data_gouv_fr_get_dataset

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

No annotations are provided, so the description carries the burden. 'Inspect...using the official public API' signals a read-only, public operation with no modification side effects. It doesn't describe return format or edge cases, but for a single-dataset lookup this is reasonable.

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 one compact sentence, front-loaded with the action verb, and contains no filler. Every part contributes to deciding the purpose or origin of the API.

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 one-parameter, no-output-schema, known-dataset lookup, the description supplies the essential context needed for selection and invocation. It could be improved by saying what the returned inspection data looks like, but nothing critical is missing.

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 already covers the parameter fully with 'Dataset slug or id' at 100% coverage. The tool description repeats this notion but adds no new semantic detail about the parameter, so the high schema-coverage 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?

The description uses a specific verb ('Inspect') and a precise target ('one data.gouv.fr dataset') identified by slug or id. This distinguishes it from sibling tools like search_data_gouv, list_dataset_resources, or get_sources, which operate at different levels or with different scopes.

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 clear context is: use this when you need details about one known dataset, identified by slug or id. It does not, however, explicitly name alternatives or say what to use for search/resource-listing instead, so it misses the top score.

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