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

Beyond the readOnly/idempotent annotations, it discloses a significant behavioral trait: the review sends a screenshot and page text to OpenAI unless the workspace has turned checks off. It also describes the actual return content (render errors, console errors, datasets, gaps), which is essential since there is no output schema.

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?

Three sentences, front-loaded with the core action and its outputs before moving to conditions and routing. The final sentence is long and stacks three alternatives, but every clause carries information an agent needs.

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?

With no output schema, the description fully compensates by enumerating the reported artifacts, and the usage section plus the OpenAI/opt-out disclosure cover the operational context. Nothing an agent needs to call this correctly is missing.

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 100%, so the baseline is 3, and the description goes further by explaining the intent behind screenshot=true ("so you can judge the layout yourself") rather than restating the schema's wording. The slug parameter is left entirely to the schema, which is acceptable here.

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 states a specific verb+resource ("test-renders a view in a real headless browser") and enumerates exactly what it reports: render errors, console errors, loaded datasets, and missing content. It also explicitly distinguishes itself from create_view and update_view, which already run the check automatically.

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?

It names three concrete triggers for calling this tool (wanting the screenshot, after changing a dataset, confirming the review is clean before telling the user it is done) and states the default behavior of the sibling tools that already run it. When-to-use and when-it-is-redundant are both covered.

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