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

Annotations already carry readOnlyHint=true and idempotent/read-safe traitsnis, and the description adds meaningful behavioral context beyond safety: it reports build state rather than published state, includes held runs awaiting spend confirmation, and scopes results to the caller's workspace. No contradiction with 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?

The description is compact and front-loaded: scope first, then response shape, then use case. The example and the explicit return fields duplicate some information but still serve the agent by making the data shape concrete without excessive prose.

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 tool with no output schema, the description is complete: it lists the full return shape, explains the 'build terms' distinction, identifies the appropriate call timing, and disambiguates from the sibling public get_dataset. An agent has enough context to invoke this tool correctly.

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 dataset_id parameter is already well-specified by the schema (type, format, pattern). The description adds only mild semantic context—that the dataset is 'my' workspace dataset and a placeholder example—but does not explain where to obtain the ID or how it interacts with the result. It is adequate but not rich.

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 verb and scope: it retrieves 'one workspace dataset in build terms' and enumerates exactly what is included (each table's build state, promotion state, live version, latest run, held run). It also distinguishes itself from the sibling get_dataset, so the agent knows this is the workspace-private variant, not the public one.

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?

It explicitly says 'This is the tool to call after a run finishes to see what it produced' and contrasts itself with 'public get_dataset, which reads the published catalog.' This gives the agent both a positive trigger and a clear alternative to rule out.

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