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WendongAI

1pdf

by WendongAI

pdf_to_markdown

Convert PDF files to Markdown text, preserving page labels and detecting headings and simple lists for structured output.

Instructions

Extract PDF text as page-labelled Markdown with heading and simple list detection.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fileYesAbsolute path to the PDF file
output_nameNoOutput file path (defaults to same dir with suffix)
Behavior3/5

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

With no annotations, the description carries the burden of disclosure. It reveals key output behavior (page labels, heading and list detection) and its non-destructive nature (extracts rather than modifies). However, it does not mention limitations (e.g., no OCR for scanned PDFs) or what happens to complex layouts, which would improve transparency.

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 a single, focused sentence that front-loads the core action and output format. Every word adds value with no fluff or repetition of schema details.

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?

Given the tool's simplicity (2 params, no output schema), the description adequately covers the core purpose and output specifics. It lacks explicit return value information, but for a conversion tool that writes a file, the description is mostly complete. Minor gaps around edge cases and alternatives are present, but the essential information is there.

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 describes both parameters fully (file path and output_name with default behavior), so schema coverage is 100%. The description adds no additional parameter-level detail, matching the baseline of 3 where the schema does the heavy lifting.

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 specifies the action ('Extract PDF text'), the resource ('PDF'), and the output format ('page-labelled Markdown with heading and simple list detection'). This distinguishes it from siblings like pdf_to_tiff (image conversion) or get_page_text (raw text extraction).

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?

The description implies usage for converting PDF text into a structured Markdown representation, hinting at a need for readable, page-labelled output. However, it does not explicitly mention alternatives or when to prefer this over get_page_text, pdf_to_json, or extract_tables, so guidance remains implicit.

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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