run_visual_test

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

With no annotations provided, the description must fully disclose behavioral traits. It states that the tool uses a 'real browser' (a nontrivial resource implication) and returns a pass/fail report, but it omits key details such as whether the tool is read-only, any potential side effects (e.g., network requests to the target URL), error handling (e.g., invalid URL), or timeouts. This is insufficient for an agent to predict execution consequences.

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 with no redundant words. The first sentence front-loads the core action and scope, and the second enumerates check types and the output. Every element contributes directly to understanding the tool—no filler or filler phrases. It is exemplary in efficiency.

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 there is no output schema or annotations, the description must fully equip an agent to call the tool. It fails to specify the exact format of the 'checks' array (e.g., that each check needs both type and value), and the promised 'detailed pass/fail report' is not described in terms of structure or fields. The tool's complexity (nested object array, four distinct check types) demands more explicit guidance than provided.

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 the description must compensate. It adds meaning to the 'checks' parameter by explaining each enum value ('has_text', 'has_element', etc.), which the schema only lists mechanically. However, it does not explain the structure of the checks array (each item requires a 'type' and a 'value'), nor does it clarify that the 'url' parameter should be a valid URI or how the value field is used per check. Thus it partially compensates but leaves structural ambiguity.

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: running visual checks against a URL using a real browser. It enumerates the four supported check types with brief explanations, which precisely defines the resource and scope. This distinguishes it from sibling tools (take_screenshot, scrape_page) which focus on capture rather than validation, even though siblings aren't explicitly named.

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 when to use this tool (when you need to verify page content via checks) but does not explicitly contrast it with alternatives like take_screenshot or scrape_page. It provides no guidance on when NOT to use it or conditions that would favor a sibling tool. The usage context is clear from the purpose but lacks explicit routing.

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