Three tools are defined with descriptions and input schemas present. However, the server exhibits significant quality gaps. Tool names lack clear action verbs (decompose_prompt and compile_prompt are somewhat descriptive but less clear than verb_object patterns like 'parse_prompt' or 'generate_prompt'). Descriptions are present but brief (119-167 chars), lacking the critical context of WHEN to use each tool and what prerequisites exist. Most critically, parameter descriptions are minimal or absent, the 'prompt' parameter in decompose_prompt has a description, but blocks_json in compile_prompt has only a generic description of the JSON structure without explaining when/why to use it. No output schemas are documented anywhere, forcing LLMs to guess what fields will be returned. Error handling is not visible in the code excerpts. The server is HTTP-based (FastMCP), which is positive for transport, but lacks modern MCP protocol features like tool annotations, progress reporting, or error categorization.

• Add explicit output schemas for all tools. For decompose_prompt, document the structure of returned 'blocks' (e.g., [{type: string, content: string, label: string, ...}]). For compile_prompt, document the returned XML structure and token count field. For list_block_types, document the array of block type objects with 'name', 'description', etc.
• Expand parameter descriptions with format guidance. For 'blocks_json', specify: 'JSON-stringified array of block objects. Each block MUST have type (one of: role, objective, context, constraints, ...), content (string), and optional label/description fields. Invalid JSON or unknown block types will be rejected.'
• Rename tools for clarity: 'decompose_prompt' → 'parse_prompt' or 'analyze_prompt'; 'compile_prompt' → 'generate_prompt' or 'build_prompt'. This makes tool selection intent clearer to LLMs.
• Enhance tool descriptions with WHEN/WHY context. Example: 'decompose_prompt: Use this to analyze and structure an unformatted prompt into reusable blocks. Call this FIRST if you have a raw prompt you want to optimize. Returns a list of blocks that can be edited or passed directly to compile_prompt.'
• Document error cases and recovery paths. Add to both decompose_prompt and compile_prompt: 'On invalid input: returns 400 with message like "Invalid block type: xyz. Valid types are: role, objective, context, constraints, examples, output_format". On API key missing: falls back to keyword-based analysis (slower, less accurate).'
• Add input validation examples to parameter descriptions. For 'prompt' in decompose_prompt: 'The prompt text must be non-empty (min 10 chars, max 50000 chars) and contain recognizable instruction patterns. Prompts that are pure whitespace or gibberish will fail gracefully.'