get_dataset_info

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

With no annotations, the description carries the behavioral burden. 'Return' indicates a read-only operation and the exact output fields are listed, which is transparent. However, it does not disclose prerequisites, error behavior, or whether an active connection is required, leaving some behavioral gaps.

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 minimal and front-loaded: one sentence states the purpose and exact output, followed by a single-line parameter explanation. Every element earns its place with no redundant wording.

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 tool with one required parameter, no nested objects, and an output schema present, the description covers purpose and parameter adequately. The main missing element is usage guidance, but the simple read-only nature of the tool makes the description mostly complete.

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 schema only defines 'dataset' as a string with no description, while the description's Args section adds meaningful semantics: 'Fully-qualified dataset name'. This compensates for the 0% schema coverage, though it could include an example or naming convention for full clarity.

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 uses a specific verb ('Return') and resource ('DCB attributes') for a single dataset, enumerating exact attributes (RECFM, LRECL, BLKSIZE, DSORG, volume). This clearly distinguishes it from sibling tools like list_datasets or read_member, which operate on dataset lists or member content.

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?

No explicit guidance is given about when to use this tool versus siblings such as list_datasets or read_member. The purpose is implied by the description, but there are no usage conditions, exclusions, or alternative-selection heuristics.

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