Skill UI

Create, edit, and analyze .docx files by unpacking OOXML, extracting text with pandoc, building documents with docx-js, and applying tracked changes.

This skill outlines a discipline for capturing and redacting evidence in bug bounty submissions. It guides users on masking sensitive data like session cookies and PII while preserving triage-useful metadata. It covers protocols for screenshots, HAR files, and HTTP requests to prevent data leaks.

Extract keywords with YAKE or RAKE, detect document language, and generate vector embeddings for RAG and search using the xberg CLI or Python API, with local, LLM, or plugin providers.

Extract structured tabular data from PDFs, spreadsheets, and images using layout-aware detection and configurable table models, with markdown or JSON cell output for LLM ingestion and downstream processing.

Extract text from scanned PDFs, photographed pages, and images lacking a text layer. Covers OCR backends like Tesseract, PaddleOCR and VLMs, language packs, force-OCR, batch tuning and failure fixes.

This skill rewrites user prompts to reduce false-positive safety triggers in AI models without bypassing policies or altering intent. It specifically targets cyber, bio/chem, and reasoning classifiers by abstracting sensitive domains and reframing offensive language into defensive equivalents. Useful for developers and researchers needing to test or discuss sensitive topics within safety guardrails.

This skill helps owners find complementary cofounders or project partners when explicitly requested. It assesses the owner's own profile using evidence-based vectors like innovation and scaling, comparing only approved own-owner profiles. It requires explicit consent before publishing or contacting others, strictly avoiding inference of sensitive traits.

This skill enables expert analysis of embedded systems and IoT firmware. It covers hardware reverse engineering, extracting file systems, identifying vulnerabilities like hardcoded credentials, and binary analysis using tools like Binwalk and Ghidra. Used for security assessments and educational purposes with strict authorization.

This skill provides a quick reference for the fp-ts Option type in TypeScript. It helps developers handle nullable values, optional data, and avoid null checks. The guide covers creating Options, transforming values, extracting data safely, and common patterns like safe property access and array handling. It also compares Option with nullable types and outlines limitations for practical usage.

HasData is a comprehensive cloud platform designed for extracting structured public web data. It supports three core execution modes: Web Scraping API for arbitrary URLs (including JS rendering), pre-parsed Scraper APIs for known platforms (like Google or Amazon), and asynchronous Scraper Jobs for bulk or recursive crawling. Ideal for market research, e-commerce intelligence, job data collection, and local business lead generation.

This skill enables users to add and manage structured evaluation results within Hugging Face model cards. It supports extracting evaluation tables from README files, importing benchmark scores via the Artificial Analysis API, and executing custom model evaluations using vLLM or lighteval backends. It ensures compatibility with the model-index metadata format for standardized model releases.

This skill enables users to build reusable command-line scripts and utilities for interacting with the Hugging Face API. It supports chaining API calls, automating repetitive tasks, and processing model or dataset data efficiently. Scripts utilize HF_TOKEN for authentication and can leverage the hf CLI for advanced repository interactions.