ws-dottie

# Zod Descriptions Enhancement Project ## Overview This project aims to comprehensively review and enhance Zod descriptions across all WSDOT and WSF API implementations to ensure they are detailed, accurate, and useful for MCP server feature detection and human developers. ## Objectives 1. **Consistency**: Ensure all APIs have comprehensive, detailed descriptions at the same level of quality 2. **Accuracy**: All information must be verified against official documentation and API responses 3. **Completeness**: Include domain context, concrete examples, and usage guidance 4. **MCP Server Ready**: Descriptions should enable proper feature detection and usage guidance ## Process ### Phase 1: Research & Verification - Review official documentation for each API (user will provide specific links per API) - Use curl with WSDOT_ACCESS_TOKEN to verify actual API responses - Cross-reference with existing schema implementations - Document discrepancies between docs and actual behavior ### Phase 2: Enhancement - Work through APIs alphabetically, one at a time - Wait for user review after each API completion - Enhance descriptions with: - Domain context focused on specific API endpoint - Concrete examples from actual curl results only - Usage patterns and common scenarios - Nullability and edge cases - Relationships to other data ### Phase 3: Validation - Verify enhanced descriptions match actual API behavior - Test with curl to confirm examples work - Ensure consistency across all APIs ## API Scope ### WSDOT APIs (12 total) 1. wsdot-border-crossings 2. wsdot-bridge-clearances 3. wsdot-commercial-vehicle-restrictions 4. wsdot-highway-alerts 5. wsdot-highway-cameras 6. wsdot-mountain-pass-conditions 7. wsdot-toll-rates 8. wsdot-traffic-flow 9. wsdot-travel-times 10. wsdot-weather-information 11. wsdot-weather-information-extended 12. wsdot-weather-stations ### WSF APIs (4 total) 1. wsf-fares 2. wsf-schedule 3. wsf-terminals 4. wsf-vessels ## Quality Standards ### Required Elements for Each Field - **Business Purpose**: Why this field exists and what it represents - **Domain Context**: How it fits into the transportation/ferry ecosystem - **Examples**: Concrete values from real API responses - **Constraints**: Valid ranges, formats, nullability (only if explicitly documented) - **Usage**: How developers typically use this field - **Relationships**: How it relates to other fields/data ### Style Guidelines - Use active voice and present tense - Be specific and concrete, not vague - Include real examples from verified sources only - Explain domain-specific terminology - Document known edge cases and API behaviors only if explicitly documented - **Nullability Approach**: Do not speculate about when nullable fields are null - Remove generic "may be null" statements (redundant with type) - Only include specific nullability conditions if explicitly documented in official sources - Use concrete examples from verified API responses rather than assumptions ## Validation Process For each API: 1. Review official documentation (primary: "Docs" column, secondary: "REST" column) 2. Use curl to verify actual API behavior 3. Compare API response to existing schema 4. Update descriptions to match reality 5. Add domain context from official WSDOT/WSF websites 6. Test enhanced descriptions for clarity ## Success Criteria - All Zod descriptions are comprehensive and detailed (minimum 3-5 sentences per field) - Information is verified against official sources (no assumptions or speculation) - Examples are concrete and accurate (from actual API responses, not invented) - Domain context is properly explained (specific to each API's transportation role) - Descriptions enable proper MCP server feature detection (clear business purpose) - Human developers can understand and use the APIs effectively (practical examples) - **Measurable**: Each field description contains at least one concrete example from real API data - **Measurable**: All function/hook descriptions include working code examples with realistic parameters - **Measurable**: Schema descriptions explain the business purpose and typical use cases ## Current Status & Completed Work ### WSF Fares API Enhancement - Phase 1 Complete ✅ **Completed Endpoints:** - ✅ `getFareLineItems` - Comprehensive fare endpoint - ✅ `getFareLineItemsBasic` - Streamlined fare endpoint - ✅ `getFareLineItemsVerbose` - Bulk fare endpoint **Quality Achievements:** - **Real API Data Integration**: Used curl to verify actual WSF API responses and terminal data - **Business Context**: Detailed explanations of fare structures, passenger categories, and vehicle classifications - **Concrete Examples**: Real terminal IDs (Seattle=7), actual fare amounts ($10.25), working code patterns - **Domain Expertise**: Puget Sound ferry operations, seasonal pricing, commuter passes, multi-ride cards ## Documentation Standards Established ### JSDoc vs Zod Schema Descriptions: Clear Separation #### **JSDoc Comments** (For Software Engineers) - **Purpose**: Technical documentation for developers reading source code - **Content**: Implementation details, parameter descriptions, practical usage examples - **Style**: Lean, technical, focused on "how to use" - **Examples**: Code samples showing function calls and data manipulation - **Length**: Concise, respecting 80-column limit #### **Zod Schema Descriptions** (For API Consumers) - **Purpose**: Business-focused documentation for API consumers and MCP server feature detection - **Content**: Business purpose, domain context, real-world usage patterns, concrete examples - **Style**: Comprehensive, business-focused, explaining "what the data represents" - **Examples**: Real API response values, business scenarios, usage patterns - **Length**: Detailed, no length restrictions ## Lessons Learned from WSF Fares Implementation ### Technical Enhancement Insights #### **1. Zod Schema Descriptions Are Primary Deliverable** - **Key Lesson**: Zod `.describe()` calls are more valuable than JSDoc comments for developer experience - **Impact**: Focus enhancement efforts on schema descriptions rather than JSDoc expansion - **Recommendation**: "Prioritize Zod schema enhancement with business context, examples, and usage guidance" #### **2. Domain Research Is Critical Pre-Work** - **Key Lesson**: Without deep business domain knowledge, descriptions become generic and unhelpful - **Impact**: WSF fares required understanding of terminal networks, seasonal pricing, collection methods - **Recommendation**: "Conduct thorough domain research using official documentation and API responses before enhancement" #### **3. Parameter Interdependencies Must Be Documented** - **Key Lesson**: Complex APIs have parameter relationships (arrays that must match, terminal relationships) - **Impact**: WSF fare calculations require understanding of fareLineItemIDs ↔ quantities relationships - **Recommendation**: "Document parameter interdependencies and validation rules within schema descriptions" ### Process Refinements #### **4. Build on Established Patterns** - **Key Lesson**: Reference existing codebase patterns ensures consistency - **Impact**: WSDOT implementations provided templates for WSF enhancement approach - **Recommendation**: "Reference and extend existing API implementation patterns rather than creating new ones" #### **5. Comprehensive Schema Coverage Required** - **Key Lesson**: Every schema level needs enhancement (parameters, outputs, fields, arrays, objects) - **Impact**: Enhanced ALL schema levels for complete API documentation - **Recommendation**: "Enhance ALL schema levels: input parameters, output schemas, individual fields, array containers, and object wrappers" ### Quality Standards Evolution #### **6. JSDoc vs Zod String Boundaries** - **Key Lesson**: JSDoc comments have 80-column limit, Zod strings have no length restrictions - **Impact**: JSDoc must be manually formatted, Zod descriptions can be comprehensive - **Recommendation**: "Maintain 80-column limit for JSDoc comments; Zod .describe() strings have no length restrictions" #### **7. Hook Comments Should Be Concise** - **Key Lesson**: Hook comments should follow existing patterns, not be verbose re-explanations - **Impact**: Simplified hook documentation while enhancing schema descriptions - **Recommendation**: "Keep hook JSDoc comments brief and consistent with existing codebase style" #### **8. Business Use Cases Belong in Zod, Not JSDoc** - **Key Lesson**: Business-focused bullet points ("essential for...") don't belong in technical JSDoc - **Impact**: JSDoc should serve software engineers with technical details; Zod serves API consumers - **Recommendation**: "Remove business use case lists from JSDoc; keep them in Zod descriptions for MCP server consumption" ### Domain-Specific Insights #### **9. Transportation APIs Have Complex Business Rules** - **Key Lesson**: WSF has complex terminal relationships, seasonal schedules, fare collection methods - **Impact**: Required documenting 15+ terminals, seasonal variations, collection methodologies - **Recommendation**: "For transportation APIs, document terminal networks, seasonal variations, and collection methodologies" #### **10. Embed Business Rules in Schema Descriptions** - **Key Lesson**: Business rules like WSF's $0.05 rounding policy are valuable in descriptions - **Impact**: Enhanced developer understanding of fare calculation constraints - **Recommendation**: "Embed relevant business rules and policies directly in schema descriptions" ### Implementation Results #### **WSF Fares API Enhancement Outcomes** - ✅ **Complete Coverage**: First 3 endpoints enhanced with comprehensive descriptions - ✅ **Domain Accuracy**: Real terminal examples, fare amounts, route relationships - ✅ **Quality Consistency**: Followed WSDOT patterns while adapting to WSF domain - ✅ **Developer Value**: Enhanced schemas provide clear business purpose and usage guidance - ✅ **Validation Ready**: All parameter relationships and business rules documented ## Enhancement Patterns & Quality Standards ### Enhanced Field Description Pattern (Current Standard) For each Zod field, follow this structure: 1. **Business Purpose** (1 sentence): What the field represents and why it exists 2. **Domain Context** (1-2 sentences): How it fits into transportation/ferry ecosystem 3. **Concrete Examples** (1-2 examples): Real values from actual API responses 4. **Technical Details** (1 sentence): Constraints, relationships, business rules 5. **Usage Guidance** (1 sentence): How developers use this field in applications ### Enhanced Function Description Pattern (Current Standard) 1. **Technical Overview**: What the function does and what it returns 2. **Parameter Details**: Type and purpose of each parameter 3. **Usage Examples**: Practical code samples with real data 4. **Error Handling**: What exceptions might be thrown 5. **Business Context**: How the data fits into the domain (in Zod descriptions) ### JSDoc Best Practices (For Engineers) - Keep concise and technical - Focus on "how to use" not "what it's for" - Include practical code examples - Respect 80-column width limit - Avoid business use case bullet points ### Zod Schema Best Practices (For API Consumers) - Comprehensive business context and domain knowledge - Real API response examples and values - Usage patterns and scenarios - Business rules and constraints - No length restrictions for thorough documentation ## Enhancement Patterns (Based on WSDOT Experience) ### Field Description Enhancement Pattern For each Zod field, follow this structure: 1. **Business Purpose** (1 sentence): What the field represents and why it exists 2. **Domain Context** (1-2 sentences): How it fits into transportation/ferry operations 3. **Concrete Examples** (1-2 examples): Real values from actual API responses 4. **Constraints/Ranges** (1 sentence): Valid ranges, formats, special conditions 5. **Usage Guidance** (1 sentence): How developers typically use this field ### Function Enhancement Pattern 1. **Enhanced Description**: Add business purpose and domain context 2. **Realistic Examples**: Show actual usage with concrete parameters 3. **Error Handling**: Mention what exceptions might be thrown 4. **Return Value Context**: Explain what the data represents ### WSF API Specific Considerations - **Different Documentation Sources**: WSF APIs may have different documentation patterns than WSDOT - **Ferry Domain Knowledge**: Focus on maritime operations, vessel schedules, terminal operations - **Passenger vs. Vehicle Context**: Consider both passenger and vehicle transportation needs - **Real-time vs. Static Data**: Some ferry data is schedule-based while other is real-time - **Geographic Complexity**: Multiple terminals, routes, and vessel types to consider ## Risk Mitigation - Never invent or assume facts (use only verified API responses) - Always verify against official documentation and API responses - Document any discrepancies found between documentation and reality - Use concrete examples from actual API calls (not assumptions) - Consult getting-started guide for documentation hierarchy - **Critical**: Never speculate about nullability - only document if explicitly stated in official sources ## Guidelines for Future WSF API Enhancement Agents ### Pre-Work Preparation 1. **Review WSDOT Patterns**: Study the enhanced WSDOT APIs to understand the quality standard and enhancement patterns 2. **Understand WSF Domain**: Familiarize yourself with ferry operations, terminals, schedules, and vessel types 3. **Review Completed WSF Fares Endpoints**: Use getFareLineItems, getFareLineItemsBasic, and getFareLineItemsVerbose as quality benchmarks 4. **Identify Documentation Sources**: Work with user to locate official WSF documentation and API endpoints 5. **Test API Access**: Confirm you can access WSF APIs and understand their structure 6. **Use curl data**: Always use curl to get current data from each endpoint before you enhance any comments or descriptions. Provide specific, data-driven, evidence-based comments and examples for Zod "describe" annotations. 7. **Use correct format**: Comments should have a maximum width of 80 characters. String values, such as those inside of function calls like describe(), should never be broken apart and concatenated. These must each remain one unified string, since the IDE will format them appropriately. 8. **Follow established patterns**: Use the completed WSF fares endpoints as your primary model for quality and style ## Terminal usage Note these annual ridership statics for each terminal. In Zod describe annotations concerning terminals, you should generally prefer examples among the higher-ranked terminals, while mixing it up. Rank Terminal Name 2023 Annual Ridership (approx.) 1 Seattle 4,500,000 2 Bainbridge Island 3,200,000 3 Edmonds 2,600,000 4 Kingston 2,600,000 5 Mukilteo 2,500,000 6 Clinton 2,500,000 7 Fauntleroy 2,100,000 8 Vashon Island 1,500,000 9 Bremerton 1,300,000 10 Southworth 1,100,000 11 Anacortes 1,000,000 12 Friday Harbor 400,000 13 Orcas Island 350,000 14 Lopez Island 250,000 15 Shaw Island 200,000 16 Point Defiance 400,000 17 Tahlequah 400,000 18 Coupeville 200,000 19 Port Townsend 200,000 ## Vessel ridership Note these annual ridership statistics for each vessel. In Zod describe annotations concerning vessels, you should generally prefer examples among the higher-ranked vessels, while mixing it up. Rank Vessel Name 2023 Annual Ridership (approx.) Primary Route(s) 1 Wenatchee 2,200,000 Seattle–Bainbridge 2 Tacoma 2,200,000 Seattle–Bainbridge 3 Puyallup 2,000,000 Edmonds–Kingston 4 Spokane 2,000,000 Edmonds–Kingston 5 Suquamish 1,300,000 Mukilteo–Clinton 6 Tokitae 1,200,000 Mukilteo–Clinton 7 Kaleetan 1,000,000 Seattle–Bremerton 8 Chimacum 1,000,000 Seattle–Bremerton 9 Issaquah 900,000 Fauntleroy–Vashon–Southworth 10 Cathlamet 900,000 Fauntleroy–Vashon–Southworth 11 Kitsap 900,000 Fauntleroy–Vashon–Southworth 12 Kittitas 800,000 Anacortes–San Juan Islands 13 Samish 800,000 Anacortes–San Juan Islands 14 Yakima 800,000 Anacortes–San Juan Islands 15 Sealth 700,000 Vashon–Pt. Defiance, San Juans 16 Tillikum 400,000 Anacortes–San Juan Islands 17 Chetzemoka 200,000 Coupeville–Port Townsend 18 Salish 200,000 Coupeville–Port Townsend ### WSF API Scope (Alphabetical Order) 1. **wsf-fares** - Pricing and fare information for ferry services 2. **wsf-schedule** - Sailing schedules and departure times 3. **wsf-terminals** - Terminal information and facilities 4. **wsf-vessels** - Vessel information and capabilities ### Enhancement Process for Each WSF API 1. **Initial Assessment**: Review current Zod schemas and identify enhancement opportunities 2. **API Exploration**: Use appropriate methods to explore actual API responses (may not have direct curl access) 3. **Documentation Review**: Cross-reference with official WSF documentation and website content 4. **Field-by-Field Enhancement**: Apply the established pattern to each Zod field 5. **Function Enhancement**: Improve function and hook descriptions with realistic examples 6. **User Review**: Submit each completed API for user feedback before proceeding ### Key WSF Considerations - **Maritime Context**: Focus on ferry operations, vessel capacities, terminal operations - **Schedule Complexity**: Consider recurring schedules vs. real-time updates - **Geographic Scope**: Multiple terminals across Puget Sound with different capabilities - **Passenger vs. Vehicle**: Different considerations for passenger and vehicle transportation - **Weather Dependencies**: How weather affects ferry operations and schedules ### Testing and Validation - **API Response Verification**: Confirm descriptions match actual API behavior - **Cross-Reference Documentation**: Ensure alignment with official WSF sources - **Realistic Examples**: Use actual ferry routes, terminal names, and vessel information - **Domain Accuracy**: Verify all maritime and ferry terminology is correct ### Success Metrics - **Quality Standard**: Match or exceed the detail level of enhanced WSDOT APIs - **Domain Expertise**: Demonstrate understanding of ferry operations and terminology - **Concrete Examples**: Every field description contains real ferry data examples - **User Validation**: Each API approved by user before moving to next ## Next Steps: Remaining WSF Fares Endpoints ### Remaining WSF Fares Endpoints to Enhance Based on the current `/src/api/wsf-fares/` directory, the following endpoints still need enhancement: 1. **getFaresCacheFlushDate.ts** - Cache management endpoint 2. **getFaresTerminalMates.ts** - Terminal relationships endpoint 3. **getFaresTerminals.ts** - Terminal information endpoint 4. **getFaresValidDateRange.ts** - Date validation endpoint 5. **getFareTotals.ts** - Fare calculation endpoint 6. **getTerminalCombo.ts** - Terminal combination endpoint 7. **getTerminalComboVerbose.ts** - Detailed terminal combination endpoint ### Enhancement Priority Recommendations 1. **getFaresTerminals** - Foundational terminal data needed by other endpoints 2. **getFaresTerminalMates** - Terminal relationships critical for fare calculations 3. **getFaresValidDateRange** - Date validation needed for all date-based queries 4. **getFareTotals** - Complex fare calculation logic 5. **getTerminalCombo** & **getTerminalComboVerbose** - Route and terminal combination data 6. **getFaresCacheFlushDate** - Cache management (lower priority) ### Quality Control Checklist for Each Endpoint - [ ] **API Testing**: Use curl to verify actual endpoint behavior and response structure - [ ] **Parameter Validation**: Ensure all required parameters are properly documented - [ ] **Response Schema**: Verify schema matches actual API responses - [ ] **JSDoc Quality**: Technical, concise, focused on engineering usage - [ ] **Zod Descriptions**: Comprehensive business context with real examples - [ ] **Concrete Examples**: Use actual API response values, not invented data - [ ] **Domain Accuracy**: Verify all ferry terminology and business rules are correct - [ ] **Consistency**: Match the quality and style of completed WSF fares endpoints ## Agent Implementation Guide ### Pre-Implementation Checklist - [ ] **Study Completed Examples**: Review getFareLineItems, getFareLineItemsBasic, and getFareLineItemsVerbose as quality benchmarks - [ ] **API Testing**: Use curl to verify actual endpoint behavior and response structure before implementation - [ ] **Domain Research**: Understand the specific business context and use cases for the endpoint - [ ] **Integration Points**: Identify how this endpoint connects with other WSF endpoints ### Implementation Workflow 1. **API Exploration**: Test endpoint with curl, analyze response structure, document actual behavior 2. **JSDoc Enhancement**: Write concise, technical descriptions focused on engineering usage 3. **Zod Schema Enhancement**: Add comprehensive business context, concrete examples, and usage guidance 4. **Code Examples**: Include practical examples showing real-world usage patterns 5. **Cross-Reference Validation**: Ensure consistency with related endpoints ### Quality Control Checklist (Pre-Review) - [ ] **JSDoc Quality**: - No marketing bullet points ("essential for...") - Technical focus on how to use the endpoint - Practical code examples with real data - Concise but informative (respects 80-column limit) - [ ] **Zod Schema Quality**: - Business purpose clearly explained - Domain context integrated - Concrete examples from actual API responses - Technical constraints and relationships documented - Usage guidance for API consumers - [ ] **Consistency Checks**: - Follows established patterns from completed endpoints - Terminal IDs and examples match actual API data - Error handling consistent with existing patterns - Hook documentation matches function documentation style ### Common Implementation Pitfalls to Avoid #### **JSDoc Issues** - ❌ **Marketing-style bullet points**: "This endpoint is essential for travel planning, booking systems..." - ❌ **Generic descriptions**: "Retrieves data from the API" without specific technical details - ❌ **Missing practical examples**: Code samples that don't show realistic usage - ❌ **Business context in JSDoc**: Save business explanations for Zod descriptions #### **Zod Schema Issues** - ❌ **Assumed nullability**: "This field may be null" without verification - ❌ **Invented examples**: Using fake IDs or values not from actual API responses - ❌ **Missing business context**: Technical-only descriptions without domain knowledge - ❌ **Inconsistent terminology**: Not matching established patterns in other endpoints #### **General Issues** - ❌ **No API testing**: Implementing without verifying actual endpoint behavior - ❌ **Inconsistent examples**: Terminal IDs that don't match between related endpoints - ❌ **Missing integration context**: Not explaining how endpoint connects with others ### Success Metrics for Each Endpoint - [ ] **JSDoc provides clear technical guidance** for software engineers - [ ] **Zod descriptions enable** proper MCP server feature detection - [ ] **Concrete examples** use actual API response values - [ ] **Business context** is accurate and helpful for API consumers - [ ] **Integration points** are clearly documented - [ ] **Consistency** maintained with established patterns ### Integration Patterns to Maintain #### **Terminal Data Flow** ``` getFaresTerminals → getFaresTerminalMates → getFareLineItems ↓ ↓ ↓ Terminal List Route Connections Fare Calculations ``` #### **Data Relationships** - **Terminal IDs**: Must be consistent across all endpoints (Seattle=7, Bainbridge=3, etc.) - **Date Parameters**: All endpoints use same date validation from getFaresValidDateRange - **Error Handling**: Consistent error patterns and validation messages - **Caching Strategy**: Use getFaresCacheFlushDate for cache coordination ### Testing and Validation Requirements #### **API Response Verification** ```bash # Test with actual data before implementation curl -s "https://www.wsdot.wa.gov/ferries/api/fares/rest/terminals/2025-09-15?apiaccesscode=$WSDOT_ACCESS_TOKEN" | jq '.' ``` #### **Schema Validation** - Verify all examples use actual API response values - Test with edge cases (invalid dates, non-existent terminals) - Ensure error responses are properly documented #### **Cross-Endpoint Consistency** - Terminal IDs match between getFaresTerminals and getFaresTerminalMates - Date formats are consistent across all endpoints - Error handling patterns are uniform ## Timeline Continue with WSF fares endpoints systematically in priority order: 1. **getFaresValidDateRange** - Foundational date validation 2. **getFareTotals** - Complex fare calculations 3. **getTerminalCombo** & **getTerminalComboVerbose** - Route combinations 4. **getFaresCacheFlushDate** - Cache management Allow for review and feedback after each endpoint completion. Use the three enhanced endpoints (getFareLineItems, getFareLineItemsBasic, getFareLineItemsVerbose) as quality benchmarks for all future work.