Find Element by Description (AI) [Pro]

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

No annotations are provided, so the description carries full burden. It indicates the tool is a read operation (vision-based, returns info) and mentions it is 'Pro', but does not disclose potential latency, error cases, or that AI vision may require network or permissions.

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 extremely concise with three sentences; the first sentence explains the core action, the second lists return values, and the third provides usage guidance and examples. No filler.

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 no output schema, the description compensates by listing return values (coordinates, type, confidence). The two parameters are well-covered by schema. However, it could mention that the query must be descriptive or that results may vary based on AI model.

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 describes both parameters. The description adds example queries for the 'query' parameter but does not provide additional semantics 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 it uses AI vision to find a UI element by natural language description and returns coordinates, type, and confidence. It effectively distinguishes from siblings like get_ui_elements (which returns all elements) and find_element (non-pro version presumably), though the sibling list includes similar tools like wait_for_element and verify_screen.

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 advises using it when locating a specific button, field, or other UI element, with example queries. It does not explicitly exclude alternatives like get_ui_elements or analyze_screen, but the context is clear enough for an AI agent to decide.

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