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riponcm/projectmem

https://github.com/riponcm/projectmem · scanned 2026-06-15 23:51 UTC (2 months, 3 weeks ago)

20 raw signals (2 security + 18 graph)

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Complete repo analysis

Last scanned 2 months, 3 weeks ago · v1 · 19 actionable findings from 2 signal sources. 1 repeated signal grouped for readability. Security checks, system graph analysis, and verified AI-agent feedback are merged into one review queue.

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88.9% cov · 17 findings

Severity distribution — click a segment to filter

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Severity: Critical 0 High 1 Medium 4 Low 6 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 2 System graph 17 Crowd 0 Layer: Quality 16 Software 1 Frontend 1 Cicd 1

Exclude dismissed / FP Exclude test files

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Scan summary Repository scanned at 99.3/100 with 88.9% coverage. It contains 396 nodes across 0 cross-layer flows, written primarily in mixed languages. Engine surfaced 18 findings — concentrated in quality (15), software (1), frontend (1). Risk profile is low: 0 critical, 0 high, 3 medium. Recommended next step: open the quality layer findings first — that's where the highest-impact wins live.

Showing 11 of 19 actionable findings. 20 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.

high Security checks quality Practices conf 0.84 Foundry mined bad chains: riponcm/projectmem

Comment chain pattern product: bad_chains Repo: riponcm/projectmem Thread: riponcm/projectmem#2 Outcome: not_resolved_or_not_observed Thread label: thread_has_human_issue_without_fix_context Source graph label: source_artifact_without_verification_graph Reasons: source_graph_has_real_artifacts, lin…

medium Security checks quality Practices conf 0.70 Foundry mined unresolved feedback: riponcm/projectmem

Graph query export: Human feedback without linked fix evidence Query id: unresolved_feedback Query type: motif_query Intent: Negative/unresolved examples that should not be hallucinated into fixes. Motif: unlinked_feedback_needs_evidence Training usage: negative_or_unresolved Graph gold label: need…

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 No CI/CD pipelines detected

No GitHub Actions, GitLab CI, or CircleCI configs found. Without CI you can't gate deploys on tests/lints.

CI/CD securityCoverage

medium System graph quality Placeholder conf 1.00 Placeholder or mock-heavy implementation detected

Found 28 placeholder/mock markers across 4 source files. This often means the repo looks complete while core flows still use generated scaffolding or fake data.

Mock dataIncompleteGenerated repo pattern

low System graph quality Debug conf 1.00 Debug logging residue appears in source files

Found 6 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 Tests conf 1.00 Low test-to-source ratio

8 tests / 35 src (ratio 0.23).

low System graph quality Integrity conf 1.00 2 occurrences Near-duplicate function bodies in 2 places

Functions with the same first-5-line body hash: src/projectmem/storage.py:ai_instructions_path, src/projectmem/storage.py:ai_instructions 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.

2 occurrences

repo-level (2 hits)

duplicatesduplication

low System graph software Dead code conf 1.00 Possibly dead Python function: stale_label

No callers detected by AST scan in this repo. Could be exported for external callers or a framework handler.

src/projectmem/staleness.py:102

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 Complexity conf 1.00 Very large file: src/projectmem/commands/visualize.py (1724 lines)

Files with >800 lines often hide complexity hotspots and discourage tests.

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