read_articles_batch

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 the rate-limiting behavior (5-second interval), the max batch size (5), the timeout parameter, and the behavior on partial failures (single failure doesn't affect others). It also mentions the return format (JSON with content and status). This is comprehensive, though it could mention whether the tool is read-only (but that's implied by '读取').

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 (typical workflow, args, returns, examples, notes). It is front-loaded with the key information (batch read, max 5, interval 5s) and every sentence adds value. It's appropriately sized for the tool's complexity.

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 (batch operation, rate limiting, partial failures), the description is complete. It covers the workflow, parameters, return format, limitations, and error behavior. The output schema exists, so return values are not over-explained. The description is sufficient for an agent to use the tool correctly.

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 must compensate. It explains the 'urls' parameter (list of article links, required, max 5) and 'timeout' (per-request timeout in seconds, default 30). It also provides an example usage. This adds meaning beyond the schema, which only lists types and 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 clearly states the tool reads multiple article contents in batch, with a specific verb ('批量读取') and resource ('多篇文章内容'). It distinguishes itself from siblings like read_article (single article) and search_news (searching) by explicitly mentioning the batch nature and the typical workflow.

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 provides explicit usage guidance: it outlines a typical workflow (search first, then batch read, then analyze), and implicitly distinguishes from read_article by focusing on batch processing. It also notes the limit of 5 articles and the time cost, which helps the agent decide when to use this tool.

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