Fetch Hot Topics

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

No annotations are provided, so the description must carry the behavioral burden. It clarifies it fetches current hot lists from named platforms)Skip. It does not mention failure modes, rate limits, live-source behavior, or output limitations, but for a simple fetch operation the core behavior is clear.

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?

One concise sentence front-loads the action and then lists supported platforms. No waste.

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 single-parameter tool with an output schema, the description adequately identifies the data source and platform set. It could mention expected use cases ('when user asks today's hot topics') or note live-source behavior, but it is largely complete.

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 schema only documents 'platforms' as a list with a default of all platforms. The tool description adds the allowed platform values (知乎/B站/GitHub趋势/HN), giving meaning 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?

Description uses a specific verb ('获取') and resource ('主流平台当前热搜榜单'), and enumerates the platforms (知乎, B站, GitHub趋势, Hacker News). It clearly states what the tool does, though it does not explicitly contrast with sibling search/recommendation tools.

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 implies when to use it (when hot topics from mainstream platforms are needed) and the schema adds default behavior (all platforms if not specified). However, it gives no explicit guidance on when to prefer this over siblings like web_search, juejin_recommended, or arxiv_search.

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