Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It discloses costs (free turn but model call, rate limits), error codes (429, 503, 402, 403), permissions (needs write permission), and the next step (call get_run). It also describes response suggestions. This is comprehensive and exceeds typical behavioral disclosure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense with information but well-structured, front-loading the core purpose and actions. While it is somewhat long, every sentence adds value—covering usage, errors, and next steps. It is not verbose or redundant, but could be slightly tighter by grouping related details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (three actions, multiple error types, permissions, rate limits, next steps), the description is remarkably complete. It covers what the tool does, when to use it, parameter semantics for the main inputs, behavioral details, and even hints at the response structure. The only missing piece is api_key, which is likely standard and not critical.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It explains message length (1-4000 chars) and conversation_id usage ('Pass conversation_id from an earlier turn to keep the context; leave it out to start a conversation'), but does not mention api_key at all. This covers two of three parameters well, but the omission of api_key is a minor gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it is a conversational turn with three specific actions (clarify, answer, research), and explicitly differentiates from find_hooks, saying 'For direct research without the question step, call find_hooks instead.' This gives a specific verb+resource and distinguishes it from siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains when to use each action (clarify, answer, research) and provides explicit alternatives, such as using find_hooks for direct research. It also states the next step to call get_run after a research action, giving clear guidance on usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.