Context Library

This directory contains reusable context for AI-assisted development. Documents here are indexed into the knowledge graph and made available for semantic search.

Directory Structure

context-library/
├── architecture/       # System architecture documentation
├── patterns/          # Design patterns and best practices
├── rules/            # Coding rules and standards
└── references/       # Library and tool references

Usage

Adding Context

1. Create markdown files in the appropriate subdirectory
2. Use hashtags to tag concepts: #async #rust #patterns
3. Cross-reference related documents: See [[async-patterns]]
4. Include code examples where relevant

Searching Context

With Terraphim running:

# Search semantically
curl -X POST http://localhost:PORT/documents/search \
  -H "Content-Type: application/json" \
  -d '{"search_term": "async patterns", "role": "Context Engineer"}'

# Via MCP in Claude Desktop
# Claude will automatically search this context when relevant

Organizing Content

architecture/

System design, data flow, API contracts, and high-level architecture decisions.

Example topics:

• System design documents
• Architecture decision records (ADRs)
• Data flow diagrams
• API contracts and schemas
• Component interactions

patterns/

Reusable design patterns, best practices, and problem-solving approaches.

Example topics:

• Async/concurrent programming patterns
• Error handling strategies
• Testing approaches
• Performance optimization techniques
• Security patterns

rules/

Coding standards, conventions, and project-specific guidelines.

Example topics:

• Language-specific coding standards
• Code review checklists
• Security guidelines
• Performance requirements
• Documentation requirements

references/

Quick reference for libraries, tools, and frameworks used in the project.

Example topics:

• Library API quick references
• Tool usage guides
• Framework conventions
• Common commands and snippets
• Troubleshooting guides

Best Practices

Document Structure

# Title

Brief description of the topic.

## Problem
What problem does this solve?

## Solution
How is it solved?

## Example
\`\`\`rust
// Working code example
\`\`\`

## Trade-offs
What are the pros and cons?

## Related
- [[other-pattern]]
- [[related-concept]]

Tagging Strategy

Use consistent hashtags across documents:

• Languages: #rust, #python, #typescript
• Categories: #async, #error, #testing, #security
• Frameworks: #tokio, #fastapi, #react
• Patterns: #pattern, #antipattern, #refactoring

Cross-References

Link related documents using [[wiki-style]] links:

## See Also

- [[async-patterns]] - Async programming patterns
- [[error-handling]] - Error handling strategies
- [[testing]] - Testing approaches

The knowledge graph will create edges between linked concepts.

Integration with Vibe-Rules

This context library complements vibe-rules:

• Context Library: Background knowledge, architecture, references
• Vibe-Rules: Actionable coding rules and patterns

Both are indexed together into the knowledge graph, allowing semantic search across all content.

Token Management

To track token usage:

1. Add metadata to document frontmatter:

---
tokens: 1500
source: OpenAI API docs
last_updated: 2025-01-20
---

# Document content...

2. Query document stats:

# Get indexing statistics
curl http://localhost:PORT/config | jq '.roles["Context Engineer"].kg'

Maintenance

Regular Updates

• Review and update documents quarterly
• Remove obsolete information
• Add new patterns as they emerge
• Update examples to match current best practices

Quality Checks

• Ensure all code examples compile/run
• Verify cross-references are valid
• Check that hashtags are consistent
• Validate document structure

Version Control

# Track changes
git add docs/context-library/
git commit -m "docs: add async cancellation pattern"

# Share with team
git push origin main

Examples

See existing context in:

• ../vibe-rules/ - Coding rules and patterns
• ../src/ - Project-specific documentation

Contributing

1. Follow the document structure template
2. Include working code examples
3. Use consistent hashtags
4. Cross-reference related documents
5. Test that examples work

See Also

• Conare Comparison - Feature comparison with Conare AI
• Knowledge Graph System - How indexing works
• Vibe Rules - Actionable coding rules