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hancengiz

PDF Reader MCP Server

by hancengiz

read-pdf

Extract text content from PDF files with options for page filtering, text cleaning, and metadata inclusion. Use this tool to retrieve specific information from PDF documents without manual reading.

Instructions

Extract text from a PDF file. Returns the full text content of the PDF with optional page filtering and text cleaning.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fileYesPath to the PDF file to extract text from
pagesNoPage range (e.g., '1-5', '1,3,5', 'all'). Default: 'all'
clean_textNoClean and normalize extracted text. Default: false
include_metadataNoInclude PDF metadata in output. Default: true
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the tool's behavior by stating it 'returns the full text content' and mentions optional features like page filtering and text cleaning. However, it lacks details on error handling, performance characteristics, or limitations (e.g., file size constraints, supported PDF formats), which would be valuable for an agent.

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 core purpose ('Extract text from a PDF file') followed by additional context about return values and optional features. Every sentence adds value without redundancy, making it efficiently structured and appropriately sized.

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 moderate complexity (4 parameters, no output schema, no annotations), the description is reasonably complete. It covers the main purpose and key behavioral aspects (returning text, optional features). However, without an output schema, it could benefit from more detail on the return format (e.g., structure of the text output, handling of metadata), slightly reducing completeness.

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 has 100% description coverage, providing clear documentation for all 4 parameters. The description adds minimal value beyond the schema by mentioning 'optional page filtering and text cleaning', which loosely corresponds to the 'pages' and 'clean_text' parameters but does not provide additional semantic context. Baseline 3 is appropriate as 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 states the specific action ('Extract text from a PDF file') and resource ('PDF file'), distinguishing it from sibling tools like 'pdf-metadata' (which likely extracts metadata) and 'search-pdf' (which likely searches within PDFs). The verb 'extract text' precisely defines the tool's function.

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 text extraction from PDFs but does not explicitly state when to use this tool versus alternatives like 'pdf-metadata' or 'search-pdf'. It mentions optional features (page filtering, text cleaning) which provide some context, but lacks explicit guidance on tool selection scenarios.

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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