aggregate_news

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the tool's function (aggregation with deduplication), output format (JSON with specific fields), and default behaviors (e.g., date_range defaults to today). However, it doesn't mention potential side effects, rate limits, authentication needs, or error conditions, which are important for a tool with multiple parameters and no annotation coverage.

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 well-structured with clear sections (purpose, Args, Returns, Examples) and uses bullet points for readability. Every sentence adds value, though the Chinese-to-English translation creates minor redundancy in the purpose statement. It could be slightly more concise in the opening lines but remains efficient overall.

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?

Given the tool's complexity (5 parameters, aggregation logic) and the presence of an output schema (which handles return values), the description is quite complete. It explains the tool's purpose, all parameters, return format, and provides examples. The main gap is lack of behavioral warnings (since no annotations exist), but otherwise it covers most contextual needs adequately.

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 description provides excellent parameter semantics beyond the input schema, which has 0% description coverage. Each parameter (date_range, platforms, similarity_threshold, limit, include_url) is clearly explained with meaning, format examples, defaults, and constraints (e.g., similarity_threshold range 0.3-1.0). This fully compensates for the schema's lack of descriptions and adds significant value.

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 purpose: '跨平台新闻聚合 - 对相似新闻进行去重合并' (cross-platform news aggregation - deduplicate and merge similar news). It specifies the verb (aggregate), resource (news), and scope (across platforms with deduplication). However, it doesn't explicitly differentiate from sibling tools like 'find_related_news' or 'search_news', which prevents a perfect score.

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 usage context through examples and parameter explanations (e.g., '不指定则查询今天' - if not specified, query today), but lacks explicit guidance on when to use this tool versus alternatives like 'find_related_news' or 'get_latest_news'. It provides some operational context but no clear when/when-not statements or named alternatives.

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