Quick Reference (30 seconds)
Purpose: Load relevant documentation on-demand based on user intent and context.
Primary Tools:
- WebSearch: Find latest documentation and resources online
- WebFetch: Retrieve specific documentation pages
- Context7 MCP: Access official library documentation (when available)
- Read, Grep, Glob: Search local project documentation
Trigger Patterns:
- User asks specific technical questions
- Technology keywords detected in conversation
- Domain expertise required for task completion
- Implementation guidance needed
Implementation Guide
Intent Detection
The system recognizes documentation needs through several patterns:
Question-Based Triggers:
- When users ask specific implementation questions (e.g., "how do I implement JWT authentication?")
- When users seek best practices or optimization guidance
- When troubleshooting questions arise
Technology-Specific Triggers:
- Detection of framework names: FastAPI, React, PostgreSQL, Docker, Kubernetes
- Detection of library names: pytest, TypeScript, GraphQL, Redis
- Detection of tool names: npm, pip, cargo, maven
Domain-Specific Triggers:
- Authentication and authorization topics
- Database and data modeling discussions
- Performance optimization inquiries
- Security-related questions
Pattern-Based Triggers:
- Implementation requests: "implement", "create", "build"
- Architecture discussions: "design", "structure", "pattern"
- Troubleshooting: "debug", "fix", "error", "not working"
Documentation Sources
The system retrieves documentation from multiple sources in priority order:
Local Project Documentation (Highest Priority):
- Check.moai/docs/ for project-specific documentation
- Check.moai/specs/ for requirements and specifications
- Check README.md for project overview
- Check docs/ directory for comprehensive documentation
Official Documentation Sources:
- Use WebFetch to retrieve official framework documentation
- Use Context7 MCP tools when available for library documentation
- Access technology-specific official websites
Community Resources:
- Use WebSearch to find high-quality tutorials
- Search for Stack Overflow solutions with high vote counts
- Find GitHub discussions for specific issues
Real-Time Web Research:
- Use WebSearch with current year for latest information
- Search for recent best practices and updates
- Find new features and deprecation notices
Loading Strategies
Intent Analysis Process:
- Identify technologies mentioned in user request
- Determine domain areas relevant to the question
- Classify question type (implementation, troubleshooting, conceptual)
- Assess complexity to determine documentation depth needed
Source Prioritization:
- If local documentation exists: Load project-specific docs first
- If official documentation available: Retrieve authoritative sources
- If implementation examples needed: Search community resources
- If latest information required: Perform web research
Context-Aware Caching:
- Cache retrieved documentation within session
- Maintain relevance based on current conversation context
- Remove outdated content when context shifts
- Prioritize frequently accessed documentation
Quality Assessment
Content Quality Evaluation:
- Authority: Official sources receive highest trust
- Recency: Content within 12 months preferred for fast-moving technologies
- Completeness: Documentation with examples ranked higher
- Relevance: Match between content and user intent
Relevance Ranking:
- Calculate match between documentation content and user question
- Weight authority (30%), recency (25%), completeness (25%), relevance (20%)
- Return highest-scoring documentation first
- Indicate confidence level in retrieved information
Practical Workflows
Authentication Implementation Workflow:
- When user asks about authentication: Detect technologies (e.g., FastAPI, JWT)
- Identify domains: authentication, security
- Load FastAPI security documentation via WebFetch
- Search for JWT best practices via WebSearch
- Provide comprehensive guidance with source attribution
Database Optimization Workflow:
- When user asks about query performance: Detect database technology
- Identify domain: performance, optimization
- Load official database documentation
- Search for optimization guides and tutorials
- Provide actionable recommendations with sources
New Technology Adoption Workflow:
- When user introduces unfamiliar technology: Detect technology name
- Load official getting started documentation
- Search for migration guides if applicable
- Find integration patterns with existing stack
- Provide strategic adoption guidance
Error Handling
Network Failures:
- If web search fails: Fall back to cached content
- If WebFetch fails: Use local documentation if available
- Indicate partial results when some sources unreachable
Content Quality Issues:
- If retrieved content seems outdated: Search for newer sources
- If relevance unclear: Ask user for clarification
- If conflicting information found: Present multiple sources with dates
Relevance Mismatches:
- If initial search yields poor results: Refine search query
- If user context unclear: Request clarification before loading
- If documentation gap exists: Acknowledge limitation
Performance Optimization
Caching Strategy:
- Maintain session-level cache for frequently accessed docs
- Keep project-specific documentation in memory
- Evict stale content based on access time
Efficient Loading:
- Load documentation only when explicitly needed
- Avoid preloading all possible documentation
- Use targeted searches rather than broad queries
Batch Processing:
- Combine related searches when possible
- Group documentation requests by technology
- Process multiple sources in parallel when appropriate
Advanced Patterns
Multi-Source Aggregation:
- Combine official documentation with community examples
- Cross-reference multiple authoritative sources
- Synthesize comprehensive answers from diverse materials
Context Persistence:
- Remember documentation loaded earlier in conversation
- Avoid redundant loading of same documentation
- Build cumulative knowledge through session
Proactive Loading:
- Anticipate documentation needs based on conversation flow
- Pre-load related topics when discussing complex features
- Suggest relevant documentation before user asks
Works Well With
Agents:
- workflow-docs: Documentation generation
- core-planner: Documentation planning
- workflow-spec: SPEC documentation
Skills:
- moai-docs-generation: Documentation generation
- moai-workflow-docs: Documentation validation
- moai-library-nextra: Nextra documentation
Commands:
- /moai:3-sync: Documentation synchronization
- /moai:9-feedback: Documentation improvements