Inspect Dataset Health and Details

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is known. The description adds valuable behavioral context: it states that absent health rows are reported as unknown rather than probed live (open-world behavior), that DataPulse is read-only and requires no API key, and that rate limits are roughly one request per second with a small burst. This goes beyond the annotations without contradicting them.

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?

The description is fairly long but packs essential information: purpose, key fields, usage guidance, exclusions, and rate-limit warnings. It is front-loaded with the core functionality before getting into alternatives and constraints. It could be slightly more concise, but every sentence earns its place through actionable details.

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?

The tool is simple (one parameter, no nested objects) and has an output schema, so the description doesn't need to detail return values. It covers the main use case, alternatives, and operational constraints (rate limiting, no API key, unknown-freshness behavior). The only minor gap is not specifying the exact format of the freshness_signal_source values, but the description does list the possible values.

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 input schema already describes the parameter dataset_id with an example and the requirement of a slug. The description reinforces this by stating it requires the slug, not a display name, which adds slight value. However, since schema coverage is 100%, the baseline of 3 is appropriate; the description's additional clarification is helpful but not critical.

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 clearly states the tool's verb ('fetch full detail') and resource ('one dataset id'), and specifies the exact fields returned (health status, last-verified timestamp, content_freshness_date, freshness_signal_source). It distinguishes itself from sibling tools by explicitly listing what to use instead for other purposes.

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 provides explicit when-to-use ('for one dataset's current published detail', 'to fetch provenance/citation metadata for a dataset found via search_datasets') and when-not-to-use ('do not use it for citation context or a Passport—use get_provenance or get_data_passport instead'). It also names alternatives clearly.

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