Server has 4 tools with mixed quality. Two static tools (get_task, check_pricing) have reasonable descriptions but lack detailed parameter documentation. Two dynamic tools (dynamic_asynchronous_endpoints, dynamic_synchronous_endpoints) are problematic: their schemas are generated at runtime from contract.json, making them invisible in static analysis. Parameter descriptions are minimal or absent. No error handling guidance. No tool annotations. Output schemas undocumented. Naming is acceptable but descriptions fall short of LLM-optimization standards (target 50-200 chars; most are 80-120 chars). This is a D-grade server with significant gaps in schema completeness and parameter clarity.

• Document output schemas for all tools. Define the structure of jsonText() responses (e.g., {task_id: string, status: string, task: object}) so LLMs know what fields to expect.
• Add enum constraints for 'action' parameters. Replace free-form strings with z.enum() listing valid endpoint names. Include descriptions like 'Asynchronous endpoint where the task was created (e.g., flux_pro, flux_realism).'
• Enhance error messages with recovery guidance. Instead of 'Unsupported RunAPI service/action/model combination', return 'Unsupported model. Available models: flux-pro, flux-realism. Call check_pricing() to verify model availability.'
• Add tool annotations. Use server.tool() with metadata: readOnlyHint for get_task and check_pricing; destructiveHint for dynamic_synchronous_endpoints if they modify state.
• Document dynamic tool schemas statically. Generate a schema registry or include contract.json schema definitions in the server definition so clients can introspect available endpoints before runtime.