audit_dataset

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. It does not state whether the tool is read-only, what side effects or outputs are produced, or how it behaves with partial parameters. The term 'Detect' implies analysis, but this is not explicit and important behavioral details are missing.

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 extremely concise with no fluff, but it is a flat list of risk categories rather than a structured explanation. It is brief and front-loaded, yet the brevity comes at the cost of needed detail.

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 5-parameter tool with no output schema and no annotations, the description is incomplete. It does not explain what the audit produces, how to provide required inputs, or what constraints exist. The agent lacks critical context needed to invoke it 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?

Schema description coverage is 0% and there are 5 parameters, so the description must compensate. It mentions 'target', 'entity', and 'temporal', which vaguely map to the target, entity, and time_column parameters, but it does not explain their formats, relationships, or the required path parameter.

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 ('Detect') and a clear resource (dataset risks), enumerating concrete risk categories: target, entity, and temporal leakage, PII, identifiers, and metric risks. This distinguishes it from siblings like profile_dataset and audit_training_code, which focus on profiling and code auditing respectively.

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 profile_dataset, audit_training_code, or review_feature_availability. It does not state conditions, exclusions, or alternatives, leaving the agent to infer the appropriate selection context.

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