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

With no annotations supplied, the description carries the full burden and does disclose two real behavioral traits: no LLM is invoked and free tier truncates each note to 300 characters. It does not cover permissions, result limits/pagination, or what happens when q matches nothing, so mutation-adjacent side effects are absent but reading scope is only partly covered.

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?

It is short and front-loads the returned fields, but the parenthetical field list reads as schema restatement and the pricing/truncation metadata is jammed into the same sentence rather than separated, muddying the read of the core purpose.

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?

For a two-parameter tool with no output schema and no annotations, the description should explain both inputs and the shape/limits of results; it leaves q entirely undocumented and says nothing about pagination or what an empty result looks like, which is significant given the truncation caveat.

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 explain the parameters and it does not: topic_id is only obliquely implied by 'topic expert', and the q parameter is never mentioned at all — its search semantics, matching fields, and 200-char cap are invisible to the agent.

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 names a specific resource (curated notes of a topic expert) and enumerates the returned fields (kind, title, content, evidence paper ids), and the phrase 'without an LLM call' implicitly separates it from expert_ask-style generation. It lacks an explicit retrieval verb, but an agent can still tell what comes back.

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?

'Without an LLM call' plus '[Free · 1 credit]' implies this is the cheap alternative to a generation tool, but the description never states when to prefer it over expert_ask or how to handle the free-tier truncation versus a paid read. Usage is only implied, not prescribed.

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