Files
our-claude-skills/AGENTS.md
Andrew Yim d1cd1298a8 feat(reference-curator): Add pipeline orchestrator and refactor skill format
Pipeline Orchestrator:
- Add 07-pipeline-orchestrator skill with code/CLAUDE.md and desktop/SKILL.md
- Add /reference-curator-pipeline slash command for full workflow automation
- Add pipeline_runs and pipeline_iteration_tracker tables to schema.sql
- Add v_pipeline_status and v_pipeline_iterations views
- Add pipeline_config.yaml configuration template
- Update AGENTS.md with Reference Curator Skills section
- Update claude-project files with pipeline documentation

Skill Format Refactoring:
- Extract YAML frontmatter from SKILL.md files to separate skill.yaml
- Add tools/ directories with MCP tool documentation
- Update SKILL-FORMAT-REQUIREMENTS.md with new structure
- Add migrate-skill-structure.py script for format conversion

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-29 01:01:02 +07:00

213 lines
6.8 KiB
Markdown

# AGENTS.md
This file documents how to effectively use Claude Code's specialized agents (via the Task tool) when working with this skills repository.
## Agent Types for Skills Development
### Explore Agent
**Best for:** Understanding skill structure, finding patterns, researching existing implementations
```
Use Task tool with subagent_type=Explore for:
- "How is the SEO technical audit skill structured?"
- "Find all skills that use Python scripts"
- "What MCP tools are commonly used in desktop skills?"
- "Compare the structure of GTM audit vs GTM manager"
```
**When to use:**
- Codebase exploration before creating new skills
- Finding patterns across multiple skills
- Understanding how existing features are implemented
### Plan Agent
**Best for:** Designing new skills, planning refactors, architectural decisions
```
Use Task tool with subagent_type=Plan for:
- "Plan a new skill for Google Analytics 4 audit"
- "Design the structure for a multi-step SEO workflow"
- "Plan the refactoring of notion-organizer to support batch operations"
```
**When to use:**
- Before creating a new skill (design first)
- When refactoring affects multiple files
- For complex feature implementations
### General-Purpose Agent
**Best for:** Multi-step tasks that combine research and action
```
Use Task tool with subagent_type=general-purpose for:
- "Create a new skill for PDF generation following the existing patterns"
- "Audit all Jamie skills for consistent branding guidelines"
- "Update all SEO skills to use a shared utility module"
```
**When to use:**
- Complex tasks requiring both exploration and implementation
- Tasks spanning multiple skills or directories
### Bash Agent
**Best for:** Git operations, running scripts, file system tasks
```
Use Task tool with subagent_type=Bash for:
- "Run the skill validation script on all custom skills"
- "Create git commits for each modified skill separately"
- "Execute the token analyzer on all SKILL.md files"
```
**When to use:**
- Running Python scripts in the skills
- Git operations (commits, branches, diffs)
- Batch file operations
## Skill-Specific Agent Recommendations
### Creating New Skills
| Task | Recommended Agent | Notes |
|------|-------------------|-------|
| Research existing patterns | Explore | Find similar skills first |
| Design skill structure | Plan | Define scope before coding |
| Generate boilerplate | general-purpose | Use init_skill.py template |
| Write SKILL.md/CLAUDE.md | Direct (no agent) | Simple file writing |
| Implement scripts | Direct (no agent) | Write Python/Bash directly |
| Validate skill | Bash | Run validation scripts |
### Auditing & Maintenance
| Task | Recommended Agent | Notes |
|------|-------------------|-------|
| Audit skill completion | Explore | Check for missing files |
| Update multiple skills | general-purpose | Batch operations |
| Refactor shared code | Plan + general-purpose | Plan first, then execute |
| Test skill scripts | Bash | Run tests and verify |
### Documentation
| Task | Recommended Agent | Notes |
|------|-------------------|-------|
| Generate skill summaries | Explore | Gather info from all skills |
| Update CLAUDE.md | Direct (no agent) | Simple documentation |
| Create usage examples | Explore + Direct | Research then document |
## Parallel Agent Execution
For independent tasks, launch multiple agents simultaneously:
```
# Good: These tasks are independent
Task 1: Explore - "Find all skills missing requirements.txt"
Task 2: Explore - "List all skills with desktop/SKILL.md"
Task 3: Bash - "Count lines of Python code per skill"
# Bad: These depend on each other
Task 1: Plan - "Design the new skill structure"
Task 2: general-purpose - "Implement the planned skill" # Needs Task 1 result
```
## Domain-Specific Routing
### SEO Skills (10-19)
- Use **seo-advisor** agent for SEO strategy questions
- Use **Explore** to understand existing SEO script patterns
- Python scripts in these skills follow `base_client.py` patterns
### GTM Skills (20-29)
- Use **gtm-manager** agent for GTM-specific debugging
- Requires Chrome GTM Debug profile for live testing
- Scripts interact with GTM API and dataLayer
### Jamie Clinic Skills (40-49)
- Brand compliance is critical - check `references/` for guidelines
- Korean language content - verify encoding in scripts
- Instagram/YouTube skills may need API credentials
### Notion Skills (31-39)
- Use Notion MCP tools (`mcp__plugin_Notion_notion__*`) directly
- Skills export data to Working with AI database
- Check schema compatibility before creating pages
### Reference Curator Skills (90-99)
- Use **reference-curator-pipeline** for full automated curation workflows
- Runs as background task, coordinates all 6 skills in sequence
- Handles QA loops automatically (max 3 refactor, 2 deep_research iterations)
- Supports three input modes: topic (full pipeline), URLs (skip discovery), manifest (resume)
```
# Full pipeline from topic
/reference-curator-pipeline "Claude Code best practices" --max-sources 5
# Direct URL crawling (skip discovery)
/reference-curator-pipeline https://docs.anthropic.com/en/docs/prompt-caching
# Resume from manifest
/reference-curator-pipeline ./manifest.json --auto-approve
```
Individual skills can still be run separately:
- `/reference-discovery` - Search and validate sources
- `/web-crawler` - Crawl URLs with auto-backend selection
- `/content-repository` - Manage stored documents
- `/content-distiller` - Summarize and extract key concepts
- `/quality-reviewer` - QA scoring and routing
- `/markdown-exporter` - Export to project files or JSONL
## Background Agents
For long-running tasks, use `run_in_background: true`:
```
# Good candidates for background execution:
- Full skill audit across all 23 skills
- Running Python tests on multiple skills
- Generating comprehensive documentation
# Not suitable for background:
- Interactive debugging
- Tasks requiring user input
- Quick file operations
```
## Agent Handoff Patterns
### Research → Implementation
1. **Explore agent**: Gather context and patterns
2. **Plan agent**: Design the approach
3. **Direct implementation**: Write the code
4. **Bash agent**: Test and validate
### Bug Fix Workflow
1. **Explore agent**: Find related code and understand the issue
2. **Direct implementation**: Fix the bug
3. **Bash agent**: Run tests to verify
### New Skill Creation
1. **Explore agent**: Study 2-3 similar existing skills
2. **Plan agent**: Design skill scope and structure
3. **Bash agent**: Run `init_skill.py` to generate boilerplate
4. **Direct implementation**: Write SKILL.md/CLAUDE.md and scripts
5. **Bash agent**: Validate and test
## Notes
- Always prefer **Explore** for open-ended questions about the codebase
- Use **Plan** before major changes to get user approval
- Direct tool use (Read, Edit, Write) is faster for simple operations
- Agents have full context of the conversation when spawned