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

Annotations already cover readOnly, idempotent, openWorld, non-destructive, so the safety profile needs no repetition. The description adds value the annotations cannot: it lists the concrete return payload (dataset_ids, titles, themes, record counts), which matters given there is no output schema.

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?

Two sentences, zero filler, and the most decision-relevant content (what it searches and where results go) is front-loaded.

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?

With no output schema, the description compensates by naming the returned fields, and annotations cover the safety profile. For a simple 3-param, zero-required search tool this is close to complete, though pagination behavior across offset/limit is left entirely to the schema.

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 all three parameters (limit, query, offset) are documented with defaults and ranges in the schema. The description only gestures at keyword semantics with 'mobility, urban services & environment', adding no format or syntax detail beyond the schema. 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?

States a specific verb (Search), resource (datasets), and data source (Aix-Marseille-Provence Open Data), plus the domain of keywords. It also names the returned fields and the sibling tools that consume dataset_ids, so an agent can distinguish it from dataset_info and 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?

The description makes clear this is the discovery entry point and routes the agent onward: 'dataset_ids (pass to query/dataset_info)'. There is no explicit when-not guidance or exclusion of alternative search tools like search_within, but the intended workflow is unambiguous.

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