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

With annotations already declaring readOnly, idempotent, and non-destructive behavior, the description adds valuable context: the archive is first-hand only, carries publish date/topic/source URL/summary, is Chinese-language, and is not the account's full history. The clarification of 'A-grade' and the coverage window give an agent accurate expectations not inferable from annotations alone.

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 organized into Purpose, Guidelines, Limits, and Ex sections with no redundant filler. It front-loads the core purpose, keeps each section to one or two sentences, and the examples are compact and directly actionable.

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 6-parameter tool with an output schema present, the description is complete: it covers the resource, the matching semantics, category filtering, language, data coverage limits, and gives runnable examples. The output schema handles return values, so nothing essential is missing for an agent to invoke the tool correctly.

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 100%, so baseline is 3. The description adds meaning by explaining that keyword matches title/topic/author/scope and category filters to a single theme, and it provides three concrete example calls that clarify how keyword, category, and language parameters combine. This lifts it above 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 clearly states a specific verb ('search') and a specific resource ('first-hand research archive of the RCB industry WeChat official account'), with content detail (conference coverage, process cases, application boundaries, market forecasts). However, it does not explicitly distinguish itself from sibling tools like get_article or other query_* tools, so it stops short of full sibling differentiation.

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 Guidelines section explains how keyword and category filtering work, and the Limits section clearly gives exclusions: Chinese-only source material, limited coverage of 63 articles from 2026-04 onward, and A-grade not meaning peer-reviewed. It does not name alternative tools or exactly when to prefer them, though the limits implicitly say when this tool is not suitable.

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