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ukvalley/AI-CMO

https://github.com/ukvalley/AI-CMO · scanned 2026-06-16 02:57 UTC (2 months ago)

11 raw signals (0 security + 11 graph)

UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 2 months ago · v2 · 11 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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Scan summary Repository scanned at 73.1/100 with 88.9% coverage. It contains 61 nodes across 0 cross-layer flows, written primarily in mixed languages. Engine surfaced 11 findings — concentrated in quality (4), security (3), cicd (2). Risk profile is high: 2 critical, 1 high, 2 medium. Recommended next step: open the quality layer findings first — that's where the highest-impact wins live.

Showing 9 of 11 actionable findings. Click TP / FP to vote on a finding's accuracy — votes adjust the confidence weighting and improve detection across the platform.

critical System graph security Secrets conf 1.00 Runtime dotenv file present in repo: .env.dev
`.env.dev` looks like a runtime dotenv file. It contains secret-looking assignments for JWT_SECRET, CLAUDE_API_KEY. Move real values to a secret manager and keep only `.env.example` style templates in source control.
.env.dev ConfigEnv fileRuntime env
critical System graph security Secrets conf 1.00 Runtime dotenv file present in repo: .env.prod
`.env.prod` looks like a runtime dotenv file. It contains secret-looking assignments for SMTP_PASS. Move real values to a secret manager and keep only `.env.example` style templates in source control.
.env.prod ConfigEnv fileRuntime env
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:208 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 hardware Coverage conf 1.00 Containers defined but no K8s/orchestration manifest found
Repo has Dockerfiles/compose but no Kubernetes/Nomad manifests. If the target deployment is K8s, the manifests may live in a separate ops repo.
Deployment
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 cicd CI/CD security conf 1.00 package.json defines install-time lifecycle scripts
preinstall/install/postinstall/prepare scripts execute during dependency installation. Review them carefully for network calls, obfuscation, shell execution, or credential access.
package.json CI/CD securitySupply chainNpm
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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