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

Annotations already declare readOnlyHint=true, idempotentHint=true and destructiveHint=false, so the safety profile is covered. The description adds real behavioral context beyond that: it explains what a 'held run' is (a run waiting for confirmation), what visibility values mean, and that category_id is null when unset. It does not mention auth/permission requirements, but for a read-only tool that is a minor gap.

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?

Front-loads the definition, then the return shape, then usage and sibling differentiation — a sensible order. The field enumeration is long, but it substitutes for the missing output schema, so it earns its space; the paragraph is dense rather than padded.

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 enumerates the return structure in detail (dataset_id, status, visibility, tables with build/promotion state, latest_run, held_run, dashboard_url), and pairs it with when-to-use and sibling routing. Nothing an agent needs to call and interpret this tool is missing.

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?

Only one parameter with 0% schema description coverage, so the description must carry the load. It supplies an invocation example ({"dataset_id": "…"}) which confirms the expected shape, and the tool name implies the ID refers to the caller's own dataset. However, it never states where dataset_id comes from or how it relates to workspace scope, so it adds only marginal meaning over the uuid format already in the schema.

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?

Opens with a specific verb+resource+scope ('One workspace dataset in build terms') and explicitly names the sibling it differs from: 'Different from the public get_dataset, which reads the published catalog.' An agent can distinguish it from get_dataset and list_my_datasets without opening any 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?

States the trigger condition directly ('the tool to call after a run finishes to see what it produced') and gives the exclusion rule against the alternative (get_dataset reads the published catalog, this reads the workspace dataset). Both when-to-use and when-not-to-use are covered.

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