Public scan — anyone with this URL can view this analysis. Sign up to track your own repos privately, run scheduled re-scans, and get AI fix prompts via your dashboard.

cdiaz7/file-22

https://github.com/cdiaz7/file-22 · scanned 2026-06-17 01:46 UTC (1 month, 1 week ago)

9 raw signals (0 security + 9 graph)

File as issue Image

UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 1 month, 1 week ago · v2 · last Δ +14.7 (diff) · 9 actionable findings from 1 signal source. Security checks, system graph analysis, and verified AI-agent feedback are merged into one review queue.

JSON

44.4% cov · 9 findings

Severity distribution — click a segment to filter

Active filters: excluding tests × Reset all

Severity: Critical 0 High 0 Medium 3 Low 6 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 0 System graph 9 Crowd 0 Layer: Software 1 Security 1 Quality 7

Exclude dismissed / FP Exclude test files

Corpus Intelligence Cross-corpus context (cohort percentile, top patterns, fix plan) is shown only on repositories you own. Sign up and connect your repo to view it.

Scan summary Repository scanned at 91.4/100 with 44.4% coverage. It contains 78 nodes across 0 cross-layer flows, written primarily in mixed languages. Engine surfaced 9 findings — concentrated in quality (7), software (1), security (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 9 of 9 actionable findings. 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 Production readiness conf 1.00 Composite production-readiness gap

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

Repo hardeningGenerated repo pattern

medium System graph security Coverage conf 1.00 No auth library detected

The scanner did not find any standard auth library (JWT, OAuth, NextAuth, Auth0, etc.). The repo has auth/admin/session surface indicators, so auth may live in custom code, in a separate service, or be missing.

auth

medium System graph quality Tests conf 1.00 Very low test-to-source ratio

0 test file(s) for 7 source file(s) (ratio 0.00). Consider adding integration or unit tests for critical paths.

Coverage

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

Found 30 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: probe_R2.py:cat_strictly_better, probe_R2.py:cat_strictly_better 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 quality Docs conf 1.00 No README detected

No README file was found. Generated repos without README context are hard to operate, validate, or safely hand off.

ReadmeRepo hardeningGenerated repo pattern

low System graph quality Integrity conf 1.00 Old/deprecated-named symbol `assign_old` in probe_R2.py:40

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: to_json

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

mm5_agent.py:100

For AI agents: Voting guide (TP/FP) MCP manifest Stdio wrapper SARIF Integrate Findings queue Vote TP/FP on findings to calibrate the engine.

For AI agents + API integrations

Email me when this repo regresses

Free. We re-scan periodically; new criticals → your inbox. No signup required for the scan itself.

API access

This page is publicly accessible at: https://repobility.com/scan/db572e50-7d85-4343-b777-59520c5ecdb7/

To check status programmatically (no auth required):

curl -s https://repobility.com/api/v1/public/scan/db572e50-7d85-4343-b777-59520c5ecdb7/

Important — please don't re-submit the same URL repeatedly. The submission endpoint is idempotent: re-submitting the same git URL returns this same scan_token, not a new one. To re-scan this repo, sign up free and use the dashboard.