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.

divake/ai_intel_ml_lidar

https://github.com/divake/ai_intel_ml_lidar · scanned 2026-06-17 01:57 UTC (1 month, 1 week ago)

15 raw signals (0 security + 15 graph)

UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 1 month, 1 week ago · v2 · last Δ -14.0 (diff) · 12 actionable findings from 1 signal source. 3 repeated signals grouped for readability. Security checks, system graph analysis, and verified AI-agent feedback are merged into one review queue.

JSON
Severity distribution — click a segment to filter
Active filters: excluding tests × Reset all
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 62.7/100 with 44.4% coverage. It contains 73 nodes across 0 cross-layer flows, written primarily in mixed languages. Engine surfaced 15 findings — concentrated in software (7), quality (7), network (1). Risk profile is low: 0 critical, 0 high, 5 medium. Recommended next step: open the software layer findings first — that's where the highest-impact wins live.

Showing 11 of 12 actionable findings. 15 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 Agent instructions conf 1.00 Agent authority lacks a verifier contract: CLAUDE.md
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.
CLAUDE.md VerificationClaude 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, tests. 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 Production readiness conf 1.00 Composite production-readiness gap
Multiple low-cost hardening controls are missing together: license, ci, tests. 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 network Security conf 1.00 Privileged port 19 in use
Port 19 is privileged (<1024). Make sure the service runs with the right caps or front it with a non-privileged port via a load balancer.
projects/01_kiss_icp_mapping/run/start_foxglove.sh Ports
medium System graph quality Tests conf 1.00 Very low test-to-source ratio
0 test file(s) for 10 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 25 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 software Dead code conf 1.00 Possibly dead Python function: cb
No callers detected by AST scan in this repo. Could be exported for external callers or a framework handler.
check_rates.py:44
low System graph software Dead code conf 1.00 Possibly dead Python function: frame_world
No callers detected by AST scan in this repo. Could be exported for external callers or a framework handler.
projects/01_kiss_icp_mapping/run/dataset_loader.py:63
low System graph software Dead code conf 1.00 4 occurrences Possibly dead Python function: generate_launch_description
No callers detected by AST scan in this repo. Could be exported for external callers or a framework handler.
4 files, 4 locations
projects/01_kiss_icp_mapping/run/kiss_only.launch.py:12
projects/01_kiss_icp_mapping/run/lidar_kiss_pipeline.launch.py:12
projects/02_fast_lio2/run/fast_lio_pipeline.launch.py:26
projects/03_autonomy/run/slam_offline.launch.py:14
low System graph software Dead code conf 1.00 Possibly dead Python function: split
No callers detected by AST scan in this repo. Could be exported for external callers or a framework handler.
projects/01_kiss_icp_mapping/run/dataset_loader.py:70
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/c6989fec-ef17-4968-92d6-c5850fe90816/

To check status programmatically (no auth required):

curl -s https://repobility.com/api/v1/public/scan/c6989fec-ef17-4968-92d6-c5850fe90816/

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.