| name | moai-workflow-jit-docs |
| description | Enhanced Just-In-Time document loading system that intelligently discovers, loads, and caches relevant documentation based on user intent and project context. Use when users need specific documentation, when working with new technologies, when answering domain-specific questions, or when context indicates documentation gaps. |
| version | 3.0.0 |
| category | workflow |
| allowed-tools | Read, Grep, Glob, WebFetch, WebSearch |
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