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pdf_to_text

PDF to Text — COPY THE WORDS OUT of a PDF: get the wording, sentences and paragraphs as plain text you can paste into an email, a document or a spreadsheet. Extract the text that is already inside a PDF and return it as a plain .txt file. Reads the PDF's existing text layer using pdftotext with a Ghostscript txtwrite fallback — it does NOT run OCR. A scanned or photographed document has no text layer, so this tool refuses it with a 422 naming pdf_ocr rather than returning an empty file; run pdf_ocr first to add a searchable text layer, then extract. Mixed documents still succeed: pages that yielded no text are reported in the X-Conversion-Notes response header instead of being dropped silently. [category: pdf]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fileYesInput file (PDF)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

The description discloses important behavioral details beyond the annotations: it uses pdftotext with a Ghostscript txtwrite fallback, refuses scanned documents instead of returning an empty file, and reports empty pages via the X-Conversion-Notes response header. This gives the agent a clear mental model of success and failure modes.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with purpose and then provides implementation and error-handling details. There is minor redundancy between the first and second sentences, but each additional sentence contributes useful behavioral context, so it remains appropriately sized.

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?

For a one-parameter conversion tool with no output schema, the description is complete: it explains what the tool returns, how it works, when it will fail, what error to expect, and what the caller should do in that failure case. Nothing needed for correct selection or invocation is missing.

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?

The schema already documents the single 'file' parameter as an input PDF with 100% coverage. The description adds meaningful context by explaining that the PDF must contain an existing text layer and that scanned files will be rejected, which is valuable semantic information beyond the raw schema.

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 states a clear verb-resource pair: extract the text already present in a PDF and return it as a plain .txt file. It explicitly says it uses the existing text layer and does NOT run OCR, which distinguishes it from OCR-based tools like pdf_ocr and photo_to_text.

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?

The description gives explicit when-to-use guidance and names an alternative: if the PDF is scanned or photographed and has no text layer, the tool returns a 422 with a reference to pdf_ocr, and the agent is told to run pdf_ocr first. It also covers mixed documents, saying pages with no text are reported rather than silently dropped.

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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