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

Annotations already mark the tool as potentially destructive, but the description adds crucial specifics: it may save files locally (original file fallback) and can submit an application on the user's behalf when no_apply=False. It also explains probe as a safe check. This exceeds the annotation signal and fully discloses behavioral traits.

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 front-loaded with the core purpose and structured logically (main purpose, side-effect warning, probe explanation, return summary). It is slightly verbose due to bilingual repetition, but every sentence adds value. Good organization.

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?

The output schema exists, so return values don't need detailed explanation, and the description still gives a concise return summary. It covers side effects, probe behavior, and fallback logic. The only gap is the meaning of n, which the schema may already describe. Overall, it's complete for the tool's complexity.

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?

With 0% schema description coverage, the description must explain parameters. It explains no_apply and probe clearly, but gives no meaning for n (likely row count) or dataset_id beyond being required. It partially compensates but leaves key parameters undocumented.

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 returns rows, links, or API templates depending on access method, which is a specific verb-resource combination. It also distinguishes itself from siblings by the mention of access_kind and the fallback behavior, making its purpose unambiguous.

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 explains when to use probe and no_apply, but does not explicitly contrast with sibling tools like search, preview, or fetch. The guidance is present for specific scenarios (401 fallback, avoiding side effects) but not for general selection between tools.

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