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

Goes beyond the annotations by disclosing a per-successful-call price ($0.001 USDC on Base paid via x402), which is critical operational context an agent cannot infer from readOnlyHint/openWorldHint/destructiveHint. It also states outputs are de-duplicated per list. It does not cover failure behavior (e.g., no matches found) or rate limits, and notably the mutation hint is false despite this being a read-style extraction.

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?

Three short sentences, each carrying distinct load: scope of extraction, use case, and cost. Purpose is front-loaded and there is 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?

For a one-parameter tool with no output schema, the description effectively enumerates the return categories (one list per entity type, de-duplicated) and discloses the payment requirement. Minor gaps remain: whether lists are always present when empty, and any input-size constraints.

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 a single required parameter and schema description coverage is 100%, so the schema already documents it fully. The description adds only the vague phrase 'in a text', providing no extra semantics such as size limits or encoding expectations — baseline 3 applies.

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?

States a specific verb ('Find') and an enumerated resource set: emails, URLs, phone-number-like strings, hashtags, @mentions and numbers, plus the de-duplication guarantee. This distinguishes it from generic siblings like 'extract', 'email' and 'html_to-text' without opening any schema.

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?

Gives a concrete usage context — 'pull contacts and links out of scraped pages or messages' — which tells the agent when it is the right call. It stops short of naming alternatives (e.g., 'extract' or 'html_to-text') or stating when not to use it, so it lacks explicit exclusions.

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