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

With no annotations, the description carries the full behavioral burden, and it usefully discloses that processing happens 'in parallel server-side' and that results are returned 'one verdict per input, in order.' It still omits operational details such as failure behavior, rate limits, or whether inputs are retained, so transparency is adequate but incomplete.

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, front-loaded with the core action and scope, followed by use cases and return behavior. Every sentence contributes and nothing is wasted.

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 simple two-parameter batch validation tool with no output schema, the description covers purpose, use cases, parallel processing, and ordering. It stops short of describing the verdict format or failure semantics, but it is nearly complete for selection and invocation.

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%, so the input schema already documents both the prompts array and the sensitivity enum thoroughly. The description does not add parameter-level detail beyond the schema, which is the expected baseline when schema coverage is 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 states a specific verb and resource ('Validate many pieces of untrusted text') and makes the batch scope explicit with 'in one call' and 'bulk', which clearly distinguishes it from the singular sibling validate_prompt. An agent can immediately tell this is the multi-item variant.

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 gives concrete usage contexts: 'bulk pre-screening, indexing pipelines, or checking a batch of retrieved documents.' It does not explicitly say when not to use it or name validate_prompt as the alternative for single inputs, but the batch-oriented guidance is clear.

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