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

The annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds genuinely new behavioral context: no prices or stock levels, page URLs returned, and conditional inclusion of guides and part-vs-part comparisons when the query is a decision question. Pagination via limit is left to the schema, which keeps this from a 5.

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?

Three sentences, each carrying distinct information: what is searchable (with examples), what comes back including the conditional comparison case, and the important negative scope ('not a store'). The return-format sentence slightly overlaps with the output schema but still adds the conditional decision-question behavior, so it earns its place.

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?

With an output schema present, the description does not need to enumerate return fields, yet it still flags the two things an agent would otherwise get wrong: no pricing/stock data, and comparisons only for decision questions. Combined with the get_part handoff, an agent has everything needed to call this correctly and interpret the result.

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 coverage is 50% — query is documented in the schema, limit is not. The description does add substantial meaning to query by showing the accepted forms (part number, spec string, keyword in English or Chinese) and by revealing that decision-style phrasings trigger comparison output. Limit's behavior beyond its default and maximum is still unexplained, which anchors this at the baseline.

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 verb and resource ('Search commercial deep-fryer parts') and then concretizes the three query modes with real examples, including a part number, a spec string, a wattage string, and a Chinese keyword. An agent can immediately tell this is a lookup/index tool rather than a detail fetch or listing tool.

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?

It gives an explicit follow-up rule — 'Use get_part afterwards when you need specifications for one record' — which clearly routes the agent between this tool and its sibling. It also sets expectations with 'This is a reference index, not a store.' The only gap is that list_parts is never contrasted, so the agent must infer how browsing differs from searching.

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