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

Beyond the readOnly/openWorld annotations, the description discloses free-call limits, post-limit payment via x402 or credits, the in-band payment location, the 6,000-character cap, GET/POST input modes, and a literal-occurrence validation rule. These are meaningful operational traits that the annotations alone do not cover.

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 mostly efficient, with no filler. Its only structural weakness is that it leads with pricing before stating the core purpose, pushing the most important identification detail into the second sentence.

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 description covers purpose, usage conditions, sibling alternative, input size limit, supported input methods, payment mechanics, and validation behavior. Since an output schema exists, it does not need to explain return values, and no material gap remains for an agent to invoke the tool correctly.

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?

The schema already documents the single required text parameter, and the description adds useful constraints: maximum 6,000 characters plus the payment parameter location under params._meta. It adds value beyond the schema, though the schema coverage is already high.

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 gives a specific verb and resource: named entity extraction, and explicitly lists the entity types covered. It also names the sibling tool extract-json and distinguishes this tool from it, so an agent can route correctly without opening the schemas.

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 states exactly when to use entity-extract: people, companies, places, dates, and amounts. It also names the alternative extract-json and the condition that selects it (when you need your own schema), giving both positive and exclusionary guidance.

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