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.
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71%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./skills/simplify-and-harden-ci/SKILL.mdnpx skills add pskoett/pskoett-ai-skills/skills/simplify-and-harden-ciRun a CI-only variant of Simplify & Harden in pull requests:
Use simplify-and-harden for interactive/local coding sessions.
CI agents do not have the same peak implementation context as the coding agent that wrote the change. Treat CI findings as structured review signals, not as full intent-aware rewrites.
Implications:
gh auth status)gh-aw installed locally for authoring/validation:gh extension install github/gh-aw- uses: github/gh-aw/actions/setup-cli@main
with:
version: v0.2.0-betaThe CI skill must enforce:
simplify_and_harden summary payloadcritical: fail check when critical harden findings existadvisory (optional): fail check when advisory findings are configured to blockExample-only template lives in references/workflow-example.md.
Keep it outside .github/workflows until you explicitly want automation enabled.
When ready to enable:
references/workflow-example.md template block into .github/workflows/simplify-and-harden-ci.md.gh aw compile --validate --strictgh aw run simplify-and-harden-ci --pushUse this prompt body in your gh-aw workflow:
Run 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) Before reporting findings, re-read all changed code with "fresh eyes" and actively look for obvious bugs, errors, confusing logic, brittle assumptions, naming issues, and missed hardening opportunities.
4) Simplify pass: detect dead code, naming clarity issues, control-flow complexity, unnecessary API surface, and over-abstraction.
5) Harden pass: detect input-validation gaps, injection vectors, auth/authz issues, secret exposure, data leaks, and concurrency risks.
6) Document pass: suggest non-obvious rationale comments as findings (do not edit files).
7) 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
8) If blocking policy is enabled and matching findings exist, mark the run as failed.Forward simplify_and_harden.learning_loop.candidates into
.learnings/LEARNINGS.md via the self-improvement workflow so recurrent
patterns can be promoted into durable agent context rules.
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If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.