Agent skill

meta

Meta - Agent System infrastructure for the ikigai project

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Install this agent skill to your Project

npx add-skill https://github.com/mgreenly/ikigai/tree/main/.claude/library/meta

SKILL.md

Meta - Agent System

Expert on the .claude/ directory structure and agent infrastructure. Use this skillset when improving or extending the agent system, skills, skillsets, or commands.

Directory Structure

.claude/
├── commands/   # Slash command definitions
├── library/    # Knowledge modules (skill directories with SKILL.md)
├── skillsets/  # Composite skill sets (JSON)
└── data/       # Runtime data (gitignored)

Skills (.claude/library/)

Each skill is a directory containing SKILL.md. Loaded via /load or as part of skillsets.

Conventions:

  • One domain per skill
  • Keep concise (~20-100 lines)
  • One directory per skill

Skill structure:

markdown
---
name: skill-name
description: Brief description
---

# Skill Name

Content here...

Commands (.claude/commands/)

Markdown files defining slash commands. The content after --- is the prompt.

Command structure:

markdown
---
description: What the command does
---

Prompt template here. Use {{args}} for arguments.

Skillsets (.claude/skillsets/)

JSON files listing skills to load together.

Skillset structure:

json
{
  "preload": ["skill-a", "skill-b"],
  "advertise": ["optional-skill-c"]
}
  • preload: Skills loaded automatically when skillset activates
  • advertise: Skills mentioned but not loaded (load on demand)

Current skillsets:

  • developer - Implementation (TDD, quality)
  • architect - Architectural decisions (DDD, DI, patterns)
  • security - Security review
  • meta - Agent system management

Best Practices

Skills:

  • Focused scope, single domain
  • Actionable guidance over theory
  • Reference docs for depth, load on demand
  • Both mechanical (how) and conceptual (why) layers

Skillsets:

  • Match a workflow phase
  • Minimal preload (only what's always needed)
  • Advertise skills that might be needed

Commands:

  • Brief description in frontmatter
  • Handle missing args gracefully
  • Clear usage examples

Efficiency Principles

The agent system is designed for token efficiency:

  1. Skillsets are minimal - Only preload skills needed for that workflow
  2. Load on demand - Don't preload "just in case"
  3. Skills are focused - One domain, ~20-100 lines
  4. Reference vs working knowledge - Large docs in separate skills

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