Render a webpage in a real browser with JavaScript enabled, then extract clean text. Returns a job ticket for async processing; poll to retrieve results.
Render a page in a real browser (JavaScript included), return clean text ($0.02 USDC/call). ASYNC — returns a job ticket; poll with x402_poll_job (job_type 'box').
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Page URL |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and does an excellent job: it discloses that the tool runs a real browser with JavaScript, is asynchronous (returns a job ticket), requires polling with a specific job type, and has a cost per call. It also notes the output format (clean text) implicitly. This gives the agent a clear behavioral model without relying on 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?
The description is concise—two sentences—with the core purpose front-loaded, followed by cost and async behavior. Every clause adds value: the real browser/JS detail, cost, async job ticket, and polling instructions. There is no filler 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?
For a tool with a single parameter, no output schema, and no annotations, the description is complete. It tells the agent how to invoke it (url), what to expect (job ticket), how to get the result (poll), and the cost. The mention of job_type 'box' ensures the polling call is correctly parameterized. Nothing essential is missing for a correct invocation.
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 has 100% description coverage for the single 'url' parameter, so the schema already documents it as 'Page URL'. The tool description adds little beyond referencing 'render a page', which aligns with the parameter. This meets the baseline of 3; it does not introduce additional semantics or format constraints.
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 a specific verb ('Render') and resource ('a page in a real browser'), and clarifies that it includes JavaScript and returns clean text. It distinguishes itself from sibling tools (e.g., x402_read, x402_screenshot) by being the rendering tool. The async/polling note adds nuance without obscuring the core purpose.
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 provides clear usage context: it is asynchronous and must be polled via x402_poll_job with job_type 'box'. It explicitly instructs the agent on how to handle the asynchronous response. However, it does not explicitly mention when not to use this tool or compare it to alternatives like x402_read, leaving some inference to the agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.