Inspect Dataset Health and Details

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

Annotations already declare readOnlyHint, openWorldHint, and idemmpotentHint, covering safety and idempotency. The description adds value by exposing freshness_signal_source semantics (last_modified, content_parse, none) and the interpretative distinction between unknown freshness and proven stale data, which is behavioral context not present in the annotations.

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: one front-loads the operational return value, the other provides the invocation context. There is no extraneous repetition and every sentence contributes actionable 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?

For a single-parameter, read-only, idempotent tool, the description covers what the call returns, the fields the agent can expect, and the intended decision use-case. With no output schema present it could have listed more about failure modes or edge cases, but the level of detail is adequate for selection and invocation.

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?

The single parameter dataset_id is already fully documented in the schema with an example, min_length, and a pointer to the registry. The description does not add further parameter-level meaning, which is acceptable since the schema provides complete coverage.

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 action (return full detail for one dataset id), the exact resource scope, and the key returned fields. It also explicitly distinguishes itself from search_datasets by framing that tool as the discovery step. This makes the reference clear and disambiguated.

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 gives a clear usage context: use it for a dataset found via search_datasets and to distinguish unknown freshness from proven stale data. It does not explicitly say when not to use it or name alternative tools for health/provenance inspection, so it stops short of a full when-not guidance.

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