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

Goes well beyond the readOnlyHint/openWorldHint annotations without contradicting them: it discloses the exact response envelope, the null-when-absent contract, the per-call price (3 credits = 3 CAD cents), and that schema-invalid input is rejected before billing. That billing-and-rejection behavior is exactly the kind of context an agent cannot get from annotations.

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?

Two sentences, front-loaded with the operation and its output contract, followed by pricing. No filler, and the cost caveat lands before the agent commits to a call.

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?

Despite having no output schema, the description fully specifies the return shape ({ data, found, total }), the null semantics, and the billing/rejection model. Combined with a complete input schema, an agent has everything needed to call this correctly and predict the response.

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 coverage is 100%, so both parameters (text, fields) are already documented with limits and patterns, and the baseline is 3. The description corroborates but adds no syntax beyond the schema — the 6,000-character cap and the 30-field cap are only in the schema, not restated or explained here.

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+resource ("pulls the fields you name out of free text") and grounds it with three concrete input examples (emails, invoices, tickets). It doesn't mention the related siblings (entity-extract, web-extract, json-validate), so an agent must infer the division of labor, but the operation itself is 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?

The domain (free text → named fields) implies when to use it, and the "strict JSON" framing hints it is the deterministic counterpart to looser extractors. However there is no explicit when-to-use, when-not, or named alternative such as entity-extract; the agent must reason about siblings on its own.

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