Server has 8 tools with basic schemas and descriptions, but significant gaps limit production readiness. All tools have descriptions (10-100 chars, mostly adequate) and input schemas with types. However, parameter descriptions are sparse or missing context. The 'generate' tool accepts an open-ended 'parameters' dict with no guidance on valid keys. Output schemas are undocumented, LLMs cannot predict response structure. Error handling is minimal (FalAPIError raised but not caught/guided). No pagination guidance for 'models' tool despite its own description warning against listing all at once. Tool naming is clear (verb_noun pattern), but composition could be tighter, 'result', 'status', 'cancel' require users to manage URLs from prior calls, increasing cognitive load.

• Document output schemas for all tools. For 'generate', specify: {response_url, status_url, cancel_url, ...}. For 'models', specify: {models: [{id, name, description, ...}], total, page}. This enables LLM planning.
• Replace 'parameters' dict in generate with explicit, typed parameters or a reference to the model's OpenAPI schema. Add description: 'Use the schema() tool first to see valid parameters for this model.'
• Wrap FalAPIError handling to return structured error responses with recovery hints. E.g., 'API key invalid. Ensure FAL_KEY environment variable is set.' or 'Model not found. Call search() to find available models.'
• Add a 'list_pending_requests' or 'get_request_status' tool to help agents track queued jobs without manually managing URLs. Alternatively, return a request_id from generate and accept it in result/status/cancel.
• Enforce pagination in models tool: add default limit=20, max_results=100, and document: 'Returns paginated results. Use page and total to iterate. Default limit is 20 to avoid context overflow.'