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基于 SOC 职业分类
| name | fix-ci |
| description | [Implementation] Analyze Github Actions logs and fix issues Use when this capability is needed. |
[IMPORTANT] Use
TaskCreateto break ALL work into small tasks BEFORE starting — including tasks for each file read. This prevents context loss from long files. For simple tasks, AI MUST ATTENTION ask user whether to skip.
Understand Code First — HARD-GATE: Do NOT write, plan, or fix until you READ existing code.
- Search 3+ similar patterns (
grep/glob) — citefile:lineevidence- Read existing files in target area — understand structure, base classes, conventions
- Run
python .claude/scripts/code_graph trace <file> --direction both --jsonwhen.code-graph/graph.dbexists- Map dependencies via
connectionsorcallers_of— know what depends on your target- Write investigation to
.ai/workspace/analysis/for non-trivial tasks (3+ files)- Re-read analysis file before implementing — never work from memory alone
- NEVER invent new patterns when existing ones work — match exactly or document deviation
BLOCKED until:
- [ ]Read target files- [ ]Grep 3+ patterns- [ ]Graph trace (if graph.db exists)- [ ]Assumptions verified with evidence
Evidence-Based Reasoning — Speculation is FORBIDDEN. Every claim needs proof.
- Cite
file:line, grep results, or framework docs for EVERY claim- Declare confidence: >80% act freely, 60-80% verify first, <60% DO NOT recommend
- Cross-service validation required for architectural changes
- "I don't have enough evidence" is valid and expected output
BLOCKED until:
- [ ]Evidence file path (file:line)- [ ]Grep search performed- [ ]3+ similar patterns found- [ ]Confidence level statedForbidden without proof: "obviously", "I think", "should be", "probably", "this is because" If incomplete → output:
"Insufficient evidence. Verified: [...]. Not verified: [...]."
docs/project-reference/domain-entities-reference.md — Domain entity catalog, relationships, cross-service sync (read when task involves business entities/models) (content auto-injected by hook — check for [Injected: ...] header before reading)Estimation — Modified Fibonacci: 1(trivial) → 2(small) → 3(medium) → 5(large) → 8(very large) → 13(epic, SHOULD split) → 21(MUST ATTENTION split). Output
story_pointsandcomplexityin plan frontmatter. Complexity auto-derived: 1-2=Low, 3-5=Medium, 8=High, 13+=Critical.
Skill Variant: Variant of
/fix— specialized for CI/GitHub Actions log analysis.
Goal: Analyze GitHub Actions CI logs to identify and fix build/test failures in the pipeline.
Workflow:
Key Rules:
docs/project-config.json → infrastructure.cicd.tool to identify CI platform (e.g., "azure-devops", "github-actions", "gitlab-ci"). Target the correct pipeline config files for that platform.file:line evidenceRoot Cause Debugging — Systematic approach, never guess-and-check.
- Reproduce — Confirm the issue exists with evidence (error message, stack trace, screenshot)
- Isolate — Narrow to specific file/function/line using binary search + graph trace
- Trace — Follow data flow from input to failure point. Read actual code, don't infer.
- Hypothesize — Form theory with confidence %. State what evidence supports/contradicts it
- Verify — Test hypothesis with targeted grep/read. One variable at a time.
- Fix — Address root cause, not symptoms. Verify fix doesn't break callers via graph
connectionsNEVER: Guess without evidence. Fix symptoms instead of cause. Skip reproduction step.
Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).
file:line evidenceMANDATORY IMPORTANT MUST ATTENTION declare Confidence: X% with evidence list + file:line proof for EVERY claim.
95%+ recommend freely | 80-94% with caveats | 60-79% list unknowns | <60% STOP — gather more evidence.
$ARGUMENTS
⚠️ Validate Before Fix (NON-NEGOTIABLE): After CI log analysis + root cause identification, MUST ATTENTION present findings + proposed fix to user via
AskUserQuestionand get explicit approval BEFORE any code changes. No silent fixes.
debugger subagent to read the github actions logs with gh command, analyze and find the root cause of the issues and report back to main agent.
1.5. Write analysis findings to .ai/workspace/analysis/{ci-issue}.analysis.md. Re-read before implementing fix.AskUserQuestion → wait for user approval.tester agent to test the fix and make sure it works, then report back to main agent.If gh command is not available, instruct the user to install and authorize GitHub CLI first.
After fixing, MUST ATTENTION run /prove-fix — build code proof traces per change with confidence scores. Never skip.
TaskCreate BEFORE startingfile:line evidence for every claim (confidence >80% to act)file:line evidence for every claim. Confidence >80% to act, <60% = do NOT recommend.
story_points and complexity in plan frontmatter. SP > 8 = split.
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