MiniMax PDF

Use this skill when visual quality and design identity matter for a PDF. CREATE (generate from scratch): "make a PDF", "generate a report", "write a proposal...

This skill appears to be what it claims: a design-driven PDF generator + form-filler. Before installing or running it, consider: - Dependency installs: running make.sh fix or the scripts can install Python packages and globally install Playwright/Chromium via npm; run in a virtualenv or container if you want to avoid changing your system Python/npm environment. - Network fetches: cover rendering loads Google Fonts via CSS @import and will fetch any cover_image URLs you provide (absolute URLs). If you render covers with remote image URLs, the renderer will make outbound HTTP(S) requests — don't pass URLs that point at sensitive internal services or that rely on credentials. - Local files: the pipeline reads and writes files (content.json, input PDFs, output PDFs). Inspect content.json and any input PDF paths you pass to ensure you aren't accidentally exposing sensitive files to a process with network access. - Inspect render_cover.js if you need absolute assurance about what the Node renderer fetches or posts. Recommended workflow: run bash scripts/make.sh check first, then run in an isolated environment (virtualenv or container) and test with non-sensitive sample documents. If you want to avoid network fetches, provide only local file:// cover images and ensure your environment has the required fonts installed so Playwright doesn't need to fetch them.

Type: OpenClaw Skill Name: yh-minimax-pdf Version: 1.0.0 The yh-minimax-pdf skill is a sophisticated PDF generation and manipulation tool that uses a design-token-based pipeline to ensure visual consistency. It includes a comprehensive set of scripts for generating covers via Playwright (render_cover.js), rendering body content with ReportLab (render_body.py), and filling PDF forms (fill_write.py). The tool supports advanced features like LaTeX math, charts, and flowcharts rendered via matplotlib. While the scripts include logic to automatically install missing dependencies (e.g., in make.sh and ensure_deps functions), this behavior is aligned with the tool's stated purpose of providing a ready-to-use document generation environment for an AI agent. No evidence of data exfiltration, malicious execution, or harmful prompt injection was found.