dex-data

url_to_markdown

Convert a public article or PDF URL into clean Markdown, extracting title, byline, site name, and word count. For PDFs, includes page count and text layer.

Instructions

Fetch a public article or PDF URL and return clean Markdown plus title, byline, site name and word count. HTML is extracted with Firefox reader-mode rules; PDFs return their text layer with page count. Image-only PDFs and client-rendered app shells return typed errors (no_text_layer, not_extractable) instead of empty output passed off as the article.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "url": "<url>"
    },
    "name": "url_to_markdown"
  }
}

Input Schema

Name	Required	Description	Default
`url`	Yes	Public http(s) URL of an article or PDF.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 7, 2026

TDQS

A4.5/5.0

Behavior5/5

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

With no annotations, the description fully carries the behavioral transparency burden. It discloses the extraction method (Firefox reader-mode rules), the PDF text-layer behavior with page count, and the typed errors (no_text_layer, not_extractable) for edge cases. This gives the agent a complete picture of expected outcomes and failure modes, exceeding what a typical description provides.

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 description is two sentences, front-loaded with the primary purpose and output, and each sentence adds essential information (what it does, how it handles HTML/PDF, and error behavior). There is no fluff or repetition, making it highly efficient.

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

Completeness5/5

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

Given the simplicity of the tool (one parameter, no output schema, no annotations), the description is remarkably complete. It covers the input, the output structure (Markdown plus metadata), the processing method, and specific error cases. Nothing an agent needs to know to call it correctly is missing.

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?

The input schema already provides 100% coverage of the single parameter 'url' with a clear description: 'Public http(s) URL of an article or PDF.' The tool description repeats the same information without adding new semantics or examples, so it adds minimal value beyond the schema. Baseline 3 is appropriate.

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?

The description clearly states the tool's function: fetching a public article or PDF URL and returning clean Markdown plus metadata (title, byline, site name, word count). It distinguishes from siblings like read_feed by specifying the Markdown conversion output and error handling, making it unambiguous.

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

Usage Guidelines4/5

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

The description implies when to use the tool (whenever a URL needs to be converted to Markdown), and notes that it handles both HTML and PDFs. It does not explicitly mention alternatives or when not to use it, but the clear purpose and specific error cases provide sufficient usage context without needing explicit exclusions.

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