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

Annotations indicate readOnlyHint=true and openWorldHint=true, which align with the description's mention of server-side generation with no API key needed, adding useful context. The description also discloses that it picks appropriate evaluators based on task type, which is beyond annotations, but doesn't detail side effects or limitations like model latency.

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: it states what it generates, the model used, and the output integration, all in three sentences. It avoids unnecessary detail and each sentence contributes to understanding the tool's purpose and behavior.

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 tool's moderate complexity, the description covers essential aspects: generation, model, output usage, and evaluator selection. With a high schema coverage and an output schema present, the description does not need to explain return values. It misses a bit on how the tool handles ambiguous task descriptions, but overall it is fairly complete.

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?

The schema already provides 100% coverage with descriptions for all parameters, including enums and hints. The description adds some value by explaining how task_type influences evaluator selection and mentions scenario_count covers happy path/edge cases/adversarial, but does not deeply elaborate beyond schema. Baseline 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 that the tool generates a complete .ia-eval.yaml evaluation contract from a plain-language description, which is a specific verb and resource. It differentiates from siblings like generate_test_cases and prompt_test_suite by focusing on the evaluation contract format and integration with run_eval_contract.

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 when to use it (when you need a ready-to-run evaluation contract) and mentions it pairs with run_eval_contract, but does not explicitly state when not to use it or name specific alternatives. However, the context is clear enough for an agent to decide.

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