compare_visual

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

With no annotations, the description carries the burden of behavioral disclosure. It states that the tool captures a URL, compares against a saved baseline, and returns diff statistics and a diff image. However, it does not explicitly address side effects (e.g., whether a new screenshot is stored), permissions, or failure behaviors, leaving some ambiguity.

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 two sentences, front-loaded with an action verb and resource. Each sentence adds value: the first defines functionality and return content, the second explains the rationale and emphasizes the AI's role. No fluff or repetition.

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?

The tool has moderate complexity with four parameters and no output schema. The description compensates by clearly stating return values (diff stats and diff image) and the intended use case (visual judgment of regressions). It lacks edge-case details like missing baselines or error handling, but overall provides sufficient context for an agent to invoke it correctly.

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 input schema provides 100% coverage with descriptions for all parameters, so the bar is at baseline 3. The description does mention the diff image and false positives, which loosely relates to includeDiffImage, but it does not add significant semantic meaning beyond what the schema already states.

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's function with a specific verb and resource: 'Capture the current state of a URL and compare it pixel-by-pixel against a saved baseline.' This distinguishes it from sibling tools like capture_baseline and list_baselines by focusing on comparison rather than creation or listing.

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 explains the tool's role in detecting regressions and acknowledges that pixel diff alone yields false positives, implying when this tool is appropriate. It does not explicitly name alternatives or state when not to use it, but the context is clear enough for an AI agent to select it over siblings.

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