ui_to_artifact

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

With no annotations provided, the description bears full responsibility for behavioral transparency. It discloses the core function and output types but omits details like file size limits, supported image formats, or whether the tool modifies anything. The description is straightforward but lacks depth on behaviors.

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, front-loaded sentence with no redundant information. Every word contributes to understanding the tool's purpose and outputs.

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 has only two parameters, no output schema, and no annotations, the description provides adequate context for typical usage. It could mention output format or limitations, but overall it is sufficient for an agent to select and invoke the tool.

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?

The schema already describes both parameters and covers 100%. The description adds value by explaining what each outputType value produces ('code' means HTML/CSS/React, 'prompt' means AI image gen prompt, etc.), which goes beyond the enum list.

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 converts UI screenshots into structured deliverables, listing four distinct output types (code, prompt, spec, description). This distinguishes it from sibling tools like analyze_data_visualization or diagnose_error_screenshot, which target specific use cases.

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 implies usage for converting UI screenshots but provides no explicit guidance on when to use this tool versus alternatives. It does not mention when not to use or which sibling handles other types of screenshots.

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