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web_extract

Read a web page as clean Markdown for an LLM: fetches the URL, drops navigation, header, footer, forms and scripts, and returns the main text as Markdown with title, description, language, author, publish date, image and word count. Optional links=true adds the page's links. Text and JSON URLs come back as-is. Costs $0.002 USDC on Base via x402.

Input Schema

NameRequiredDescriptionDefault
urlYesPage URL
linksNotrue adds the page's links (up to 300)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses exactly what content is discarded, what metadata is returned, the 300-link cap, the passthrough behavior for text/JSON URLs, and — critically — that each call costs $0.002 USDC on Base via x402. It omits failure modes, size/timeout limits, and whether JS-rendered pages are supported, which keeps it from a 5.

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?

The core operation is front-loaded in the first clause, followed by two short, purposeful sentences for the optional parameter and pricing. Every clause adds information; nothing is padding or repetition of the title.

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?

There is no output schema, and the description compensates by enumerating the returned metadata fields (title, description, language, author, publish date, image, word count) and the shape of the result (Markdown main text). The paid x402 requirement is also covered, which is the highest-stakes unknown; only error/limit behavior is left unaddressed.

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%, so the schema already documents both parameters, making 3 the baseline. The description adds only marginal meaning — the 'text and JSON URLs come back as-is' clause implies url handling varies by content type, and the links note restates the schema's own 'up to 300' wording rather than extending it.

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

Purpose5/5

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

States a specific verb and resource ('Read a web page as clean Markdown'), then makes the transform concrete: fetch URL, strip navigation/header/footer/forms/scripts, return main text plus metadata. The word 'web page' plus the Markdown-conversion framing cleanly separates it from document_to_markdown (documents) and website_audit (auditing) among the siblings.

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

Usage Guidelines3/5

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

Usage is implied by the LLM-consumption framing and the note that text/JSON URLs pass through unchanged, which hints at when the tool is not the right choice for those URLs. However, there is no explicit when-to-use/when-not-to-use statement and no pointer to alternatives such as document_to_markdown for non-HTML content.

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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