shadow-ai-git

name

shadow-ai-git

description

Detect and triage shadow AI usage from Git repositories and source trees, including model/provider SDKs, agent frameworks, MCP configs, prompts, RAG/vector stores, eval or training artifacts, CI/CD AI usage, AI supply-chain dependencies, and secret-name indicators. Use when Codex needs to catalog AI usage from code, dependency manifests, lockfiles, GitHub Actions, Dockerfiles, prompt files, or repository configuration.

Git Shadow AI Detection

Use this skill to identify AI usage and AI-adjacent risk from source repositories.

Workflow

1. Start from one checked-out repo, a directory containing multiple repos, or a text file of repo paths.
2. Run scripts/analyze_git_shadow_ai.py --input <repo-or-folder> --output-dir <analysis>.
3. For multiple explicit paths, use --repo-list <paths.txt> instead of --input.
4. Review confidence before making claims:
   • confirmed_code_usage: direct import, API call, MCP config, model ID, provider client, or runtime configuration.
   • dependency_signal: package, lockfile, image, or build dependency without direct usage.
   • prompt_or_data_signal: prompt, eval, training, dataset, or benchmark artifact.
   • ci_cd_signal: AI provider, AI tool, or AI dependency in build or workflow automation.
   • keyword_only: weak naming, docs, or comments signal; validate manually.
5. Hand the output directory to git-security-report for consolidated reporting.

Evidence Interpretation

• Treat code/config evidence as stronger than dependency-only evidence.
• Treat MCP server definitions as tool-exposure evidence even when no model call is present.
• Treat prompts, evals, and datasets as data-governance evidence, not proof of runtime usage by themselves.
• Treat CI/CD AI evidence as a separate operational risk because code, secrets, build logs, and artifacts may be exposed.
• Use references/ai-code-patterns.yaml for match classes, references/evidence-confidence.md for scoring, and references/git-ai-risk-categories.md for review categories.

Outputs

The analyzer writes:

• git_shadow_ai_summary.json
• git_shadow_ai_findings.csv
• git_ai_dependencies.csv
• git_ai_prompts.csv
• git_ai_mcp_findings.csv
• git_ai_rag_findings.csv

Keep source repositories and customer evidence separate from reusable skill fixtures.