visual_check

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

No annotations provided, but the description fully discloses behavior: default saves to disk and returns path, mode-dependent image return, degradation on failure, and cross-library support. This is comprehensive transparency for a mutable tool without annotations.

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?

Well-structured and front-loaded with purpose. While slightly verbose, each sentence adds unique value (use cases, parameter logic, mode details). Minor penalty for length but still efficient.

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?

No output schema, but description explains both return formats (path string vs image block). Covers failure behavior, library compatibility, and references another guidance tool. Complete for a screenshot action with 3 parameters.

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 0%, so description carries full burden. It explains filename (optional, implied), session_id (required), and return_image with detailed context on when to use true vs false, including mode constraints—far beyond what the schema alone provides.

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 captures a screenshot for visual validation and explicitly lists use cases where DOM/ARIA checks are insufficient (canvas/image text, layout, overlap, color). This distinguishes it from sibling tools like execute_step or get_locator_guidance.

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?

Provides explicit guidance: when to use (visual validation), when to set return_image=true (multimodal models unable to read saved file), and references get_locator_guidance('visual') for deeper decision-making. Also warns about text-only deployments not supporting image content.

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