critique_answer

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

No annotations are provided, so the description must fully disclose behavioral traits. It states the tool returns per-model critiques, which is helpful, but does not mention potential costs, rate limits, or any side effects. It lacks depth but is not misleading.

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 two sentences long, front-loading the action and then the value. Every word earns its place; no fluff. It is highly concise and well-structured.

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 there is an output schema, return values are covered. However, the tool has 5 parameters and 3 required ones, and the description does not mention anything about token usage, model availability, or possible constraints. It is adequate but could provide more context for a critique tool.

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 100%, so the description does not need to add much. It does not provide additional semantics beyond the parameter descriptions in the schema, such as clarifying the role of 'model_aliases' or 'temperature.' Baseline score of 3 is appropriate.

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's purpose: 'critique a draft answer to a question' and 'Returns per-model critiques with identified weaknesses and suggested improvements.' It uses a specific verb and resource, and distinguishes from sibling tools like 'ask_model' (which generates answers) and 'pick_best_answer' (which selects).

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 mentions 'Useful for improving a draft before finalizing it,' which provides clear context for when to use the tool. However, it does not explicitly state when not to use it or compare to alternatives, though sibling names imply different purposes.

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