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Nizoka

pdfnative-mcp

Split PDF into ranges

split_pdf
Idempotent

Split a PDF into multiple documents by specifying page ranges. Each range produces a separate PDF file.

Instructions

Split one PDF into several documents — one per requested page range (pdfnative v1.4 page-tree API). Ranges are 0-based and inclusive; end defaults to start (a single page). Each output is a fresh, self-contained PDF (signatures/AcroForm dropped; URI links kept unless dropAnnotations=true). Encrypted sources are rejected (ENCRYPTED_SOURCE). In base64 mode every produced PDF is returned as its own embedded resource block; in file mode each is written to a 1-based indexed sibling of outputPath ('out.pdf' → 'out-1.pdf', 'out-2.pdf', …). Use extract_pages instead when you want a single PDF from an arbitrary page subset.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rangesYesPage ranges to extract, one output PDF per range. 0-based, inclusive; `end` defaults to `start` (a single page).
encryptNoRe-encrypt the produced PDF with the PDF Standard Security Handler (AES-128 V4/R4 default, or AES-256 V5/R6). RC4 is never emitted. Requires a Web Crypto CSPRNG. Applied to every produced range.
passwordNoPassword to open an encrypted source PDF (user or owner — both are tried). Omit for unencrypted documents. Never logged or echoed back.
pdfBase64YesBase64-encoded source PDF. Pass `password` for an encrypted source.
outputModeNobase64
outputPathNoBase output path (file mode). Each PDF is written to an indexed sibling: 'out.pdf' → 'out-1.pdf', 'out-2.pdf', …
dropAnnotationsNoWhen true, drop ALL annotations. Default keeps self-contained URI link annotations.
maxOutputSizeBytesNoMaximum size, in bytes, of each produced PDF. Defaults to 268435456 (256 MiB).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeYes
countYes
partsYes
totalBytesYes
Behavior5/5

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

The description discloses many behavioral details beyond annotations, such as dropping signatures/AcroForm, keeping URI links by default, rejecting encrypted sources, and the indexed naming in file mode. No contradictions with annotations.

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 with 5 sentences, front-loaded with the primary purpose, and includes only relevant details. Each sentence serves a clear purpose.

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's complexity (8 parameters, nested objects, output schema), the description covers all critical aspects: splitting behavior, range semantics, object handling, encryption, output modes, error conditions, and an alternative tool. It is complete for an AI agent to select and invoke the tool correctly.

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 description coverage is high (88%). The description adds meaningful context for parameters like ranges (0-based inclusive, default end), outputMode (base64 vs file behavior), and encryption options, enhancing understanding beyond the 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 clearly states the tool's function: 'Split one PDF into several documents — one per requested page range.' It uses a specific verb and resource and distinguishes from sibling tool extract_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?

The description explicitly provides usage guidelines, including when to use alternatives: 'Use extract_pages instead when you want a single PDF from an arbitrary page subset.' It also details range conventions, behavior for annotations and encryption, and output modes.

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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