french_school_map_search_education_datasets

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

There are no annotations, so the description must disclose all behavioral traits. It only states the search action and resource but omits any details about pagination, rate limits, authentication, error behavior, or the nature of results (e.g., whether it returns dataset metadata or links). This is a significant gap for an external API interaction.

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, concise sentence without redundancy. However, it is too sparse, missing crucial usage and parameter details. While it is effectively front-loaded with the core purpose, the lack of structure (e.g., bullet points or examples) reduces its value. It earns a middle score for being concise but incomplete.

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 no annotations, no output schema, and only 2 parameters (both optional), the description provides only a high-level purpose. It does not explain the return format, error handling, or how results are structured. An agent cannot fully anticipate the tool's behavior or output, especially for an external data source like data.gouv.fr.

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 has 0% description coverage, meaning the description must explain the parameters 'query' and 'page_size'. It does not mention either parameter, their formats, defaults, or semantics. The agent has no added meaning beyond the schema's type/default information, which is insufficient for correct usage.

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 clear verb ('Search') and resource ('data.gouv.fr') with a specific domain ('education datasets') and lists relevant examples (IPS, Parcoursup, etc.). It distinguishes this tool from the sibling 'french_school_map_search_schools' by focusing on datasets rather than schools, though it does not explicitly name alternatives.

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?

No explicit guidance is provided on when to use this tool versus the sibling tools (e.g., search_schools, get_sources). The description implies usage for education dataset discovery, but there is no mention of conditions, exclusions, or alternatives. The agent is left to infer context.

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