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task-analyzer

Analyze task context and produce YAML task analysis with skill recommendations.

225|24|Updated Jul 27, 2025
Search Tags:#workflow optimization#metacognition#skill selection#task analysis
One-click install
npx skills add https://github.com/shinpr/ai-coding-project-boilerplate --skill task-analyzer
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: task-analyzer
Source: https://github.com/shinpr/ai-coding-project-boilerplate/tree/main/.claude/skills-ja/task-analyzer
Command: npx skills add https://github.com/shinpr/ai-coding-project-boilerplate --skill task-analyzer

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill eliminates guesswork in task analysis by automatically identifying the fundamental purpose, estimating scale, and recommending appropriate skills.

Core Features & Use Cases

  • Metacognitive Analysis: Understand task essence beyond surface-level work.
  • Skill Matching: Select the most relevant skills based on task metadata and tags.

Quick Start

Analyze the task "Implement user authentication with tests" and recommend the best skills to use.

Core Features & Use Cases

  • Scale Estimation: Classify tasks as small (1-2 files), medium (3-5 files), or large (6+ files).

Quick Start

Use this Skill to analyze any development task and get structured recommendations for implementation.

Frequently Asked Questions about task-analyzer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I analyze a task to determine its scope and complexity before starting?▼

Task analysis identifies the fundamental purpose, estimates whether work spans 1-2 files (small), 3-5 files (medium), or 6+ files (large), and classifies the task type—bug fix, feature, refactor, or design—to set realistic expectations and resource allocation.

What's the best way to select the right skills for a development task?▼

Skill selection maps task metadata and tags against a skills index to recommend the most relevant tools ranked by priority, showing why each skill fits, typical use patterns, and the scope it handles best.

How does metacognitive analysis help when planning implementation work?▼

Metacognitive analysis moves beyond surface-level task descriptions to uncover the problem being solved and its dependent relationships, preventing wasted effort on misaligned implementations and clarifying what dependencies must be handled first.

Can I use task analysis to estimate file count and implementation difficulty?▼

Yes, task analysis produces structured YAML output containing estimated file counts, task essence, type classification, and tags that distinguish complexity levels across small, medium, and large scope changes.

What output do I get from analyzing a task?▼

Task analysis produces YAML-structured output mapping task analysis results—essence, type, scale, estimated files, tags—and selected skills with priority ranking, reasoning, typical use cases, and scope recommendations from a skills index.

Should I analyze task scope before choosing implementation tools?▼

Yes, understanding task essence and scale first ensures skill selection matches actual work complexity; skills recommended for large refactors differ from those for single-file bug fixes, reducing misalignment between planning and execution.

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