Strong foundation with 12 well-named tools using consistent verb_noun patterns (list_, get_, create_, update_, transition_, claim_, add_, move_, sync_). All tools have descriptions (avg 120 chars, within 10-1024 range). Input schemas are complete with Pydantic models providing type definitions. However, output schemas are not documented, responses are inferred as dicts without field specifications. Parameter descriptions are present but some lack constraint details (e.g., 'to_state' accepts 7 values but no enum). Error handling is minimal, no recovery guidance or categorization. Security is adequate (no secrets in params) but lacks permission gates and audit trail documentation.

• Document output schemas for all tools. Specify fields returned by create_task (task_id, created_at, etc.), list_tasks (tasks[], total_count, next_cursor), and claim_next_task (task_id, project_id, status). Use TypedDict or Pydantic models in docstrings.
• Convert constrained parameters to enums. Change 'to_state' to enum[ready|claimed|in_progress|review|done|blocked|cancelled], 'note_type' to enum[success|blocked|retryable_failure|unrecoverable], 'view_kind' to enum[list|gantt|table|kanban].
• Add constraint details to parameter descriptions. E.g., 'limit: Maximum tasks to return (1-100, default 50)', 'priority: Priority level (0-3, where 0=low, 3=urgent)', 'due_date: ISO 8601 date string (YYYY-MM-DD)'.
• Implement error handling with recovery guidance. Return structured errors: {error: string, code: string, retryable: bool, suggestion: string}. E.g., 'Project not found. Try list_projects() to find valid project_id.'
• Add permission gates and audit trail documentation. Document required scopes (read:tasks, write:tasks, admin:tasks) for each tool. Add logging guidance: 'Tool logs actor, task_id, old_state, new_state, timestamp to audit trail.'

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

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