The server demonstrates strong definition quality with detailed parameter schemas, clear descriptions, and thoughtful constraint handling. All 8 tools are explicitly registered with non-empty descriptions and well-formed Zod schemas. Naming follows verb_noun patterns consistently (list_tasks, get_task, register_human_request, etc.). Parameter types are declared via Zod with proper validation. However, output schemas are not explicitly documented in the tool descriptions, the LLM must infer response structure from the description text alone. Error handling descriptions are present but could be more actionable. Tool names and descriptions are generally 15-300+ chars, meeting baselines. The human-request tools show sophisticated constraint validation (task ID regex, version tracking, criteria uniqueness). Overall, this is a well-engineered server that would benefit from explicit output schema documentation.

• Add explicit output schema definitions to each tool description. Example: 'Returns: { tasks: [{ id, title, status, assigned_to }], total, has_more, next_offset }'. This eliminates guessing and enables confident downstream planning.
• Enhance error handling with recovery actions. For register_human_request, add: 'Returns 409 if task is already claimed, use cancel_human_request on the existing request first, then retry.'
• For list_tasks state enum, add brief explanations: 'state: working (agent is executing), waiting_input (blocked on human input), errored (last execution failed)'.
• Consider breaking up the list_tasks description into a concise main statement ('List task summaries with filtering and pagination') followed by a 'Details' or 'Implementation notes' section to separate UI-facing guidance from token-expensive edge-case details.
• Add per-tool output schema examples as comments in the source code (e.g. in src/bounded-reads.ts) so maintainers stay aware of response structure contracts.