Skill UI

ADHX provides a dedicated API to fetch X/Twitter posts as clean, structured JSON. It extracts comprehensive data, including author profiles, engagement metrics (likes, retweets), and full article content for long-form posts. This method is vastly superior to traditional scraping techniques, making it ideal for LLM analysis, summarization, and structured data workflows.

AKF is the native metadata format specifically designed for tracking AI-generated or AI-modified content. It allows users to stamp files (including DOCX, PDF, images, and code) with detailed trust scores, source provenance, and compliance metadata. This tool is essential for professional workflows requiring strict auditing, compliance assurance, and verifiable data lineage, especially concerning regulations like the EU AI Act, HIPAA, and SOX.

Guides creators already near product-market fit to grow an organic audience through free, authentic content, consistent scheduling, email ownership, and build-in-public feedback before spending on ads.

This skill outlines the architecture and methodology for deploying canary files (honeytokens) across critical file systems. By placing decoy documents with known content in high-value locations, this system monitors for unauthorized modifications, deletions, or encryption attempts. It detects ransomware by triggering high-fidelity alerts via File Integrity Monitoring (FIM) systems, serving as a crucial deception layer that complements existing EDR/AV solutions.

This skill provides comprehensive analysis and structured data extraction for academic research papers hosted on Hugging Face and arXiv. It can read paper content in markdown format, retrieve key metadata (authors, abstracts, GitHub repos), and identify linked assets such as associated models, datasets, and Spaces. Use this when the user provides a Hugging Face or arXiv URL, or explicitly requests a summary or explanation of an AI research topic.

This guide outlines the implementation of Remote Browser Isolation (RBI) as a core component of a Zero Trust architecture. It details policies for URL risk classification, Data Loss Prevention (DLP) controls, and Content Disarm and Reconstruction (CDR). This is essential for hardening web access, protecting against zero-day exploits, phishing, and preventing data exfiltration from untrusted web content.

This guide provides a comprehensive blueprint for implementing robust Data Loss Prevention (DLP) policies using Microsoft Purview. It covers the configuration of sensitivity labels (encryption, content marking) and the creation of custom DLP rules using regex patterns. The workflow extends to endpoint DLP deployment for controlling file operations on Windows and macOS devices, ensuring sensitive data protection across SharePoint, Exchange, and OneDrive. It leverages PowerShell and the Microsoft Graph API for advanced, programmatic compliance management.

This framework implements robust input and output validation guardrails for LLM-powered applications. It prevents prompt injection, detects and redacts PII, filters toxic content, and validates model outputs against defined schemas. Use it when deploying AI agents that handle sensitive data or require strict adherence to corporate policies, ensuring a secure and trustworthy AI interaction layer.

The Santa Method is a multi-agent adversarial verification framework designed to improve output quality by requiring two independent reviewers (Agent B and Agent C) to pass the content before publication. It eliminates single-agent bias and systematically improves outputs through iterative refinement loops until convergence or manual escalation.

This skill guides the entire video content lifecycle, from initial strategy development to multi-platform distribution. Use it to define YouTube channel positioning, write viral short-form scripts (Reels, TikTok), or systematically repurpose long-form assets like podcasts and blogs into comprehensive video pipelines for maximum reach and authority building.

This skill guides the operation, consolidation, and maintenance of complex working systems within Google Workspace (Docs, Sheets, Slides). It emphasizes treating files as integrated systems—such as trackers or planning hubs—requiring careful inspection, precise edits, and structural cleanup rather than simple content rewriting. Use it for consolidating scattered data, cleaning shared spreadsheets, or ensuring the correct canonical version of a document is utilized.

This skill builds an active voice profile by extracting stylistic patterns, rhythms, and signatures from genuine source materials—such as posts, essays, and site copy. Instead of relying on generic AI tropes, it creates a reusable VOICE PROFILE block, ensuring consistent brand messaging across all content, social media, and outreach campaigns.