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clean_web_scrape

Scrape any public webpage and convert it into clean, sanitized, token-efficient Markdown for LLM ingestion, automatically paying HTTP 402 microtransactions when required.

Instructions

Scrapes any public webpage and returns clean, sanitized, token-efficient Markdown for LLM ingestion. Automatically handles HTTP 402 microtransactions (0.005 USDC on Base) if required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe target webpage URL to scrape (must start with http:// or https://).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.4.1

TDQS

A3.6/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden and does disclose a non-obvious trait: automatic HTTP 402 microtransaction handling at 0.005 USDC on Base, i.e. this call can incur cost. It leaves out rate limits, JS-rendering behavior, and failure modes for blocked or dynamic pages, so it is good but not complete.

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

Conciseness5/5

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

Two sentences, zero filler: the purpose and output contract come first, and the payment caveat follows. Every clause earns its place.

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

Completeness4/5

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

For a single-parameter, no-output-schema tool, the description covers purpose, return format, and cost behavior adequately. It stops short of describing how the tool behaves on pages requiring JS, login, or anti-bot measures, which matters for a scraper.

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?

Schema description coverage is 100% with a single well-documented url parameter, so the schema does the heavy lifting and the baseline is 3. The description adds no format or constraint detail (e.g. handling redirects or non-HTML content) beyond what the schema already states.

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?

States a specific verb (scrapes) and resource (any public webpage), plus the output form (clean, sanitized, token-efficient Markdown for LLM ingestion). This clearly separates it from siblings like clean_web_search or synthesize_web_digest, though no sibling is named explicitly.

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?

The description never says when to pick this over clean_web_search or synthesize_web_digest, nor what prerequisites exist. The only implicit guidance is the 'public webpage' scope constraint, which mildly excludes authenticated/private pages but is not framed as usage guidance.

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