This is a minimal proof-of-concept tool with critical deficiencies across naming, description, and schema quality. The single tool 'decompose_goal' has a basic description but lacks proper input/output schema documentation, parameter descriptions, and error handling. The implementation is purely stateless logic with no MCP server scaffolding visible, it appears to be a standalone Python client class, not an MCP server. No tool registration, no schema validation, no error guidance. This would not function as a production MCP server.

• Implement a proper MCP server scaffold (e.g., using mcp-sdk or similar) that exposes tools over STDIO, HTTP+SSE, or Streamable HTTP.
• Expand tool description to 150 - 250 characters. Include: what decomposition means, when to call this tool vs. other planning methods, and the structure of returned subtasks.
• Document the output schema explicitly: { 'subtask_plan': [string], 'estimated_steps': integer, 'dependencies': [{'task_id': string, 'depends_on': [string]}] } or similar.
• Add constraints to 'high_level_goal' parameter: min/max length, forbidden characters, examples of good goals ('Build a mobile app' vs bad goals like empty string or single char).
• Implement actual goal decomposition logic instead of a stub. Parse goal semantics, extract key nouns/verbs, and generate contextually relevant subtasks.
• Add error handling: validate input, return clear recovery guidance if input is invalid (e.g., 'Goal must be 10-500 characters, non-empty, and describe a concrete objective').
• Consider tool annotations (readOnlyHint, idempotentHint) to signal that this tool is safe to call multiple times and does not modify state.