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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is fully covered. The description adds genuinely useful non-annotation context: it is a single-dataset metadata read positioned as a prerequisite to querying. It stops short of noting any rate limits or caching semantics, so 4 rather than 5.

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?

A single em-dash-joined sentence that front-loads the operation and return payload before the workflow hint. No filler, every clause carries information.

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?

There is no output schema, and the description partly compensates by naming the returned concepts (fields/schema, themes, record count). For a one-parameter read-only lookup this is nearly complete; only the exact response shape beyond those three items is unstated.

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% and the single dataset_id parameter is documented in the schema as coming from search_datasets. The description's 'one ... dataset' phrasing reinforces cardinality but adds no format or syntax detail beyond the schema, so baseline 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 states a specific verb and resource ('Get metadata for one Strasbourg Open Data dataset') and enumerates the payload (fields/schema, themes, record count). It is immediately distinguishable from sibling search_datasets (find datasets) and query (run a query).

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 gives explicit sequencing guidance: 'call before query to learn the column names', naming the sibling tool that follows it. The agent knows both when to use this tool and what it enables downstream, with nothing left to inference.

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