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

Annotations already mark this as read-only and non-destructive. The description adds meaningful behavioral context beyond that: it returns a score, grade, ranked fixes, and a signed proof, and it emphasizes that every result re-derives from a fresh public fetch, which affects how an agent should interpret the output.

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 and front-loaded with the core verb and resource. Each sentence adds value: scope, checked items, return values, verification guarantee, and a docs link. There is no fluff or repetition of the schema.

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 single-parameter, read-only audit tool with no output schema, the description is complete. It explains what will happen, what the result looks like, and the guarantee that results are reproducible from public fetches. No critical missing context is apparent.

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?

There is only one parameter, url, and its schema description already specifies that it must be a public HTTP(S) agent endpoint/site URL. The tool description does not add new parameter-level information, but with 100% schema description coverage, this is an acceptable baseline.

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 identifies the tool's action: auditing a public agent or API URL for verifiability. It enumerates specific checked artifacts (llms.txt, MCP card, robots, sitemap, handshake endpoints, signed proofs) and the concrete output (score, grade, ranked fixes, signed proof), which distinguishes it from generic siblings like validate or verify_proof.

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 makes the intended context clear: public agent/API URLs only, with all results derived from public fetches. It does not explicitly compare against sibling tools or state when not to use it, but the public-only constraint and audit-specific focus provide sufficient guidance for most cases.

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