list-experiments-for-dataset

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

No annotations provided, and the description does not explicitly state that the operation is read-only, nor does it disclose any potential side effects. It only describes return format without 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?

The description is moderately concise with clear sections (purpose, example usage, expected return). However, it could be more succinct without losing essential information.

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 lack of output schema, the description provides expected return format, but missing parameter explanations and usage context. The tool has 3 parameters with no guidance, making it incomplete for an agent to use correctly.

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%. The description does not explain the three parameters (dataset_id, dataset_name, limit) or their roles, leaving the agent without guidance on how to use them. The example uses a dataset ID but does not clarify which parameter is used.

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 'Get a list of all the experiments run on a given dataset' with specific verb (Get), resource (experiments), and condition (on a given dataset). Differentiates from siblings by specifying retrieval of experiments by 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?

Includes an example usage and expected return, but does not explicitly state when to use this tool versus alternatives like 'get-dataset-experiments'. No guidance on prerequisites or limitations.

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