evaluate_output

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

No annotations are provided, so the description must disclose behavioral traits, but it does not. It does not explain what FJA criteria are, what the output looks like, whether the operation is read-only, or any side effects. The single sentence offers no behavioral transparency beyond the bare action.

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 one short sentence with no filler, which is concise, but it is under-specified for a tool with three parameters and a specific evaluation framework. It lacks structure or elaboration, though it is front-loaded with the core purpose.

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?

Despite the presence of an output schema, the description is incomplete for practical use. It does not explain the FJA criteria or provide any usage context, such as what the evaluation result contains or when this tool is appropriate. The sibling tool further underscores the lack of contextual guidance.

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 and no parameter details in the description, the agent receives no semantic context for 'prompt,' 'response,' or 'user_context.' The description fails to explain how these parameters relate to the FJA criteria, leaving the agent to guess parameter meaning.

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 evaluates an LLM response, using the verb 'evaluate' with a specific resource. It references 'FJA criteria,' which adds specificity, though the acronym is unexplained. It is distinguishable from the sibling 'compare_outputs' in that this evaluates a single response rather than comparing two.

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 provides no guidance on when to use this tool versus alternatives. There is no mention of 'compare_outputs' or any exclusions/prerequisites. The only implied usage is tautological—use it when you need to evaluate a response—which does not help an agent select between sibling tools.

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