get_dlp_dataset

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

With no annotations provided, the description carries the behavioral burden. 'Get' implies a read operation with no destructive side effects, which is accurate, but the description does not disclose what 'details' are returned, possible error behavior, or idempotency. It is minimally adequate but thin.

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 a single sentence with no wasted words and is easy to scan. It loses one point because the brevity is somewhat boilerplate ('get details') rather than adding structuring detail that would make the description more informative.

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?

The tool is low complexity, the schema fully documents both required parameters, and the get semantics are clear enough to make a correct call. However, there is no output schema, no annotations, no description of what the returned details contain, and no relationship to sibling tools like list_dlp_datasets, leaving meaningful gaps for an agent.

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 100%, with account_id and dataset_id already described in the input schema. The tool description adds no parameter-specific meaning beyond implying the dataset is selected by ID, so it stays at the baseline.

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 clearly identifies the action ('get') and resource ('specific DLP dataset'). The word 'specific' signals a single-item fetch rather than the listing behavior of sibling list_dlp_datasets, and 'DLP dataset' distinguishes it from other resource getters in the sibling list.

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?

There is no guidance about when to use this tool versus list_dlp_datasets or get_dlp_profile, nor any precondition such as needing a known dataset_id. The word 'specific' is only an implicit hint, not explicit usage direction.

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