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

Annotations already declare readOnlyHint=true, idempotentHint=true and openWorldHint=true, so safety is covered; the description adds the non-obvious query-language guidance and the output hand-off to datagov_query. It does not mention result-count behavior or that only up to 20 hits come back, which would have made this a 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?

Three short sentences with zero filler, and the core purpose is front-loaded ahead of the tips and hand-off. Every sentence carries distinct 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?

With no output schema, the description does the necessary work by naming the return content (datasets + resource_id) and how to consume it. The only gap is pagination/limit behavior for a tool that clearly returns a bounded list.

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 coverage is only 50%: 'query' is documented in-schema, but 'limit' has no description anywhere. The description compensates partially by telling the agent what to put in 'query' (Hebrew terms), but says nothing about what 'limit' controls or that it caps at 20 – though the maximum is visible in the schema itself.

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 and resource ('Search Israel's national open-data portal') and names the concrete payload ('datasets and their resource_id values'). It also points at the sibling consumer (datagov_query), so an agent can tell this apart from the other datagov tool 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?

'Hebrew queries work best' plus 'resource_id values for datagov_query' gives clear context and an implied two-step workflow (search then query). It stops short of an explicit exclusion such as 'do not use this to fetch dataset rows', leaving the boundary with datagov_query only implied.

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