create_eval_dataset

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

No annotations are provided, so the description carries the full burden. It discloses that frozen=true makes items permanently immutable, which is a critical behavioral detail. It also mentions the item limit. However, it does not describe the return value or error conditions, missing some behavioral details.

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?

Three sentences: first defines the action, second covers limits, third explains frozen. All sentences are essential and front-loaded. No wasted words.

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?

Covers key constraints and behavioral aspects. Lacks return value description and prerequisites (e.g., authentication), but for a creation tool with no output schema, it is mostly complete. The sibling tools provide context for retrieval.

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 coverage is 100%, so baseline is 3. The description adds value beyond the schema by explaining that inputText is fed to the model and expectedOutput is used as a judge reference, and that name must be unique within the account. This enriches parameter understanding.

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?

Clearly states the action 'Create a golden dataset' with the HTTP method and resource, and includes the 'Pro+ only' restriction, distinguishing it from other dataset-related tools like run_eval_dataset or get_eval_dataset.

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?

Provides important usage constraints: Pro+ only, up to 20 test cases, up to 50 datasets per account, and the effect of frozen=true. However, it does not explicitly mention when to use this tool versus alternatives or when not to use it.

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