task-analyzer

GitHub

执行元认知任务分析与技能选择。通过解析任务本质、估算规模及识别类型,结合标签匹配从技能索引中筛选并排序推荐技能,辅助确定工作复杂度与所需工具。

dev-workflows-fullstack/skills/task-analyzer/SKILL.md shinpr/claude-code-workflows

Trigger Scenarios

需要评估任务复杂度和工作量时 决定使用哪些专业技能来完成特定任务时 分析代码修改或功能开发的根本目的时

Install

npx skills add shinpr/claude-code-workflows --skill task-analyzer -g -y
More Options

Non-standard path

npx skills add https://github.com/shinpr/claude-code-workflows/tree/main/dev-workflows-fullstack/skills/task-analyzer -g -y

Use without installing

npx skills use shinpr/claude-code-workflows@task-analyzer

指定 Agent (Claude Code)

npx skills add shinpr/claude-code-workflows --skill task-analyzer -a claude-code -g -y

安装 repo 全部 skill

npx skills add shinpr/claude-code-workflows --all -g -y

预览 repo 内 skill

npx skills add shinpr/claude-code-workflows --list

SKILL.md

Frontmatter
{
    "name": "task-analyzer",
    "description": "Performs metacognitive task analysis and skill selection. Use when determining task complexity, selecting appropriate skills, or estimating work scale."
}

Task Analyzer

Provides metacognitive task analysis and skill selection guidance.

Skills Index

See skills-index.yaml for available skills metadata.

Task Analysis Process

1. Understand Task Essence

Identify the fundamental purpose beyond surface-level work:

Surface Work Fundamental Purpose
"Fix this bug" Problem solving, root cause analysis
"Implement this feature" Feature addition, value delivery
"Refactor this code" Quality improvement, maintainability
"Update this file" Change management, consistency

Action: Map the user request to one row in the Surface Work → Fundamental Purpose table above. If no row matches, state the fundamental purpose explicitly before proceeding.

2. Estimate Task Scale

Scale File Count Indicators
Small 1-2 Single function/component change
Medium 3-5 Multiple related components
Large 6+ Cross-cutting concerns, architecture impact

Scale affects skill priority:

  • Scale >= Large → include documentation-criteria and implementation-approach in selectedSkills with priority high
  • Scale = Small → limit selectedSkills to task-type essential skills only (max 3)

3. Identify Task Type

Type Characteristics Key Skills
Implementation New code, features coding-principles, testing-principles
Fix Bug resolution ai-development-guide, testing-principles
Refactoring Structure improvement coding-principles, ai-development-guide
Design Architecture decisions documentation-criteria, implementation-approach
Quality Testing, review testing-principles, integration-e2e-testing

4. Tag-Based Skill Matching

Extract relevant tags from task description and match against skills-index.yaml:

Task: "Implement user authentication with tests"
Extracted tags: [implementation, testing, security]
Matched skills:
  - coding-principles (implementation, security)
  - testing-principles (testing)
  - ai-development-guide (implementation)

5. Implicit Relationships

Consider hidden dependencies:

Task Involves Also Include
Error handling debugging, testing
New features design, implementation, documentation
Performance profiling, optimization, testing
Frontend typescript-rules, test-implement
API/Integration integration-e2e-testing

Output Format

Return structured analysis with skill metadata from skills-index.yaml:

taskAnalysis:
  essence: <string>  # Fundamental purpose identified
  type: <implementation|fix|refactoring|design|quality>
  scale: <small|medium|large>
  estimatedFiles: <number>
  tags: [<string>, ...]  # Extracted from task description

selectedSkills:
  - skill: <skill-name>  # From skills-index.yaml
    priority: <high|medium|low>
    reason: <string>  # Why this skill was selected
    # Pass through metadata from skills-index.yaml
    tags: [...]
    typical-use: <string>
    size: <small|medium|large>
    sections: [...]  # All sections from yaml, unfiltered

Note: Section selection (choosing which sections are relevant) is done after reading the actual SKILL.md files.

Skill Selection Priority

  1. Essential - Directly related to task type
  2. Quality - Testing and quality assurance
  3. Process - Workflow and documentation
  4. Supplementary - Reference and best practices

Metacognitive Question Design

Generate 3-5 questions according to task nature:

Task Type Question Focus
Implementation Design validity, edge cases, performance
Fix Root cause (5 Whys), impact scope, regression testing
Refactoring Current problems, target state, phased plan
Design Requirement clarity, future extensibility, trade-offs

Warning Patterns

Detect and flag these patterns:

Pattern Warning Mitigation
Large change detected Pair with implementation-approach Split into phases per strategy
Implementation task detected Pair with testing-principles Apply TDD from start
Error fix requested Pair with ai-development-guide Apply 5 Whys before fixing
Multi-file task without plan Pair with documentation-criteria Create work plan first

Version History

  • 66e3b29 Current 2026-07-05 12:00

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dev-skills/skills/documentation-criteria/SKILL.md
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Metadata

Files
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Version
66e3b29
Hash
af84d9c1
Indexed
2026-07-05 12:00

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