get_dataset

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

With no annotations supplied, the description carries the burden and does disclose meaningful behavior: the result is automatically stored, a formatted preview with an @obj_ ID is returned, and nested properties require the object store tools. It also states an error message is returned instead of the Dataset. Missing are permission/read-only expectations and any note on large datasets or truncation of the preview.

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 opening sentence is well front-loaded, but Sphinx artifacts (':param', ':returns:') leak into agent-facing text, and the object-store advice is spread over four separate sentences that repeat the same idea. Roughly a third of the text could be collapsed into one sentence.

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 with no output schema, the description covers the return shape (test_case_id, session_id or inputs, expected, setup/cleanup), the object-store retrieval path, and the error case. Only the parameter's origin/format and access expectations are left unstated.

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?

Schema description coverage is 0%, so the description must compensate, and it only says ':param dataset_id: The Dataset's id.' — essentially a restatement of the parameter name/title. It does not clarify the id format or where the id comes from (e.g., a prior list_datasets call).

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 and resource ('Fetches one Dataset') and immediately scopes the payload ('with all its test cases, in the order an Experiment replays them'), which distinguishes it from list_datasets and from experiment-level tools. The agent knows exactly what it gets back without opening the 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?

Guidance is given for the output side-channel ('Use the object store tools in combination with the object ID', 'pass this result to other functions'), but there is no guidance on when to call this versus list_datasets, get_experiment, or update_dataset. Usage is implied by 'one Dataset' but alternatives are never named.

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