batch_fetch

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 caching (already visited URLs return instantly), rate limiting to avoid captchas, parallelism for batches ≥8, auto-detection of workers, and the return format with separators. It also explains article_only extraction via Trafilatura. This is rich behavioral detail that significantly aids agent decision-making.

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 dense but well-structured: purpose first, then cache, rate limit, parallelism, return format, article_only, and an example. Every sentence adds value, though it could be slightly more concise by integrating the max_chars explanation more explicitly.

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 complex tool with 4 parameters and no annotations, the description covers caching, rate limits, parallelism, output format, and article extraction. It lacks explicit explanation of max_chars and error handling, but overall it is sufficiently complete for an agent to use it effectively, especially with an output schema present.

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 explain all parameters. It explains article_only and max_parallel explicitly, and urls implicitly, but max_chars is only shown in the example and not defined. This leaves a gap for one of the four parameters, though the example provides some contextual clue.

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 it opens multiple URLs in a single browser for deep research, contrasting with single fetches. It uses a specific verb (opens) and resource (URLs), and distinguishes from siblings like fetch_page by emphasizing batch use for 30-50 sources.

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?

It implies when to use: for deep research on many sources in one call instead of a series of cold starts. It contrasts with single fetch, but does not explicitly name alternatives or exclusions. The context is clear enough that an agent would know to prefer this for batch operations.

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