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CI-only Simplify & Harden workflow for pull requests using gh-aw (GitHub Agentic Workflows). Runs headless scan-and-report checks for simplify/harden/document, posts structured findings, and can block merges on critical or advisory classes. Use when: you want automated quality/security review in CI without interactive approvals.
npx skill4agent add pskoett/pskoett-ai-skills simplify-and-harden-cinpx skills add pskoett/pskoett-ai-skills/simplify-and-harden-cisimplify-and-hardengh auth statusgh-awgh extension install github/gh-aw- uses: github/gh-aw/actions/setup-cli@main
with:
version: v0.2.0-betasimplify_and_hardencriticaladvisoryreferences/workflow-example.md.github/workflowsreferences/workflow-example.md.github/workflows/simplify-and-harden-ci.mdgh aw compile --validate --strictgh aw run simplify-and-harden-ci --pushRun Simplify & Harden in CI (headless mode) for this pull request.
Rules:
1) Review only files changed in this PR.
2) Do not modify repository files.
3) Simplify pass: detect dead code, naming clarity issues, control-flow complexity, unnecessary API surface, and over-abstraction.
4) Harden pass: detect input-validation gaps, injection vectors, auth/authz issues, secret exposure, data leaks, and concurrency risks.
5) Document pass: suggest non-obvious rationale comments as findings (do not edit files).
6) Emit structured YAML under key `simplify_and_harden`, including:
- simplify findings
- harden findings (critical/advisory split)
- summary counts
- `review_followup_required`
- learning loop candidates for self-improvement ingestion
7) If blocking policy is enabled and matching findings exist, mark the run as failed.simplify_and_harden.learning_loop.candidates.learnings/LEARNINGS.mdself-improvement