5.6 KiB
5.6 KiB
description
| description |
|---|
| Display information about a Map of Content (MOC) file |
Graph MOC (Map of Content)
Display information about a specific MOC (Map of Content) file, which serves as a thematic navigation hub.
0. Locate AZKG Repository
Check for AZKG_REPO_PATH environment variable:
- Use bash conditional:
if [ -z "$AZKG_REPO_PATH" ]; then REPO_PATH=$(pwd); else REPO_PATH="$AZKG_REPO_PATH"; fi - If AZKG_REPO_PATH is set: Use that path as the repository root
- If AZKG_REPO_PATH is not set: Use current working directory (pwd)
- Store result as REPO_PATH for all subsequent file operations
All file operations must use REPO_PATH:
- Read:
Read(REPO_PATH/filename.md)orRead("$REPO_PATH/filename.md") - Write:
Write(REPO_PATH/filename.md)orWrite("$REPO_PATH/filename.md") - Edit:
Edit(REPO_PATH/filename.md)orEdit("$REPO_PATH/filename.md") - Grep:
Grep(pattern, path=REPO_PATH)or with explicit path - Glob:
Glob(pattern, path=REPO_PATH)or with explicit path
Example usage:
# Check environment variable
if [ -z "$AZKG_REPO_PATH" ]; then
REPO_PATH=$(pwd)
else
REPO_PATH="$AZKG_REPO_PATH"
fi
# Then use REPO_PATH for all operations
Read("$REPO_PATH/agents.md")
Concrete examples:
- If AZKG_REPO_PATH="/c/Users/dothompson/OneDrive/src/witt3rd/donald-azkg" → Read("/c/Users/dothompson/OneDrive/src/witt3rd/donald-azkg/agents.md")
- If AZKG_REPO_PATH is not set and pwd is /c/Users/dothompson/OneDrive/src/witt3rd/donald-azkg → Read("agents.md") or use full path from pwd
Task
Show:
- MOC name and theme
- Total notes linked in this MOC
- List of all notes with their brief descriptions
- Section organization within the MOC
Input
User provides the MOC name (e.g., "agents", "mcp", "python", "rust")
Common MOCs:
- agents_moc.md - AI agents and agentic systems
- mcp_moc.md - Model Context Protocol
- python_moc.md - Python development
- rust_moc.md - Rust programming
- typescript_moc.md - TypeScript and React
- windows_moc.md - Windows development
- writing_moc.md - Writing and communication
- csharp_moc.md - C# development
Execution Steps
1. Normalize MOC Name
Ensure filename has _moc.md suffix:
- Input: "agents" → "agents_moc.md"
- Input: "agents_moc" → "agents_moc.md"
- Input: "agents_moc.md" → "agents_moc.md"
2. Verify MOC Exists
Use Glob to check if MOC file exists:
Glob "agents_moc.md"
If not found, list available MOCs and suggest closest match.
3. Read MOC Content
Use Read tool to get full MOC content.
4. Parse MOC Structure
Extract:
- Title (H1 heading)
- Sections (H2 headings)
- Wikilinks in each section
- Brief descriptions next to each wikilink
Example MOC structure:
# Agents - Map of Content
## Core Concepts
- [[agents]] - AI agents powered by LLMs
- [[semantic_routing]] - Intelligent model selection
## Coding Assistants
- [[claude_code]] - Agentic AI coding assistant
- [[claude_code_agents]] - Subagent system
5. Count Notes
Count total wikilinks across all sections.
Output Format
MOC: agents_moc.md
============================================================
Theme: AI agents and agentic systems
Total notes: 15
## Sections and Notes:
### Core Concepts (5 notes)
- [[agents]] - AI agents powered by LLMs for autonomous action
- [[semantic_routing]] - Intelligent model selection based on query
- [[react_agent_pattern]] - Design pattern for agent UIs
- [[llm_self_talk_optimization]] - Token-efficient agent communication
- [[agentic_development_context]] - Comprehensive development ecosystems
### Coding Assistants (5 notes)
- [[claude_code]] - Anthropic's agentic AI coding assistant
- [[claude_code_agents]] - Subagent system for parallel tasks
- [[claude_code_plugins]] - Extensibility via slash commands
- [[claude_code_hooks]] - Lifecycle event system
- [[zettelkasten_claude_plugin]] - Knowledge graph plugin
### Integration & APIs (2 notes)
- [[agent_mcp_apis]] - MCP APIs for agent tool integration
- [[adding_mcp_to_claude_code]] - Adding custom agents
### Related Topics (3 notes)
- [[mcp_overview]] - Protocol for agent tool integration
- [[react_framework]] - UI framework for agents
============================================================
💡 Next steps:
• Use `/graph-note [filename]` to explore any note in this MOC
• Use `/create-note` to add new notes to this domain
• Use `/search-notes #agents` to find all agent-tagged notes
Use Cases
- Explore a domain: See all notes in a specific theme
- Find related notes: Discover notes you didn't know existed
- Assess coverage: Check if a topic area is well-covered
- Navigate efficiently: Jump to specific concepts in a domain
- Plan additions: Identify gaps where new notes are needed
Tools Used
- Glob - Verify MOC file exists, list all MOCs
- Read - Get full MOC content
- Parse logic - Extract sections, wikilinks, descriptions
Present Results
After displaying MOC information:
- Assess coverage (comprehensive vs sparse)
- Comment on organization (clear sections vs needs structure)
- Suggest if MOC is getting too large (might need splitting)
- Identify potential notes to add based on theme
- Note any wikilinks that point to non-existent notes
If MOC Not Found
MOC not found: unknown_moc.md
Available MOCs:
- agents_moc.md - AI agents and agentic systems
- mcp_moc.md - Model Context Protocol
- python_moc.md - Python development
- rust_moc.md - Rust programming
- typescript_moc.md - TypeScript and React
- windows_moc.md - Windows development
- writing_moc.md - Writing and communication
- csharp_moc.md - C# development
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