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earlyprototype

notebooklm-py-diet-mcp

pdf_to_png

Convert a PDF file into separate PNG images, one per page, for viewing slide decks and documents with language models.

Instructions

Convert a PDF file to individual PNG images (one per page).

Useful for making slide deck pages visible to LLMs for review or editing.

Args: pdf_path: Path to the source PDF file output_directory: Directory to write PNGs into. Defaults to a folder beside the PDF named _pages/ dpi: Render resolution (default 200 -- good balance of quality and size)

Returns: Dictionary with output directory, list of page image paths, and page count

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dpiNo
pdf_pathYes
output_directoryNo
Behavior4/5

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

With no annotations, the description fully bears the burden for behavioral disclosure. It explains the conversion process, default output directory naming, and return value structure. It could mention side effects like file overwriting or required permissions, but the current level is adequate.

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 concise at about 6 sentences plus structured Args and Returns. It is front-loaded with the purpose and every sentence serves a clear function without redundancy.

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?

Given the tool has 3 parameters, no output schema, and no annotations, the description covers purpose, use case, parameter details, and return format completely. An agent can understand when and how to invoke it correctly.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must compensate. It explains that pdf_path is the source file, output_directory defaults to a folder beside the PDF named <filename>_pages/, and dpi defaults to 200 with a quality-size balance, adding significant meaning beyond the schema's type and defaults.

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?

Description clearly states 'Convert a PDF file to individual PNG images (one per page).' This is a specific verb+resource combination that differentiates it from the sibling tool 'png_to_pdf' which performs the reverse operation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description says 'Useful for making slide deck pages visible to LLMs for review or editing.' This provides clear context for when to use the tool. No explicit when-not or alternative tools are mentioned, but the sibling list implies the reverse operation.

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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