select_option

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

With no annotations, the description carries full burden. It discloses auto-detection and that custom dropdowns are handled by clicking then finding by text cascade, but does not detail waiting behavior, error handling, or side effects like state changes.

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?

Two sentences, no fluff. Front-loaded with main action, then details. Every sentence earns its place.

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 tool's simplicity, the description adequately covers the main scenarios and behavior. It does not explain return values, but no output schema exists, and the tool's purpose is straightforward.

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 coverage is 100%, so baseline is 3. The description adds the notion of 'text cascade' for custom dropdowns, which adds marginal meaning beyond the schema's field descriptions. No significant new parameter semantics.

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 selects from native <select> or custom dropdown, auto-detects type, and explains custom dropdown behavior. This distinctively identifies the tool's purpose and resource, differentiating it from siblings like click_element or fill_form.

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 provides context on when to use the tool (for selecting options from dropdowns) and distinguishes between native and custom types, but lacks explicit exclusion statements or alternative tool names as seen in the calibration example.

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