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scrape_webpage

Scrape a webpage and retrieve its content in markdown, HTML, text, or JSON format. Pay per call using USDC on Base.

Instructions

Scrape any webpage and return content as markdown, html, text, or json. Pay-per-call web scraping for AI agents.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe URL to scrape (http or https)
formatNoOutput format (default: markdown)
wait_forNoCSS selector to wait for before extracting
wait_msNoMilliseconds to wait after page load (max 10000)
viewportNoViewport size (default: desktop)
Behavior3/5

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

The description mentions 'Pay-per-call' as a behavioral cost, which is helpful. However, it lacks details on rate limits, error handling, JavaScript execution, or any destructive actions. Since no annotations are provided, the description carries the full burden, and this is insufficient for a scraping tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise at two sentences, with no unnecessary words. It conveys the core function and a key behavioral note. However, it could be slightly more structured by front-loading the primary action and then format options.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 5 parameters and no output schema, the description should provide more context about return values, error conditions, or prerequisites. It only mentions output formats and pay-per-call, leaving gaps about behavior like waiting, viewport, or URL validation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

All 5 parameters are described in the schema (100% coverage). The description adds limited value by listing output formats, but this is already covered by the enum. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Scrape any webpage' and lists output formats, which is a specific verb+resource. However, it does not distinguish from sibling tools like extract_structured_data, which might also scrape but for different purposes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. For example, there is no mention of when to use scrape_webpage over screenshot_webpage or extract_structured_data.

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

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