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.

Rybjuani/nm_suite_clean

https://github.com/Rybjuani/nm_suite_clean · scanned 2026-06-16 02:56 UTC (2 months ago)

13 raw signals (0 security + 13 graph)

File as issue Image

UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 2 months ago · v2 · 13 actionable findings from 1 signal source. Security checks, system graph analysis, and verified AI-agent feedback are merged into one review queue.

JSON

66.7% cov · 13 findings

Severity distribution — click a segment to filter

Active filters: excluding tests × Reset all

Severity: Critical 0 High 0 Medium 6 Low 4 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 0 System graph 13 Crowd 0 Layer: Quality 11 Frontend 1 Cicd 1

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 85.0/100 with 66.7% coverage. It contains 64 nodes across 0 cross-layer flows, written primarily in mixed languages. Engine surfaced 13 findings — concentrated in quality (11), frontend (1), cicd (1). Risk profile is low: 0 critical, 0 high, 6 medium. Recommended next step: open the quality layer findings first — that's where the highest-impact wins live.

Showing 10 of 13 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 Agent instructions conf 1.00 Agent authority lacks a verifier contract: .clinerules

This agent instruction grants code or shell authority but does not state the verification gate that decides promotion. The recurring safe pattern is: LLM proposes; deterministic tests/build/security checks verify; only verified code promotes.

.clinerules VerificationCline 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 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 quality Integrity conf 1.00 Network/subprocess call without timeout or try/except — build_neuromood.py:758

`subprocess.run(...)` here lacks both a `timeout=` arg and an enclosing try/except. This is exactly the class of bug that took down our git-clone earlier (HTTP/2 stream cancel surfaced as a fatal). Add a `timeout=` and wrap in try/except, or use a wrapper that retries.

runtime safetyRobustness

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 Tests conf 1.00 Very low test-to-source ratio

0 test file(s) for 1 source file(s) (ratio 0.00). Consider adding integration or unit tests for critical paths.

Coverage

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 43 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 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 Integrity conf 1.00 Stub function `_validate_runtime_env_values` (body is just `pass`/`return`) — build_neuromood.py:445

Likely an AI scaffold that was never filled in. Remove or implement.

Empty handlerDead code

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/e32038b2-0469-4ffc-a64e-fae52cc77584/

To check status programmatically (no auth required):

curl -s https://repobility.com/api/v1/public/scan/e32038b2-0469-4ffc-a64e-fae52cc77584/

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.