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

With no annotations, the description carries the behavioral burden and discloses important traits: output is LLM-condensed, cached for 7 days, costs $0.005 USDC via Solana/x402, and the schema exposes a free tier. It does not fully explain the payment flow or error behavior, but it provides substantial operational context.

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 densely front-loaded and appropriately sized: purpose and output are stated first, followed by input, optional question, and cost. Every sentence carries useful information with no filler.

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?

There is no output schema, so the description helpfully explains what is returned: base URL, auth scheme, rate-limit and error notes, key endpoints, and source links. It also mentions caching and cost, though it stops short of fully documenting payment failure or no-match behavior.

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 100%, so the baseline is 3. The description repeats the api input forms and optional question, but does not add meaning beyond the schema for free_trial or x402_payment.

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 states a specific verb and resource: it looks up a public API's OpenAPI spec, llms.txt/docs, and returns metadata such as base URL, auth scheme, and key endpoints. This is clear, but it does not explicitly distinguish itself from the sibling api_endpoint tool, so it falls short of the top score for sibling differentiation.

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 by explaining that it finds API specs and docs and accepts an optional focus question, but it never explicitly says when to choose this tool over api_endpoint or other alternatives. There are no exclusions or prerequisite guidance beyond the payment note.

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