聚合国际新闻

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

Annotations already provide readOnlyHint=true and openWorldHint=true, covering the safety profile. The description adds meaningful behavioral context by specifying the clustering criteria (similar titles, keywords, temporal proximity) and that the output consists of traceable event clusters, which is valuable in the absence of an output schema. It does not fully explain cluster structure or traceability mechanics, but it goes beyond the annotations.

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 one efficient sentence, front-loaded with the primary action and then the clustering behavior. There is no filler, repetition, or redundant detail, making it appropriately 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?

With 8 parameters, no output schema, and no parameter descriptions, a single-sentence description is insufficient for reliable invocation. It omits how time ranges are specified, what the returned clusters contain, how 'traceable' is expressed, and how filters such as category, language, and source_ids interact with clustering.

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%, so the description should compensate, but it does not explain any of the 8 parameters. Words like '查询' and '关键词' only weakly hint at a keyword query, while from, to, sort, limit, category, language, and source_ids receive no elaboration. An agent must rely entirely on parameter names and schema defaults.

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 states a specific verb (查询, query) and resource (国际新闻, international news), then explains that it forms traceable event clusters based on similar titles, keywords, and temporal proximity. This clearly differentiates it from sibling tools like search_international_news, which retrieves individual articles, and aggregate_china_news, which is China-specific.

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 clustering behavior implies the tool is intended for grouped-event discovery rather than simple search, so usage context is partially inferable. However, the description does not explicitly say when to prefer this tool over alternatives like search_international_news, nor does it mention any exclusions or when-not-to-use conditions.

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