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luisobr2/indigo-next

https://github.com/luisobr2/indigo-next · scanned 2026-06-16 04:32 UTC (1 month, 4 weeks ago)

10 raw signals (0 security + 10 graph)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 1 month, 4 weeks ago · v1 · 8 actionable findings from 1 signal source. 2 repeated signals grouped for readability. Security checks, system graph analysis, and verified AI-agent feedback are merged into one review queue.

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66.7% cov · 8 findings

Severity distribution — click a segment to filter

Active filters: excluding tests × Reset all

Severity: Critical 0 High 0 Medium 4 Low 3 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 0 System graph 8 Crowd 0 Layer: Hardware 1 Frontend 1 Security 1 Quality 5

Exclude dismissed / FP Exclude test files

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Scan summary Repository scanned at 74.7/100 with 66.7% coverage. It contains 18 nodes across 0 cross-layer flows, written primarily in mixed languages. Engine surfaced 10 findings — concentrated in quality (5), hardware (3), frontend (1). Risk profile is low: 0 critical, 0 high, 4 medium. Recommended next step: open the quality layer findings first — that's where the highest-impact wins live.

Showing 7 of 8 actionable findings. 10 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 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 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 3 source file(s) (ratio 0.00). Consider adding integration or unit tests for critical paths.

Coverage

low System graph hardware Supply chain conf 1.00 3 occurrences Docker base image is tag-pinned but not digest-pinned: node:22-alpine

Container tags can be retagged upstream. Pin production base images to a reviewed digest (`image@sha256:...`) when reproducibility and supply-chain integrity matter.

lines 7, 21, 28

Dockerfile:7, 21, 28 (3 hits)

containersPinned dependencies

low System graph quality Agent instructions conf 1.00 Multiple root agent instruction files without precedence

The repo has multiple top-level AI-coder instruction files. Without precedence rules, different agents may follow different policies.

Governance

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

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

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