mayotte_get_dataset

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

With no annotations, the description must carry the full burden. The verb 'inspect' implies a read-only operation, and 'using the official public API' suggests a safe, external call. However, it does not explicitly state non-mutation, rate limits, or any side effects, leaving some ambiguity.

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 single, front-loaded sentence that communicates the tool's purpose without any fluff. Every word adds value, making it highly concise and well-structured.

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 tool is simple (one parameter, no output schema) and the description explains its core functionality. However, it does not mention what happens on failure or what the return format is, leaving some details unspecified. For a basic get-by-id tool, this is adequate but not thorough.

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%—the parameter 'dataset' is already described as 'Dataset slug or id.' The description adds no additional meaning beyond what the schema provides, so it meets the baseline but does not exceed it.

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 clearly states the tool inspects a single data.gouv.fr dataset by slug or id, using a specific verb (inspect) and resource. This distinguishes it from sibling tools like search or list, which handle different operations.

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 description conveys a clear use case: when you have a specific dataset slug or id and want to inspect it. It does not explicitly mention alternatives or when not to use, but the context is clear enough for an agent to infer its purpose.

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