菜单
Validates all CI skills in this repo. Checks Agent Skills spec compliance, gh-aw workflow compilation, permission correctness, and structural conventions. Use when CI skills have been added or modified and you want to verify they compile and conform before committing.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Captures learnings, errors, corrections, and feature requests to enable continuous improvement. Use when: (1) User corrects Claude ('No, that's wrong...', 'Actually...'), (2) User requests a capability that doesn't exist, (3) Claude realizes its knowledge is outdated or incorrect, (4) A better approach is discovered for a recurring task, (5) Receiving a Handoff block from self-healing (a recurring verified heal at Recurrence-Count >= 3) to distill into a memory file or new skill. For ACTIVE runtime failures where the agent needs to apply and verify a fix mid-task, use `self-healing` instead (it files HEAL- entries with proof; self-improvement promotes accumulated patterns). Also review learnings before major tasks. For CI-only/headless learning capture, use self-improvement-ci.
Implementation + audit loop using parallel agent teams with structured simplify, harden, and document passes. Spawns implementation agents to do the work, then audit agents to find complexity, security gaps, and spec deviations, then loops until code compiles cleanly, all tests pass, and auditors find zero issues or the loop cap is reached. Use when: implementing features from a spec or plan, hardening existing code, fixing a batch of issues, or any multi-file task that benefits from a build-verify-fix cycle.
Monitors context window health throughout a session and rides peak context quality for maximum output fidelity. Activates automatically after plan-interview and intent-framed-agent. Stays active through execution and hands off cleanly to simplify-and-harden and self-improvement when the wave completes naturally or exits via handoff. Use this skill whenever a multi-step agent task is underway and session continuity or context drift is a concern. Especially important for long-running tasks, complex refactors, or any work where degraded context would silently corrupt the output. Trigger even if the user doesn't say "context surfing" — if an agent task is running across multiple steps with intent and a plan already established, this skill is live.
[Beta] Creates permanent eval cases from promoted learnings and runs regression checks against them. Turns failures into test cases that prevent silent regression. This is the outer loop's regress-test step. Use when a learning is promoted and has a clear pass/fail condition, or on cadence to verify promoted rules still hold.
[Beta] CI-only learning aggregation workflow using gh-aw (GitHub Agentic Workflows). Scans .learnings/ files on a schedule, groups entries by pattern_key, identifies promotion-ready patterns, and posts a gap report as a PR or issue comment. Use when: you want automated cross-session pattern detection in CI/headless pipelines without interactive prompts. For interactive use, use learning-aggregator.
[Beta] Cross-session analysis of accumulated .learnings/ files. Reads all entries, groups by pattern_key, computes recurrence across sessions, and outputs ranked promotion candidates. This is the outer loop's inspect step — it turns raw learning data into actionable gap reports. Use on a regular cadence (weekly, before major tasks, or at session start for critical projects). Can be invoked manually or scheduled.
| name | skill-tester-ci |
| description | Validates all CI skills in this repo. Checks Agent Skills spec compliance, gh-aw workflow compilation, permission correctness, and structural conventions. Use when CI skills have been added or modified and you want to verify they compile and conform before committing. |
Validates all CI skills (*-ci) in this repo. Runs spec validation, compiles gh-aw workflows, and checks CI-specific conventions.
gh-aw to a new version (API changes may break workflows)gh-aw CLI installed (gh extension install github/gh-aw)python3 with pyyaml installedquick_validate.py available at .claude/skills/skill-creator/scripts/Run quick_validate.py on every CI skill:
for d in skills/*-ci/; do
python3 .claude/skills/skill-creator/scripts/quick_validate.py "$d"
done
Extract workflow blocks from each CI skill's references/workflow-example.md and compile with gh aw compile:
# Extract markdown code blocks with frontmatter
# Copy to temp .github/workflows/
# Run: gh aw compile
Pass criteria: Zero compilation errors. Warnings are reported but don't fail.
CI workflows in strict mode must NOT use write permissions directly. Verify:
issues: write (use safe-outputs: add-comment instead)pull-requests: write (use safe-outputs: create-pull-request-review-comment instead)contents: write unless the workflow creates files (eval-creator create mode)| Check | Rule | Severity |
|---|---|---|
Has references/workflow-example.md | Required for all CI skills | Error |
| Workflow example has frontmatter block | At least one ```markdown block with --- | Error |
| Name matches folder | Frontmatter name == directory name | Error |
| Description mentions gh-aw | CI skills should reference gh-aw | Warning |
| Has corresponding interactive skill | foo-ci should have a foo counterpart | Warning |
For workflows that use call-workflow:
workflow_call in its on: section## CI Skill Test Results
**Date:** YYYY-MM-DD
**gh-aw version:** vX.Y.Z
**Skills tested:** N
**Passed:** N
**Compile errors:** N
**Spec failures:** N
### Compilation Results
- [skill-name]: ✓ compiled (N KB) | ✗ error: [message]
### Spec Results
- [skill-name]: ✓ valid | ✗ [error]
### Permission Issues
- [skill-name]: [issue]
Invoke manually:
/skill-tester-ci
Or run the script directly:
bash skills/skill-tester-ci/scripts/run-tests.sh
skill-tester for those)