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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world corpus), so the bar is lower. The description adds genuinely useful behavioral context by disclosing the return shape — best-matching pages with an id for `fetch` — which matters because no output schema exists to document this.

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?

Two tight sentences with zero padding. The scope of the corpus is front-loaded and the handoff to `fetch` is placed last, matching the order an agent needs the information.

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 three-parameter search tool with no output schema, the description supplies the two things an agent most needs: what corpus is searched and what the results look like. The only minor gap is guidance on result quality or what to do when no match is found, which is not strictly required.

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 100%, with each of the three parameters documented (query examples, limit default/max, section enum), so the baseline is 3. The description's list of covered topics loosely maps to the section enum but adds no syntax or format guidance beyond what the schema already provides.

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?

States a specific verb and resource ('Search docs.bithuman.ai') and enumerates the covered corpus (avatar SDKs, REST API, deployment, models, pricing). It also distinguishes itself from its sibling by explaining that result ids are meant to be passed to `fetch`, so the retrieval-then-fetch pipeline is unambiguous.

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 makes clear this is the entry point for documentation lookup and that its output feeds `fetch`, which implies when to use it. It does not state explicit exclusions (e.g., what to do if search returns nothing, or when to skip straight to fetch), so it falls short of a full when/when-not statement.

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