search-experiments

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

Annotations already declare readOnlyHint=true and openWorldHint=true, indicating safe read behavior. The description adds minimal behavioral context beyond what's in the schema (filter and pagination). It does not explain response format, default behavior, or any side effects, but since annotations cover safety, the bar is lowered. However, the description still lacks useful 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 a single sentence with no extra words, achieving high conciseness. It is front-loaded with the purpose, but could include more useful information without becoming verbose.

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 6 parameters, no output schema, and many sibling tools, the description is too sparse. It does not explain pagination mechanics, filter syntax beyond schema, or how to use it effectively, leaving gaps for an AI agent.

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 100%, so the schema already documents all parameters. The description adds no additional meaning beyond what's in the schema, so a 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 'Search experiments with filter and pagination', which clearly identifies the tool's action and scope. However, it does not differentiate from sibling search tools like 'search-runs' or 'search-logged-models', so it lacks explicit distinction.

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 does not provide any guidance on when to use this tool versus alternatives. It implicitly covers search, but no when-to-use, when-not-to-use, or prerequisites are mentioned, which is a gap given the many sibling search tools.

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