Single tool 'mcp-reasoner' has a complete input schema with 7 parameters, all typed and constrained (enums, min/max bounds). However, the tool description is generic and lacks actionable guidance on when/why to use it. Parameter descriptions are present but minimal (10-30 chars each), below the 72-char baseline. No output schema is documented, LLMs cannot predict what the tool returns or chain results to downstream tools. The tool name 'mcp-reasoner' is a noun, not a verb; it should be 'reason' or 'run_reasoning' to signal the action. No error handling guidance visible. Overall: schema is solid, naming and descriptions are weak, output is undocumented.

• Rename tool from 'mcp-reasoner' to 'reason' or 'execute_reasoning' to follow verb_noun convention and signal the action to LLMs.
• Expand tool description to 150-250 chars: explain what reasoning strategies do, when to use each (beam_search for breadth, mcts for depth), and what the output contains (e.g., 'Returns a reasoning trace with selected paths and confidence scores').
• Document the output schema explicitly: 'Returns {reasoning_trace: string[], selected_paths: {path: string, confidence: 0-1}[], final_conclusion: string}' or similar.
• Enhance parameter descriptions to 50-100 chars each. E.g., 'thought': 'A single logical reasoning step (1-500 chars). Be concise, specific, and build on prior steps.' 'strategyType': 'beam_search explores multiple paths in parallel (good for breadth); mcts simulates outcomes (good for depth).'
• Add error handling guidance in tool description: 'If reasoning diverges or loops, reduce beamWidth, increase totalThoughts, or switch strategies. Returns error with recovery hint if max iterations exceeded.'