task-analyzer
GitHub分析任务本质,从技能目录中匹配最小必要执行技能和元认知防护规则。根据代码证据(如缺陷、重构、前端)选择治理、风控或补充类技能,生成执行指导、潜在陷阱及关键问题,确保所选技能能切实改变验证或风险处理流程。
Trigger Scenarios
Install
npx skills add shinpr/claude-code-workflows --skill task-analyzer -g -y
SKILL.md
Frontmatter
{
"name": "task-analyzer",
"description": "Selects the smallest set of task-execution skills and metacognitive safeguards for standalone task and diagnosis workflows."
}
Task Analyzer
Use skills-index.yaml as the available skill catalog. Documentation routing and workflow Structural Scale belong to documentation-criteria, not this skill.
Process
1. Identify Task Essence
State the observable purpose beyond the surface operation. Preserve an explicitly invoked recipe or governing artifact as the entry point.
2. Match Skills to Task Evidence
Extract task-evidence tags and match them to the catalog. Add a skill only when its rules change the requested action, verification, or handling of a concrete risk.
| Task evidence | Consider |
|---|---|
| Observed defect or failure | ai-development-guide, testing-principles |
| Code implementation or refactoring | coding-principles, testing-principles |
| Requested design artifact | documentation-criteria |
| Multiple credible implementation strategies requiring cost comparison | implementation-approach |
| Observable cross-boundary behavior that cannot be proven more cheaply | integration-e2e-testing |
| React or TypeScript frontend code | typescript-rules and applicable frontend testing rules |
Select in this order:
governing: defines the requested output or selected workflow.risk-control: changes proof or handling of an activated failure mode.supplementary: resolves a concrete remaining risk.
3. Generate Execution Guidance
Generate only warnings and questions that can change skill selection, verification, escalation, or the first action. Prefer the smallest evidence-gathering action that can establish the target or cause.
Task analysis does not own Structural Scale, file-count estimation, documentation requirements, approval gates, implementation phases, or subagent topology.
Output
taskAnalysis:
essence: <fundamental purpose>
extractedTags: [<task evidence tag>]
selectedRules:
- skill: <skill name from skills-index.yaml>
priority: <governing|risk-control|supplementary>
reason: <how it changes execution or verification>
sections: [<relevant section name>]
metaCognitiveGuidance:
taskEssence: <fundamental purpose>
pastFailures: [<applicable known failure pattern>]
potentialPitfalls: [<task-specific risk>]
firstStep:
action: <smallest evidence-gathering or execution action>
rationale: <why it comes first>
metaCognitiveQuestions: [<question that can change the approach>]
warningPatterns:
- pattern: <applicable warning>
mitigation: <proportionate response>
Return skill names and relevant section names. The consumer loads the named skills; filesystem paths, catalog metadata, and skill bodies remain at their source.
Completion Check
- Task essence, tags, and first action are tied to the current request.
- Every selected skill changes execution, verification, or a concrete risk response.
- The selected set is the smallest sufficient set.
- Questions and warnings are task-specific and proportionate.
- Structural Scale and workflow routing remain with their owning process.
Version History
-
0d96a63
Current 2026-08-05 22:03
重构:基于证据收敛设计决策,简化流程,移除规模估算逻辑。
-
56ab6c1
2026-07-19 22:42
重构提示词执行指南;细化大型任务的技能优先级逻辑,区分架构影响与非实现类任务的策略要求;优化小型任务的选择限制说明。
- 66e3b29 2026-07-05 11:58


