Skip to main content
Glama

split_pdf

Split oversized PDFs into smaller chunks that fit within OCR.space API size limits. Handles files exceeding 1 MB (free) or 5 MB (pro) by grouping pages into compliant segments.

Instructions

Split a large PDF into smaller chunks that fit within API size limits. Useful for processing PDFs that exceed the 1 MB (free) or 5 MB (pro) limit. Each chunk contains as many pages as possible while staying under the limit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tierNoTarget tier determines size limit: free=1MB, pro=5MBfree
file_pathYesPath to the PDF file to split
output_dirNoDirectory for output chunks (uses temp dir if not specified)
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses the splitting behavior ('Each chunk contains as many pages as possible while staying under the limit') and limits, but it does not mention whether the original file is preserved or detail output chunk naming/structure. This is a moderate transparency level for a utility tool.

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 composed of two concise sentences that front-load the action and then provide necessary context. No filler or repetition of schema information. Every sentence earns its place.

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?

For a simple preprocessing tool with 3 parameters and no output schema, the description covers purpose, use case, and behavioral nuances. It lacks explicit notes on whether the original is modified and how chunks are consumed downstream, but these are not critical given the tool's simplicity and the schema coverage.

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 has 100% parameter coverage, describing file_path, tier (with enum values and size limits), and output_dir. The description adds no parameter-specific details beyond the schema, but the schema is rich enough; the 'as many pages as possible' behavior is contextual, not parameter semantics. Baseline 3 is appropriate.

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 uses a specific verb 'Split' and clear resource 'large PDF into smaller chunks', and explicitly ties it to API size limits. It distinguishes from sibling OCR tools by focusing on preprocessing. The purpose is unambiguous.

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 states when to use it: 'Useful for processing PDFs that exceed the 1 MB (free) or 5 MB (pro) limit.' This provides clear context, though it does not explicitly mention when not to use it or name alternatives. However, siblings are unrelated OCR tools, so this is sufficient.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/agentic-ai-forge/ocr-space-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server