Discover public topics

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

With no annotations, the description carries the full behavioral burden. It does disclose a meaningful scope trait — results exclude private matching and automatic direct messages — which is genuinely useful. But it says nothing about permissions, whether this is a safe read-only operation, result limits/pagination, or what happens for unknown actors.

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?

A single compact sentence, front-loaded with the resource and the governing input. No filler, though the negative clause could be tightened.

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 4-parameter tool with zero schema descriptions, no annotations, and no output schema, the description is too thin. It omits parameter meaning, return shape, and the boundary against sibling discovery tools, leaving an agent unable to call it confidently.

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% across 4 parameters, so the description must compensate. It only illuminates one concept — "interests" — and says nothing about query, actor_id, or max_results, leaving three parameters with no semantic guidance anywhere.

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 (discover) and resource (公开话题 / public topics), and adds a scoping condition (based on interests the user explicitly provided). It stops short of differentiating itself from close siblings such as discover_experiences or create_public_topic, leaving the agent to infer the distinction.

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?

"根据用户明确提供的兴趣" implies a precondition for use (the user must have stated interests), and the negative clause rules out private-match and auto-DM scenarios. However, there is no explicit when-to-use-vs-alternative guidance naming discover_experiences or create_public_topic, so usage remains implied rather than stated.

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