 repeated signals grouped for readability. Security checks, system graph analysis, and verified AI-agent feedback are merged into one review queue.

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Scan summary Repository scanned at 85.6/100 with 88.9% coverage. It contains 525 nodes across 4 cross-layer flows, written primarily in mixed languages. Engine surfaced 25 findings — concentrated in quality (13), software (5), cicd (3). Risk profile is low: 0 critical, 0 high, 5 medium. Recommended next step: open the quality layer findings first — that's where the highest-impact wins live.

Showing 17 of 21 actionable findings. 25 raw detector signals were grouped into reader-sized issues. Click TP / FP to vote on a finding's accuracy — votes adjust the confidence weighting and improve detection across the platform.

medium System graph quality Placeholder conf 1.00 Critical user flow still appears backed by mock or placeholder data
A payment/auth/admin/order/billing-style flow contains mock, fake, TODO, dummy, or placeholder markers in runtime source. In the Fable corpus this is a high-leverage completeness smell: the app can look finished while the money, identity, or tenant flow is still scaffolded.
Mock dataCritical flowGenerated repo pattern
medium System graph cicd CI/CD security conf 1.00 3 occurrences GitHub Actions workflow grants broad write permissions
CI tokens with write permissions increase blast radius when an action, dependency, or PR workflow is compromised. Prefer job-level least-privilege permissions.
3 files, 3 locations
.github/workflows/automerge.yml
.github/workflows/release.yml
.github/workflows/security.yml
CI/CD securitySupply chainGithub actions
medium System graph network Security conf 1.00 Privileged port 30 in use
Port 30 is privileged (<1024). Make sure the service runs with the right caps or front it with a non-privileged port via a load balancer.
.github/workflows/codeql.yml Ports
low System graph quality Integrity conf 1.00 8 env vars used in code but missing from .env.example
Drift between code and config docs. The first few: `FIGMARK_CONFIG_PATH`, `FIGMARK_HOST`, `FIGMARK_LOG_LEVEL`, `FIGMARK_MAX_CONCURRENT_JOBS`, `FIGMARK_MAX_UPLOAD_BYTES`, `FIGMARK_PORT`, `FIGMARK_REQUEST_TIMEOUT_SECONDS`, `FIGMARK_WORK_DIR`. Add them (with a placeholder/comment) to .env.example so o…
config drift
low System graph hardware Coverage conf 1.00 Containers defined but no K8s/orchestration manifest found
Repo has Dockerfiles/compose but no Kubernetes/Nomad manifests. If the target deployment is K8s, the manifests may live in a separate ops repo.
Deployment
low System graph quality Debug conf 1.00 Debug logging residue appears in source files
Found 33 console/debugger/print-style debug statements in non-test source. This is a common fast-generation residue before production cleanup.
CleanupRepo hardeningGenerated repo pattern
low System graph quality Integrity conf 1.00 3 occurrences Near-duplicate function bodies in 2 places
Functions with the same first-5-line body hash: scripts/extract_diagrams_F.py:find, src/figmark/diagrams.py:find This is *the* AI-coder failure mode (4× more duplication in vibe-coded repos — see https://jw.hn/ai-code-hygiene). Consolidate or document why they're separate.
3 occurrences
repo-level (3 hits)
duplicatesduplication
low System graph quality Integrity conf 1.00 Old/deprecated-named symbol `test_pipeline_annotate_pdf_produces_annotated_copy` in tests/test_annotate.py:4
Names with suffixes like `_old`, `_v1`, `_deprecated` usually indicate replaced-but-not-removed code (typical AI-coder leftover). Confirm and delete, or rename if it's the active version.
old markerDead code
low System graph quality Integrity conf 1.00 Old/deprecated-named symbol `test_pipeline_annotate_pdf_produces_annotated_copy` in tests/test_pipeline.py:246
Names with suffixes like `_old`, `_v1`, `_deprecated` usually indicate replaced-but-not-removed code (typical AI-coder leftover). Confirm and delete, or rename if it's the active version.
old markerDead code
low System graph software Dead code conf 1.00 Possibly dead Python function: loud
No callers detected by AST scan in this repo. Could be exported for external callers or a framework handler.
src/figmark/pipeline.py:75
low System graph software Dead code conf 1.00 Possibly dead Python function: run_describe
No callers detected by AST scan in this repo. Could be exported for external callers or a framework handler.
src/figmark/pipeline.py:142
low System graph software Dead code conf 1.00 Possibly dead Python function: run_one
No callers detected by AST scan in this repo. Could be exported for external callers or a framework handler.
examples/run_eval.py:41
low System graph software Dead code conf 1.00 Possibly dead Python function: store
No callers detected by AST scan in this repo. Could be exported for external callers or a framework handler.
src/figmark/pipeline.py:153
low System graph software Dead code conf 1.00 Possibly dead Python function: worker
No callers detected by AST scan in this repo. Could be exported for external callers or a framework handler.
src/figmark/parallel.py:137
low System graph quality Provenance conf 1.00 Shallow git history limits provenance confidence
The repository is a shallow clone. Origin/evolution analysis cannot distinguish fresh generation, imported legacy code, or long-lived human code with high confidence.
Git historyGenerated repo pattern
low System graph quality Integrity conf 1.00 Stub function `_noop` (body is just `pass`/`return`) — src/figmark/pipeline.py:81
Likely an AI scaffold that was never filled in. Remove or implement.
Empty handlerDead code
low System graph api Wiring conf 1.00 Unused endpoint: POST /v1/convert
`src/figmark/api.py` declares `POST /v1/convert` but no frontend code we scanned calls it. This is fine if the endpoint serves external clients (mobile app, third-party, server-side webhooks). Otherwise it's dead code — consider removing or documenting who consumes it.
Unused endpoint
For AI agents: Voting guide (TP/FP) MCP manifest Stdio wrapper SARIF Integrate Findings queue Vote TP/FP on findings to calibrate the engine.
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