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document_to_markdown

Downloads a public document (PDF, DOCX, XLSX, ODT, CSV, HTML, XML, images) up to 10 MB and returns its content as clean Markdown for LLM use. Images are described by a vision model. 0.005 USDC per call via x402.

Input Schema

NameRequiredDescriptionDefault
urlYesPublic document URL
maxCharsNo
paymentProofNoPayment proof: USDC tx hash on Polygon or Base (0x...) or Solana tx signature. Omit on the first call to receive the 402 payment instructions, pay, then call again with the proof.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.8/5.0
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 the 10 MB cap, that only public URLs work, per-call cost and x402 payment, and that images are captioned by a vision model rather than OCR'd. It omits failure behavior (oversized document, paywalled/private URL, unsupported format) and any rate-limit or output-size notes.

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 tightly packed sentences: capabilities and limits first, then the cost/payment model. No filler and nothing buried.

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?

No output schema, but the description states the return shape (clean Markdown, images described) well enough. The remaining gap is lead-in to maxChars/truncation behavior and error cases, which matters somewhat for a paid per-call tool but is minor overall.

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 coverage is 67%: url and paymentProof are documented in-schema (paymentProof quite thoroughly), but maxChars has no description anywhere, and the tool description never explains whether exceeding it truncates or errors. At that coverage level the schema does the heavy lifting, so baseline 3 is appropriate with no compensating detail added.

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 (downloads) and transformation (returns content as clean Markdown) over a named set of formats (PDF, DOCX, XLSX, ODT, CSV, HTML, XML, images), plus a size ceiling. It is clear what the tool does, but it never names or contrasts with the closely related siblings web_extract/web_render, so an agent must infer the boundary itself.

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 only implied: 'public document' and 'for LLM use' scope the tool, and '0.005 USDC per call via x402' hints at the metered path, but there is no explicit when-to-use/when-not guidance and no mention of web_extract or web_render as alternatives for HTML/web pages.

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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