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

With no annotations, the description carries the full burden of behavioral disclosure. It adds useful context by revealing the default backend URL and the ability to override it via a parameter, plus a rule against direct API calls. However, it does not disclose return format, error handling, or whether the operation is read-only, leaving some important behavioral aspects undisclosed.

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 three sentences long, front-loaded with the core purpose in the first sentence. Every sentence serves a distinct function: purpose, usage guidance, and configuration detail. There is no redundancy or filler, making it optimally concise.

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?

The tool is simple (2 parameters, no output schema, no annotations), and the description adequately covers purpose, usage, and endpoint configuration. However, it omits information about response format or potential error scenarios, which would be helpful for an agent to correctly interpret results. The absence of this detail is a noticeable gap, but not critical for a basic search tool.

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?

The input schema already provides descriptions for both parameters (query and search_api_url), achieving 100% schema coverage. The description's mention of the default URL and configurability simply restates what the parameter description already says, adding no novel semantic information beyond the schema.

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 the tool's function with a specific verb ('search') and resource ('Xinyang internal knowledge base'), and further clarifies scope by listing example content types (product parameters, technical solutions, company policies, etc.). This makes the tool's purpose unmistakable even without sibling tools to differentiate from.

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 provides explicit when-to-use guidance: 'must use this tool' when users ask about internal knowledge topics. It also explicitly prohibits alternative actions (direct curl/fetch calls to the backend API), leaving no ambiguity about the correct invocation path.

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