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Nizoka

pdfnative-mcp

Add international text

add_international_text
Idempotent

Adds multilingual text in 24 scripts with auto BiDi, shaping, and emoji support. Specify language and paragraphs to generate a PDF with proper typography.

Instructions

Generate a PDF rendering text in any of 24 scripts (Arabic, Hebrew, Thai, CJK, Devanagari, Bengali, Tamil, Telugu, Sinhala, Tibetan, Khmer, Myanmar, Ethiopic, Cyrillic, Greek, Georgian, Armenian, Vietnamese, Turkish, Polish, Latin fallback) with optional COLRv1 colour emoji. BiDi reordering (incl. UAX#9 isolates), Arabic harakat positioning, and complex-script OpenType shaping are handled automatically by the embedded Noto fonts; input is NFC-normalised for maximal glyph coverage and embedded newlines auto-split into paragraphs. Pass lang as a single code or an array (e.g. ["ar","emoji"]) for multi-script runs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleYesPDF title (rendered as page heading and stored as document metadata).
langYesLanguage / script identifier. Either a single code (e.g. 'ar'), a comma-separated list ('ar,emoji'), or an array (['ar','emoji']). Multiple codes enable multi-font run splitting (script + emoji + Latin fallback).
paragraphsYesOrdered list of paragraphs to render in the chosen script.
pdfANoOptional PDF/A conformance level. When set, Tagged PDF + sRGB OutputIntent + XMP metadata are emitted; the 'latin' Noto Sans fallback is auto-registered for non-WinAnsi Latin (ISO 19005-1 §6.3.4). See docs/guides/PDFA.md for the full authoring guide.
outputModeNobase64
outputPathNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeYes
sizeBytesYes
filePathNoAbsolute sandboxed file path (when mode='file').
base64NoBase64-encoded PDF bytes (when mode='base64').
Behavior4/5

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

The description adds significant context beyond annotations: auto-handling, NFC normalization, newline splitting, PDF/A conformance, and COLRv1 emoji support.

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 a dense single paragraph with front-loaded purpose, but slightly verbose; could be structured into bullet points.

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 complexity (6 params, many scripts, PDF/A, output modes), the description covers key behaviors and refers to an external guide, though return values are not explained (output schema likely covers).

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 coverage is 67%, but the description adds meaning for lang (single code or array) and mentions paragraph splitting, compensating for schema gaps.

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 generates a PDF rendering text in 24 scripts with optional emoji, distinguishing it from siblings like generate_basic_pdf.

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 explains automatic handling of BiDi, harakat, and OpenType shaping, but does not explicitly mention when to use this tool versus alternatives.

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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