Server has 11 well-named tools with consistent verb_noun patterns (create_, add_, revise_, delete_, get_, summarize_, branch_, verify_, list_). All tools have descriptions (avg ~80 chars, within baseline 34-392). Input schemas are present with typed parameters and descriptions. However, output schemas are not formally documented, responses are inferred from code. Error handling uses ToolError but lacks recovery guidance. No parameter constraints (enums, ranges) visible. Descriptions are functional but brief, missing WHEN/WHY context that LLMs need for tool selection. No examples of parameter validation or dependency hints.

• Add formal output schemas to all tool definitions. Use FastMCP's schema parameter to document return types (e.g., {chain_id: string, topic: string, created_at: string}).
• Expand descriptions to 100-200 chars with WHEN/WHY context. E.g., 'Add a thought to extend the reasoning chain. Use this after create_thought_chain to build sequential steps. If you need to change an existing thought, use revise_thought instead.'
• Add parameter constraints: step_number (min: 1), limit (min: 1, max: 100), offset (min: 0). Use JSON Schema minimum/maximum and enum fields.
• Enhance error messages with recovery guidance. E.g., raise ToolError(f'Chain {chain_id} not found. Available chains: {[c.id for c in available]}. Call list_chains() to discover.').
• Implement dry-run or confirmation for delete_thought and delete_chain. Add optional 'confirm' parameter or return a confirmation token that must be passed to execute the deletion.