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

No annotations are provided, so the description carries the behavioral transparency burden. It clearly indicates the tool is a discovery/listing operation that returns IDs only, which implies a read-only behavior with no side effects. It does not describe pagination or ordering, but for a zero-parameter list tool this is a minor gap.

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 a single, front-loaded sentence with no filler. 'Discovery:' immediately sets the tool's category, and every remaining word adds useful information: what is listed, what kind of IDs, and which sibling tool they feed into.

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?

For a zero-parameter tool with an output schema present, this description is complete. The agent knows the tool lists benchmark experiment IDs for use with cognitive.get_experiment, and there are no parameters to document or edge cases to warn about.

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 has zero properties, so there are no parameter semantics to clarify. Per the baseline for zero-parameter tools, the description does not need to compensate for missing parameter documentation, and the schema coverage is already complete.

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 specific verb ('list') and a specific resource ('recorded benchmark experiment IDs'), and ties the tool to cognitive.get_experiment, which makes its purpose immediately clear. This differentiates it from sibling tools like cognitive.get_experiment, which returns a single experiment's details rather than the list of IDs.

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 phrase 'for cognitive.get_experiment' implies this tool is the discovery step before retrieving a specific experiment, giving some usage context. However, it does not explicitly state when to use this tool versus alternatives or when not to use it, so the guidance remains mostly implied.

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