advanced_search_tweets

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 reveals that the tool returns a dict with about 20 tweets per page, that queryType defaults to 'Latest', and that cursor enables pagination. This is valuable behavioral context beyond the schema, though it omits potential errors, rate limits, and more detailed edge-case behavior.

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 uses a clear, structured Args/Returns format with minimal but complete detail. Every line contributes useful information, and there is no redundant or filler text. The example query adds value without bloating the description.

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 search tool with no output schema, the description gives an overview of the return format but lacks specific fields of the returned tweets, limitations of the query syntax (only one example), and error handling behavior. The pagination and queryType details are helpful, but the tool's complexity warrants more depth to be fully 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 provides only types and defaults (0% schema description coverage), so the description must compensate. It explains every parameter: query with a full example, queryType with allowed values and default, and cursor with pagination semantics. This fully covers the parameter meanings and usage details.

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 searches tweets ('高级搜索推文') and provides a concrete query example showing advanced syntax. This distinguishes it from sibling tools that are specific retrieval operations (e.g., get_user_last_tweets, get_tweets_by_ids) rather than general search.

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 shows how to construct a query (with OR, from:, since:) and explains queryType options and cursor pagination, giving implied usage context. However, it does not explicitly state when to prefer this over alternatives or provide any exclusions, so the guidance is implicit rather than explicit.

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