Back to Skills

pdf

majiayu000
Updated 10 days ago
62 views
58
9
58
View on GitHub
Metapdfwordai

About

This PDF skill provides comprehensive PDF manipulation capabilities including text extraction, form handling, and document merging/splitting. Use it when Claude needs to programmatically process, generate, or analyze PDF documents at scale. It supports both Python libraries for core operations and includes advanced features for form filling and table extraction.

Quick Install

Claude Code

Recommended
Primary
npx skills add majiayu000/claude-skill-registry -a claude-code
Plugin CommandAlternative
/plugin add https://github.com/majiayu000/claude-skill-registry
Git CloneAlternative
git clone https://github.com/majiayu000/claude-skill-registry.git ~/.claude/skills/pdf

Copy and paste this command in Claude Code to install this skill

GitHub Repository

majiayu000/claude-skill-registry
Path: skills/d54585ee-5994-456e-bdf3-d37117eeaa1d
0

Related Skills

content-collections

Meta

This skill provides a production-tested setup for Content Collections, a TypeScript-first tool that transforms Markdown/MDX files into type-safe data collections with Zod validation. Use it when building blogs, documentation sites, or content-heavy Vite + React applications to ensure type safety and automatic content validation. It covers everything from Vite plugin configuration and MDX compilation to deployment optimization and schema validation.

View skill

himalaya-email-manager

Communication

This Claude Skill enables email management through the Himalaya CLI tool using IMAP. It allows developers to search, summarize, and delete emails from an IMAP account with natural language queries. Use it for automated email workflows like getting daily summaries or performing batch operations directly from Claude.

View skill

sglang

Meta

SGLang is a high-performance LLM serving framework that specializes in fast, structured generation for JSON, regex, and agentic workflows using its RadixAttention prefix caching. It delivers significantly faster inference, especially for tasks with repeated prefixes, making it ideal for complex, structured outputs and multi-turn conversations. Choose SGLang over alternatives like vLLM when you need constrained decoding or are building applications with extensive prefix sharing.

View skill

evaluating-llms-harness

Testing

This Claude Skill runs the lm-evaluation-harness to benchmark LLMs across 60+ standardized academic tasks like MMLU and GSM8K. It's designed for developers to compare model quality, track training progress, or report academic results. The tool supports various backends including HuggingFace and vLLM models.

View skill