Skill UI

A comprehensive guide detailing offensive methodologies for exploiting Layer 2 (ARP spoofing, VLAN hopping) and Layer 3 (DNS poisoning, DHCP attacks) network infrastructure. Covers credential capture, traffic interception, and privilege escalation using tools like Bettercap, Responder, and ntlmrelayx. Essential for authorized internal penetration testing and red teaming.

A comprehensive tool for managing scope across the entire lifecycle of a legal matter. It helps legal teams establish a baseline scope, proactively track all out-of-scope (OOS) activities, draft necessary client communications, and manage scope creep. By automating capture and surfacing confirmations, it transforms scope management from an adversarial task into a professional, client-focused service, preventing budget surprises and ensuring project alignment.

This skill provides comprehensive, non-destructive testing for deployed Power Pages sites. It navigates the site, performs page crawling, verifies HTTP status codes, captures network API requests (Web API/OData), and detects console errors. It supports testing core site load, authentication flow, and data integrity.

A skill that captures Guixingren's AI technology media creation mindset, featuring Silicon Valley first-line perspectives, China-US dual-line narratives, rapid news aggregation structure, and AI community productization operations. Suitable for AI industry news writing, Silicon Valley reporting, China-US AI comparison analysis, developer tool reviews, and AI community operations, including hackathons, podcasts, and offline events.

This specialized sub-agent is responsible for transforming high-level feature proposals and technical specifications into a formal, comprehensive 'design.md' document. It systematically captures all necessary technical details, including architectural decisions, data flow diagrams, detailed file changes, API contracts, and thorough testing strategies. Use this skill during the planning phase of any complex software change to ensure technical completeness and feasibility.

DataLad manages scientific datasets using Git and git-annex, handling large files efficiently by storing content remotely. It captures computational provenance for reproducible analysis, allowing users to clone, fetch, and publish datasets from repositories like OpenNeuro. Ideal for managing large data files and ensuring analysis reproducibility.

Measure reference videos into reusable style packs: 3D LUT grades, cut rhythm, stills, overlay plates, and specs for generative models. Use to capture looks, build repeatable grades, and match pacing.

A specialized skill for generating hyper-realistic, humanized images using Google AI Studio (Gemini). It simulates the imperfections of real photography—such as natural lighting, slight camera shake, and depth of field—to create content that looks genuinely captured by a smartphone. Ideal for creating high-quality assets for social media (influencer style) or educational materials.

Capture and retrieve durable YYLO Ledger artifact Records with intentional profiles, payload modes, provenance, retention, and secret-safe immutable evidence.

Atlas Ledger is a critical companion designed to provide lasting 'memory' to project contracts. It automatically processes detected deviations or 'drift' (e.g., from audits or reviews) and distills these instances into formal, actionable contract clauses (WHEN/DON'T/INSTEAD). These clauses are written to a persistent project memory file, Atlas.md. This mechanism ensures that lessons learned from failure are systematically captured, allowing future contract cycles to incorporate these rules, thereby strengthening overall project governance and reliability.

This skill interviews users to extract project vision, decisions, and preferences into durable documentation like README and ADRs. It follows a structured loop: checking existing docs, asking varied questions, and updating documents after every answer. The goal is to save user judgment and knowledge into clear markdown files. It ensures consistency and captures the project's core identity through back-and-forth interaction.

This skill guides you through a comprehensive, multi-phase interview to capture every necessary detail of a new project idea. It is designed to run BEFORE any code is written, forcing detailed specification gathering across purpose, features, data models, and technical constraints. The output is a clean, self-contained prompt.md file, ensuring subsequent development is based on solid, unambiguous requirements and preventing costly mistakes.