Read dataset

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds substantive behavioral content on top: the payload includes `import_in_progress`, signalling that a dataset may be mid-import and its data incomplete, and that `runs` is only the newest set rather than history. It does not mention permissions or failure behavior for a bad id.

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?

Very compact and front-loaded: identification first, payload contents second, sibling routing last. Every clause carries information and none is filler. The telegraphic, punctuation-dense formatting is slightly harder to parse than plain sentences, which keeps it off a 5.

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 takes on the job of describing returns and does so field by field, including the subtle import-state flag. Combined with the annotation coverage, an agent has what it needs to select and invoke this correctly. It omits what happens on a missing or malformed id, a small remaining gap.

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?

There is a single parameter at 100% schema description coverage, with the `ds_...` format documented in the schema itself. The description says "by id" but adds no format, validation, or lookup-failure semantics beyond that. Baseline 3 is correct when the schema fully carries the parameter.

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 ("read dataset", "One dataset by id") and immediately enumerates the returned fields, which lets an agent recognize this as the single-resource fetch. It distinguishes itself from list_datasets and list_dataset_rows by explicitly noting rows come from the other tool. Only minor deduction for the bare heading, which is tautological on its own before the body clarifies.

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?

Gives explicit routing for two adjacent needs: row data goes to `list_dataset_rows`, and enrichment prompt text goes to `get_enrichment`. That is real when-to-use-something-else guidance rather than implied usage. There is no explicit statement of preconditions or when not to call it at all, so it stops short of a 5.

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