Skill UI

This skill acts as a literature-research assistant, orchestrating a Python CLI to interface with APIs like Semantic Scholar and arXiv. It enables users to search for academic papers by topic, retrieve detailed metadata, perform impact analysis using citation tracking, download PDFs, and extract text content. It streamlines the entire academic research workflow from initial discovery to deep reading.

This powerful router analyzes complex document types (scanned, medical, table-heavy, etc.) and determines the optimal conversion pipeline (tools, flags, cleanup) to extract data into various formats like Markdown, JSON, or DOCX. It goes beyond simple text extraction by prioritizing the preservation of document structure, relational data, and high fidelity, ensuring the generated output is accurate for downstream machine processing.

This guide provides comprehensive instructions for PDF processing using Python libraries like pypdf, pdfplumber, and reportlab. It covers essential operations such as merging, splitting, extracting text and tables, creating PDFs, and rotating pages. Additionally, it includes command-line tools like pdftotext and qpdf for automation. Suitable for developers needing to automate document workflows.

A comprehensive suite designed for AI agents to perform safe, deep, and multi-format web searches. It allows agents to retrieve current web information, analyze PDFs, extract YouTube transcripts, and access GitHub code files. Instructions include guidelines for varying search depths and using specialized tools for code context retrieval.

This skill generates Puppeteer scripts for browser automation, web scraping, and PDF creation. It supports headless Chrome, network interception, wait strategies, and cloud integration for testing. Ideal for automating browser interactions and extracting data efficiently.

A structured client-facing format for red-team engagements and penetration testing reports. Includes standardized sections for findings, severity assessment, impact analysis, and proof of concept. Suitable for delivering reports to CISOs and technical stakeholders requiring DOCX/PDF output.

Convert approved documentation, repositories, or PDFs into reusable agent skills using the Skill Seekers workflow. Review generated content for triggers, guidance, and security before installation. Supports licensing checks and excludes private credentials.

This tool extracts key information from PDF files and generates a concise bullet-point summary. It reads the document text, identifies main topics, and returns 3-5 essential points to help users quickly understand the core content without reading the entire document.

Check PDFs and images for signs of tampering or forgery using the Stipple API. Returns a risk band, inspection quality, and per-signal evidence for payslips, invoices, bank statements, IDs, and contracts before you rely on them.

A comprehensive skill for interacting with Weaviate vector databases. It enables advanced operations including semantic search, hybrid keyword querying, schema inspection, data exploration, collection creation, and bulk data import (CSV, JSON, PDF). Use this skill when you need to query data conceptually, retrieve specific raw objects, or manage the lifecycle of Weaviate collections.

Xberg is a document intelligence library supporting 107 formats including PDF, Office, and images. It extracts text, tables, and metadata using OCR and chunking. Available for Python, Node.js, Rust, and CLI. Ideal for developers building document processing applications with multi-language bindings and structured output.

Detects prompt injection hidden in legal documents (pleadings, skeletons, evidence) before AI reads them. Scans PDF, Word, HTML, email attachments for invisible text, Unicode smuggling, and AI-directed instructions. Fails closed with optional hook integration.