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pdf_to_markdown

Read-onlyIdempotent

Converts PDF to reading-order Markdown for LLM consumption. Reconstructs up to 2 content columns, infers headings from font size, detects lists; tables rendered as plain text.

Instructions

Convert a PDF to clean, reading-order Markdown for LLM consumption: reconstructs up to 2 content columns (plus full-width title/footer bands), infers headings from font size, and detects bullet/numbered lists. Pages with 3 or more columns fall back to single-column reading order. Tables are emitted as plain reading-order text, NOT reconstructed as Markdown tables. Best on clean, digital (text-based) PDFs; degrades on scanned/image-only PDFs (use pdf_render_pages for those) and very complex layouts. Returns the first 10 pages by default.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filePathYesAbsolute path to the PDF file
pagesNoPage range, e.g. '1-5' or '1,3,5'. Defaults to first 10 pages.
Behavior5/5

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

Annotations provide readOnlyHint, destructiveHint, idempotentHint. Description adds details on column reconstruction, heading inference, list detection, table treatment, and page defaults. No contradiction.

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?

Single well-structured paragraph front-loading purpose, then details, then limitations. Every sentence adds value with no redundancy.

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?

Covers most aspects: output format (Markdown), page handling, limitations. Could be more explicit about return type (e.g., string), but good for a tool without output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, but description adds context: page range format examples and default behavior (first 10 pages). FilePath requirement is clear.

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 converts PDF to Markdown for LLMs, with specific details on column handling, heading inference, list detection, and table behavior. It distinguishes from sibling tools like pdf_render_pages.

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 states best use case (clean digital PDFs), warns about scanned PDFs and complex layouts, and recommends pdf_render_pages as alternative for scanned PDFs.

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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