batch_check

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

No annotations are provided, so the description carries the full disclosure burden. It states that it returns each domain's stance, use-case policies, and bot lists side-by-side, and also communicates the 2-25 domain constraint. Since this is a read-only lookup operation, the lack of side-effect warnings is acceptable, though it does not explicitly state read-only.

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 a short paragraph followed by a well-structured Args block. It front-loads the primary purpose in the first sentence and uses minimal, high-value wording for the parameter explanation.

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?

Given the single parameter and the presence of an output schema, the description provides sufficient context for an agent to select and invoke the tool correctly. The 2-25 range and example ensure valid input, and the return description clarifies what to expect.

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 only defines 'domains' as an array of strings, but the description's Args section adds crucial semantics: it defines the required count (2-25), provides a concrete example, and clarifies that the entries are domain names. This fully compensates for the 0% schema description coverage.

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 opens with 'Compare AI policies across multiple domains using the Maango registry', which clearly states the verb (compare), resource (AI policies), and scope (multiple domains). It also mentions the batch nature (2-25 domains) and differentiates from single-lookup siblings like lookup_domain.

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 explicitly instructs the agent that this is for comparing 2-25 domains at once, making it obvious when to use it. However, it does not explicitly name alternatives like 'use lookup_domain for a single domain', so it lacks formal exclusions.

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