get_latest_news

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

No annotations are provided, so the description carries the full burden. It discloses that include_url default False is for saving tokens, and it provides display behavior guidelines (show all data by default, only summarize when explicitly requested). These are valuable behavioral traits beyond simple parameter listing. However, it does not mention rate limits, error cases, or side effects, though this is a read-only tool.

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 for Args, Returns, and display suggestions. The purpose is front-loaded in the first sentence. The three bullet points for display suggestions are slightly verbose but each adds actionable guidance. Overall, it is concise and every part serves a purpose, though it could be tightened slightly.

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 moderate complexity (3 optional parameters, output schema present), the description covers the purpose, parameter semantics, return type, and even agent-facing display behavior. It is missing edge-case guidance (e.g., what happens if no data is available) and explicit comparison to alternatives, but for a simple retrieval tool it is quite 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 zero description coverage, but the description fully compensates by explaining each parameter: platforms (list of IDs, default all), limit (default 50, max 1000), include_url (whether to include URLs, default false, saves tokens). It includes concrete examples and usage rationale, adding significant meaning beyond the schema's type definitions.

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 function: '获取最新一批爬取的新闻数据，快速了解当前热点' (get the latest batch of crawled news data for quick understanding of current hot topics). It uses a specific verb+resource construction and distinguishes from siblings like get_news_by_date (specific date) and search_news (search) by emphasizing 'latest' and 'hot topics'.

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 for retrieving the most recent news ('最新一批') and for quick insight into hot topics, but it does not explicitly compare with alternatives or state when not to use this tool. The '数据展示建议' section provides guidance on how to present results to users, which is useful but not about tool selection. Thus, usage context is implied but not fully explicit.

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