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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and non-destructive, so the safety profile is covered structurally. The description adds the return shape (dataset_ids, titles, themes, record counts), which is genuinely useful, but says nothing about rate limits, ranking behavior, or empty-result handling.

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 tight sentences with the verb and source front-loaded, then the return contract and the handoff to downstream tools. No filler, no restatement of the title.

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 usefully summarizes the return fields and the chaining target, and the schema covers pagination fully. It is complete enough to call correctly; only richer ranking/edge-case behavior is absent.

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% with all three parameters (limit, query, offset) documented including defaults and ranges, so the schema carries the load. The description only loosely maps 'keyword' to the query parameter and adds no syntax, operator, or multi-term guidance beyond it.

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) and resource (datasets) scoped to a named source (Grand Paris Sud Open Data), and lists the keyword domains it covers. It also enumerates what comes back, letting an agent distinguish it from sibling dataset_info/query tools without opening a schema.

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?

Clearly implies the discovery step of a workflow by telling the agent to pass returned dataset_ids to query/dataset_info, which routes it ahead of those siblings. It does not state when NOT to use it (e.g., versus search_within or datasets already known), so it stops short of explicit exclusions.

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