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
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1---2name: modu-ai-moai-adk-moai-workflow-jit-docs3description: Quick Reference (30 seconds)4---56## Quick Reference (30 seconds)78Purpose: Load relevant documentation on-demand based on user intent and context.910Primary Tools:1112- WebSearch: Find latest documentation and resources online13- WebFetch: Retrieve specific documentation pages14- Context7 MCP: Access official library documentation (when available)15- Read, Grep, Glob: Search local project documentation1617Trigger Patterns:1819- User asks specific technical questions20- Technology keywords detected in conversation21- Domain expertise required for task completion22- Implementation guidance needed2324## Implementation Guide2526### Intent Detection2728The system recognizes documentation needs through several patterns:2930Question-Based Triggers:3132- When users ask specific implementation questions (e.g., "how do I implement JWT authentication?")33- When users seek best practices or optimization guidance34- When troubleshooting questions arise3536Technology-Specific Triggers:3738- Detection of framework names: FastAPI, React, PostgreSQL, Docker, Kubernetes39- Detection of library names: pytest, TypeScript, GraphQL, Redis40- Detection of tool names: npm, pip, cargo, maven4142Domain-Specific Triggers:4344- Authentication and authorization topics45- Database and data modeling discussions46- Performance optimization inquiries47- Security-related questions4849Pattern-Based Triggers:5051- Implementation requests: "implement", "create", "build"52- Architecture discussions: "design", "structure", "pattern"53- Troubleshooting: "debug", "fix", "error", "not working"5455### Documentation Sources5657The system retrieves documentation from multiple sources in priority order:5859Local Project Documentation (Highest Priority):6061- Check .moai/docs/ for project-specific documentation62- Check .moai/specs/ for requirements and specifications63- Check README.md for project overview64- Check docs/ directory for comprehensive documentation6566Official Documentation Sources:6768- Use WebFetch to retrieve official framework documentation69- Use Context7 MCP tools when available for library documentation70- Access technology-specific official websites7172Community Resources:7374- Use WebSearch to find high-quality tutorials75- Search for Stack Overflow solutions with high vote counts76- Find GitHub discussions for specific issues7778Real-Time Web Research:7980- Use WebSearch with current year for latest information81- Search for recent best practices and updates82- Find new features and deprecation notices8384### Loading Strategies8586Intent Analysis Process:8788- Identify technologies mentioned in user request89- Determine domain areas relevant to the question90- Classify question type (implementation, troubleshooting, conceptual)91- Assess complexity to determine documentation depth needed9293Source Prioritization:9495- If local documentation exists: Load project-specific docs first96- If official documentation available: Retrieve authoritative sources97- If implementation examples needed: Search community resources98- If latest information required: Perform web research99100Context-Aware Caching:101102- Cache retrieved documentation within session103- Maintain relevance based on current conversation context104- Remove outdated content when context shifts105- Prioritize frequently accessed documentation106107### Quality Assessment108109Content Quality Evaluation:110111- Authority: Official sources receive highest trust112- Recency: Content within 12 months preferred for fast-moving technologies113- Completeness: Documentation with examples ranked higher114- Relevance: Match between content and user intent115116Relevance Ranking:117118- Calculate match between documentation content and user question119- Weight authority (30%), recency (25%), completeness (25%), relevance (20%)120- Return highest-scoring documentation first121- Indicate confidence level in retrieved information122123### Practical Workflows124125Authentication Implementation Workflow:126127- When user asks about authentication: Detect technologies (e.g., FastAPI, JWT)128- Identify domains: authentication, security129- Load FastAPI security documentation via WebFetch130- Search for JWT best practices via WebSearch131- Provide comprehensive guidance with source attribution132133Database Optimization Workflow:134135- When user asks about query performance: Detect database technology136- Identify domain: performance, optimization137- Load official database documentation138- Search for optimization guides and tutorials139- Provide actionable recommendations with sources140141New Technology Adoption Workflow:142143- When user introduces unfamiliar technology: Detect technology name144- Load official getting started documentation145- Search for migration guides if applicable146- Find integration patterns with existing stack147- Provide strategic adoption guidance148149### Error Handling150151Network Failures:152153- If web search fails: Fall back to cached content154- If WebFetch fails: Use local documentation if available155- Indicate partial results when some sources unreachable156157Content Quality Issues:158159- If retrieved content seems outdated: Search for newer sources160- If relevance unclear: Ask user for clarification161- If conflicting information found: Present multiple sources with dates162163Relevance Mismatches:164165- If initial search yields poor results: Refine search query166- If user context unclear: Request clarification before loading167- If documentation gap exists: Acknowledge limitation168169### Performance Optimization170171Caching Strategy:172173- Maintain session-level cache for frequently accessed docs174- Keep project-specific documentation in memory175- Evict stale content based on access time176177Efficient Loading:178179- Load documentation only when explicitly needed180- Avoid preloading all possible documentation181- Use targeted searches rather than broad queries182183Batch Processing:184185- Combine related searches when possible186- Group documentation requests by technology187- Process multiple sources in parallel when appropriate188189## Advanced Patterns190191Multi-Source Aggregation:192193- Combine official documentation with community examples194- Cross-reference multiple authoritative sources195- Synthesize comprehensive answers from diverse materials196197Context Persistence:198199- Remember documentation loaded earlier in conversation200- Avoid redundant loading of same documentation201- Build cumulative knowledge through session202203Proactive Loading:204205- Anticipate documentation needs based on conversation flow206- Pre-load related topics when discussing complex features207- Suggest relevant documentation before user asks208209---210211## Works Well With212213Agents:214215- workflow-docs: Documentation generation216- core-planner: Documentation planning217- workflow-spec: SPEC documentation218219Skills:220221- moai-docs-generation: Documentation generation222- moai-workflow-docs: Documentation validation223- moai-library-nextra: Nextra documentation224225Commands:226227- /moai:3-sync: Documentation synchronization228- /moai:9-feedback: Documentation improvements229230---231> Converted and distributed by [TomeVault](https://tomevault.io/claim/modu-ai) — claim your Tome and manage your conversions.232<!-- tomevault:4.0:skill_md:2026-04-11 -->