ai_risk_classify

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

Describes the evaluation process and references regulations, and notes the return is a 'structured analysis framework for the host to complete,' implying interactive use. No annotations are present, so the description carries the full burden but does not disclose all behavioral traits (e.g., side effects, auth requirements).

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 well-structured with a clear purpose statement, explanation of the evaluation framework, and an Args section. It is reasonably concise for the complexity, though some sentences could be tightened.

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?

Given the single parameter and presence of an output schema, the description provides adequate context for the tool's purpose and input. The notion of a 'structured analysis framework' is somewhat vague, but sufficient for an agent to understand the tool's role.

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?

With 0% schema description coverage, the description compensates by providing detailed guidance on what to include in the deployment_description parameter (system purpose, users, decisions, data, oversight). This adds significant meaning beyond the schema's basic type and title.

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?

Clearly states it classifies risk tier and applicable regulations for an AI deployment, referencing specific controls (HOC-001, EU AI Act, NIST AI RMF). Does not explicitly differentiate from sibling tools like ai_red_team and ai_safety_screen, but the distinct purpose is evident.

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?

Provides guidance on when to use (evaluating deployment description against HOC-001) and what to include in the description. Lacks explicit when-not-to-use examples or alternatives, though the context of siblings might imply they are for different tasks.

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