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santiagocuadraguemes/nzyme-talent-engine

https://github.com/santiagocuadraguemes/nzyme-talent-engine · scanned 2026-06-16 00:02 UTC (2 months, 3 weeks ago)

17 raw signals (0 security + 17 graph)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 2 months, 3 weeks ago · v1 · 17 actionable findings from 1 signal source. 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 2 Low 9 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 0 System graph 17 Crowd 0 Layer: Software 2 Api 1 Frontend 1 Cicd 1 Quality 11 Security 1

Exclude dismissed / FP Exclude test files

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Scan summary Repository scanned at 76.6/100 with 88.9% coverage. It contains 363 nodes across 0 cross-layer flows, written primarily in mixed languages. Engine surfaced 17 findings — concentrated in quality (11), software (2), api (1). Risk profile is high: 0 critical, 1 high, 2 medium. Recommended next step: open the quality layer findings first — that's where the highest-impact wins live.

Showing 12 of 17 actionable findings. Click TP / FP to vote on a finding's accuracy — votes adjust the confidence weighting and improve detection across the platform.

high System graph security Agent instructions conf 1.00 Agent instruction/config may expose a secret: CLAUDE.md

Agent-facing files are routinely pasted into LLM/tool contexts. Move literal tokens, keys, and passwords into a secret manager or document them as placeholders only.

CLAUDE.md:42 SecretsClaude instruction

medium System graph quality Agent instructions conf 1.00 Agent instructions exist but release-hardening basics are missing

AI-coder instruction files were found, but the repo is missing license, ci. Treat this as a contract gap: the agent is guided, but the generated output is not yet guarded by the controls that make it repeatable.

Repo hardeningGenerated 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

low System graph quality Production readiness conf 1.00 Composite production-readiness gap

Multiple low-cost hardening controls are missing together: license, ci. Opus verification showed these co-occurring gaps are a better readiness signal than reading each flag in isolation.

Repo hardeningGenerated repo pattern

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

Found 70 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 Near-duplicate function bodies in 2 places

Functions with the same first-5-line body hash: tools/backfill_experience_fields.py:main, tools/backfill_outcome_ids.py:main 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.

duplicatesduplication

low System graph quality License conf 1.00 No license file detected

No LICENSE/COPYING/NOTICE file was found. Generated repositories often omit licensing, which blocks reuse and automated intake.

Repo hardeningGenerated repo pattern

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

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

core/notion_client.py:192

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

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

scripts/harvester.py:64

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: scripts/harvester.py (1525 lines)

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

low System graph quality Complexity conf 1.00 Very large file: scripts/observer.py (1704 lines)

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

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