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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint, covering safety and idempotency. The description adds value by specifying the concrete metadata returned (fields/schema, themes, record count), which is beyond what annotations provide.

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?

Single sentence with a dash for clarity, front-loaded with the core purpose, then details and usage hint. Every part is essential and concise.

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 simple tool (one parameter, rich annotations, no output schema), the description fully covers what an agent needs: what it does, what it returns, and when to use it. No gaps remain.

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% for the only parameter (dataset_id), so baseline is 3. The description doesn't add new information about the parameter beyond the schema, but it implicitly ties the parameter to the tool's purpose, which is minimal added value.

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 action ('Get metadata'), the resource ('one Île-de-France Open Data dataset'), and the contents (fields/schema, themes, record count). It distinguishes from sibling tools like search_datasets and query by specifying that this is for metadata before querying.

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?

Explicit guidance: 'call before query to learn the column names' tells the agent exactly when to use this tool. It implies a sequential dependency with the query tool, establishing a clear usage pattern.

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