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

Annotations cover the read-only and closed-world profile, and the description layers on genuinely useful behaviour: return shape { valid, errors }, a hard cap of 50 error messages, and a billing rule (1 credit per successful call, invalid input rejected before billing). That last point tells the agent failed validations are free, which is non-obvious and actionable.

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 tight sentences: what it does, what it returns with the error cap, then the cost model. Zero waste and the core operation is front-loaded.

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?

With no output schema, the description carries the return contract and does so precisely, including the error cap. Billing and the subset limitation round out an adequate picture for a two-parameter validator.

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%, with both parameters documented, including the enumerated subset of keywords supported. The description only restates that a subset is accepted and adds no format or syntax detail beyond the schema, so the baseline of 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 and resource: validate a JSON value against a JSON-Schema subset, and lists every error path. The operation is clearly distinct from neighbours like json-extract, tool-schema or dataset-validate. It does not name any sibling explicitly, so it stops short of the top mark.

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?

Nothing is said about when to reach for this versus siblings such as tool-schema or dataset-validate, and no prerequisites or exclusions are given. The single-purpose validator name makes the use case strongly implied, which fits a 3 rather than a 2.

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