Usercall MCP demonstrates solid definition quality with consistent verb-noun naming, complete parameter schemas using Zod, and comprehensive descriptions. All 5 tools are explicitly registered with clear intent. Tool names are action-oriented (create_study, update_study, get_study_status, get_study_results, delete_study) and follow the verb_noun pattern. Descriptions range 195-340 chars, which is within the 10-1024 optimal range. Schemas are complete with type constraints, enums, and range limits. However, there are gaps in output documentation, the return types are not formally documented for agents to understand expected response structure. Error handling for the 402 insufficient-credits case is explicit (special UsercallApiError handling with checkout_url), which is good, but generic API errors lack actionable recovery guidance. Parameter descriptions could be more LLM-optimized with explicit constraint statements (e.g., 'must be 1-200' rather than relying on schema minLength/maxLength). The _note appending pattern (create_study, update_study) is a reasonable attempt at guidance but is informal and not a substitute for formal output schema documentation.

• Formally document the response schema for each tool. Use JSDoc or TypeScript interfaces to declare field names, types, and nesting. Example: create_study returns { study_id: string; interview_link: string; ... }. This enables agents to understand and chain tool calls.
• Enhance error messages to guide recovery. For 404 (study not found), return 'Study not found. Verify the study_id. Call list_studies() to see available studies.' (requires adding list_studies tool). For 400 (bad request), parse the API response and extract the specific validation error.
• Expand parameter descriptions to 80-150 chars with concrete constraints and context. Example: 'Business context for the study (e.g., product name, market segment, user pain point). Distinguishes this study from key_research_goal. Max 2000 chars.'
• Add a confirmation pattern for delete_study. Introduce an optional 'confirm_deletion' parameter that defaults to false. When false, return a message: 'Study deletion would release X credits. Call again with confirm_deletion: true to proceed.' This prevents accidental deletions.
• Document the format of study_media.url. Clarify whether Figma prototype URLs must be publicly shareable and what happens if the URL becomes inaccessible during interviews.
• Provide pagination guidance for tools that may return large result sets (e.g., if future versions add list_studies). Describe how to handle results > 100 items and what the response structure is for cursor/offset pagination.