search-prompt-optimization-jobs

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the description adds minimal behavioral context. It indicates the search is scoped to an experiment, but does not disclose pagination behavior, filter syntax, or what data is returned.

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, short sentence that is efficient and directly conveys the purpose. However, it lacks any structural elements like bullet points or explicit separation of concerns.

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 search tool with no output schema, the description is minimal. It provides the basic scope (experiment) but omits details on returned fields, ordering, or default behavior. The schema covers parameters adequately.

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?

All 4 parameters are fully described in the input schema with 100% coverage. The description adds no additional meaning beyond the schema, meeting the baseline for schema coverage.

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 clearly states the action ('Search') and the resource ('prompt optimization jobs') and scopes it to an experiment. This distinguishes it from sibling tools like 'get-prompt-optimization-job' (single job) and 'create-prompt-optimization-job'.

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?

No guidance is provided on when to use this tool versus alternatives such as 'get-prompt-optimization-job' or 'cancel-prompt-optimization-job'. There is no mention of prerequisites or typical use cases.

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