Single tool 'sequentialthinking' has a well-structured Pydantic schema with comprehensive field descriptions and validation logic. However, the tool name lacks a clear action verb (should be 'process_thought' or 'add_thought'), and the description is generic. Schema is visible and typed, but output structure is not documented. No error handling guidance for LLMs. Validators are present but complex interdependencies (isRevision→revisesThought, branchFromThought→branchId) are not clearly surfaced in descriptions.

• Rename tool to 'process_thought' or 'add_thought' to start with a clear action verb. This helps LLMs parse intent from the name alone.
• Expand tool description to 100-150 chars explaining: (1) what it does (records a step in sequential reasoning), (2) when to use it (when breaking down complex problems), (3) what it returns (confirmation + thought ID for chaining).
• Document the output schema explicitly in the tool description or as a separate field. E.g., 'Returns: {thought_id: string, sequence_number: int, status: "recorded"|"revised"|"branched"}'.
• Add inline notes in parameter descriptions for interdependencies. E.g., for isRevision: 'If true, revisesThought MUST be set to a thought number < thoughtNumber.' For branchFromThought: 'If set, branchId MUST also be provided.'
• Implement structured error responses. Catch validation errors and return {error: string, recovery_hint: string, valid_values?: object} so LLMs can self-correct without retrying blindly.

Inferred effective spec: <=2025-11-25.

• Relies on Logging (deprecated) - log to stderr or use OpenTelemetry