task-analyzer

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