select_assays

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

No annotations are provided, so the description carries full burden. It reveals the interactive, stateful nature (first vs second call), the prompting for study_id if missing, and the pairing of indices. While it doesn't explicitly state read-only or permission requirements, the behavior is well-disclosed for a selection tool.

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 somewhat lengthy due to detailed step-by-step instructions, but it is well-structured with bullet points and clear sections. Most sentences provide necessary information, though some redundancy could be trimmed.

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 the presence of an output schema (not shown), the description appropriately avoids detailing return values. It covers the interaction flow, input constraints, and formatting instruction. The description is complete for an agent to understand the tool's full behavior.

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?

With 0% schema description coverage, the description thoroughly explains both parameters: study_id (if missing, prompt; example given) and selection (string of comma-separated indices, pairs consecutive indices, must be even count). This adds critical meaning beyond the schema.

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 tool lists and selects assays for a study and renders the response in markdown format. The verb 'list and select' combined with the resource 'assays' provides a specific purpose. It also distinguishes from sibling tools, which are focused on different data operations.

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 outlines a two-step process: first call to generate a menu, second call with a selection string. It specifies when to provide study_id, how to format selection, and that an even number of indices is required. This provides clear guidance on when and how to use the tool.

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