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netintel_page_extract

Extract clean readable text from any article or web page, removing ads and boilerplate. Returns content, word count, reading time, and language.

Instructions

Fetch any article or web page and extract clean readable text stripped of ads and boilerplate. Returns content, word count, reading time, and language. For JavaScript-rendered or bot-walled pages a plain fetch can't read, use netintel_exa_contents instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.61

TDQS

A4.2/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the return shape (content, word count, reading time, language) and the ad/boilerplate stripping behavior, but says nothing about authentication, rate limits, size/timeout limits, or what happens on an unreadable or failed fetch.

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?

Three tight sentences: purpose and output first, the fallback routing last. Every sentence carries information and nothing is padded.

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?

With no output schema and no annotations, the description does cover both the return fields and the key failure routing, which is most of what an agent needs for a single-param read tool. It stops short of error behavior and hard limits, which leaves a modest gap.

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 0% and there is one required param, so the description must compensate. 'Fetch any article or web page' implies the url parameter is a page URL, which is marginally useful, but no format, encoding, or validation details are added beyond the self-explanatory 'url' name.

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 (fetch a page, extract readable text) plus the transformation applied (strip ads and boilerplate). It also names the sibling it is not by pointing to netintel_exa_contents for harder pages, so an agent can distinguish it from netintel_web_fetch/netintel_exa_contents without opening a schema.

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

Usage Guidelines5/5

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

Explicitly names the alternative (netintel_exa_contents) and the exact condition that selects it (JavaScript-rendered or bot-walled pages a plain fetch can't read). The when-to-use boundary is stated rather than inferred.

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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