list_dlp_datasets

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

With no annotations provided, the description carries the full burden of behavioral disclosure. The 'List' verb implies a read operation, but the description does not disclose pagination behavior, response contents, or permission requirements. For a tool with no output schema, this leaves meaningful 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 a single six-word sentence with no wasted words, and the core scope ('for an account') is front-loaded. It earns its place but is minimal to the point of bordering on under-specification, which is penalized in other dimensions rather than here.

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 simple one-parameter list tool, the description adequately conveys the primary operation and account scoping, and the schema fully covers the parameter. However, with no output schema and no annotations, the missing return-value and pagination context leaves the definition merely adequate rather than 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 description coverage is 100% — the single account_id parameter is documented with 'The account ID' in the schema itself. Per the baseline rule, when coverage exceeds 80% the description need not add parameter detail. The description's 'for an account' phrasing does reinforce the parameter's role but adds no new information.

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 (List), a specific resource (DLP datasets), and a scope (for an account). It is clear and unambiguous about what the tool does. However, it does not explicitly name or distinguish itself from the sibling get_dlp_dataset, leaving the agent to infer the list-vs-get distinction from the verb alone.

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?

The description gives no guidance on when to use this tool versus alternatives. It does not mention that get_dlp_dataset should be used for a single dataset, nor does it name any sibling or exclusion condition. An agent must infer usage entirely from the tool name and the verb 'List.'

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