evaluate_response_quality

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does not say whether the evaluation is deterministic, what the rubric scores, what the score range is, or that the third parameter is optional — all of which matter for interpreting the result.

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?

A single short sentence with no filler and the core action front-loaded. It is efficient, though the brevity is partly under-specification rather than disciplined concision.

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?

An output schema exists, so return values need not be described, but with zero annotations and zero schema coverage the description is too thin for a tool whose whole value is the rubric it applies. Nothing tells the agent what 'quality' means here or how 'category' changes the evaluation.

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% for three parameters, and the description adds no parameter information at all. 'prompt' and 'response' are self-explanatory by name, but 'category' with its 'general' default and its effect on the rubric is completely 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?

States a specific verb+resource ('Evaluate response quality'), which is clearer than a tautology, but 'heuristic rubric' is left vague — the agent cannot tell what criteria are applied or how this differs from siblings like bloom_evaluate_model or run_calibration_test. Names a sibling-adjacent concept without differentiating itself.

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?

No when-to-use guidance, no when-not-to, and no named alternative. Given the crowded sibling list containing several evaluation/calibration tools, the agent is left to guess when this tool is the right choice.

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