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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, so the safety profile is covered. The description adds useful behavioral context by describing the output structure and the async option ('Pass async:true to avoid timeout'), which goes beyond the schema and annotations.

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 three sentences, front-loading the main purpose, then efficiently listing inputs, outputs, use case, and async tip. Every sentence adds value without redundancy or fluff.

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 has an output schema, so return values are covered structurally. The description still provides essential context: inputs, outputs, use case, and async behavior. No critical information is missing for selection and invocation.

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 50%, meaning two parameters (risk_threshold and include_bias_metrics) lack schema descriptions. The description mentions 'optional risk thresholds' for risk_threshold and 'dataset identifier (Hugging Face ID or URL)' for dataset_id, but it doesn't explain include_bias_metrics at all. This partially compensates but leaves one parameter semantically undocumented.

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 states the tool audits AI training datasets for EU AI Act compliance, with bias detection and regulatory risk assessment. It specifies the primary resource (training datasets) and distinct outputs (compliance score, bias metrics, regulatory warnings, source references), setting it apart from sibling tools like ai_act_incident_response.

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?

It explicitly notes the tool is 'Ideal for pre-deployment risk evaluation', giving a clear use case. However, it does not mention when not to use it or suggest alternative tools for other compliance tasks, so it lacks direct exclusions/alternatives but provides enough context.

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