List Experiments

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It does reveal that results are ordered most recent first and that experiments are persistent resources that should be destroyed, which is useful context. However, it does not explicitly state that this is a read-only operation or describe any other behavioral nuances such as default status handling.

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 extremely concise, with the core purpose in the first sentence and practical usage guidance in the second. Every sentence adds distinct value, and the structure front-loads the most important 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?

This is a simple listing tool with optional parameters and an output schema, so the description does not need to explain return values. It gives the ordering and the intended use cases. A slight gap is the absence of explicit guidance about when to prefer get_experiment for single-item lookup, but overall the tool is sufficiently contextualized.

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 input schema already provides 100% documentation coverage for both parameters, including defaults, constraints, and examples. The description adds no additional parameter-level meaning beyond what the schema contains, so the 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 states a clear verb and resource: 'List experiments', and adds the ordering 'most recent first'. This distinguishes it from sibling tools like get_experiment, which retrieves a single experiment. The use-case reference to sandboxes also makes the tool's purpose concrete.

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 explicitly says when to use the tool: to find a previously created sandbox or to check for undestroyed experiments before creating another. It does not explicitly name alternatives or exclusion conditions, so it falls short of the strongest usage guidance, but the context is clear.

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