score_response

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

No annotations provided, so description carries full burden. It mentions that scorers reusing LLM judge use the engagement's target, but does not disclose side effects (e.g., is it idempotent?), error handling, or permission 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 concise and front-loaded with the primary purpose. The three sentences each add value without 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?

With 5 parameters, no schema descriptions, and no annotations, the description leaves significant gaps. It does not mention required permissions, async behavior, or constraints on inputs (e.g., valid scorer names).

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 the description does not explain each parameter beyond 'named PyRIT scorer' for scorer_name. Parameters like scorer_params and conversation_id are left ambiguous.

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 scores arbitrary text using a named PyRIT scorer, and lists the return fields. However, it does not explicitly differentiate from sibling tools like get_scores, which might retrieve existing scores.

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 implies usage when you want to score text and references list_capabilities to find available scorers, but lacks explicit guidance on when to use this tool versus alternatives (e.g., get_scores).

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