Skill UI

This CLI alias executes a comprehensive teardown protocol for PUA agents, designed for development environments. It safely releases all active agent and loop states, ensuring a clean system reset. It automatically manages configuration files like ~/.pua/config.json, preserving unknown fields while providing reliable, evidence-based cleanup.

This CLI alias acts as a dedicated command to disable the PUA always-on mode feature, typically used within AI coding environments like Claude Code. By modifying the user's configuration file (`~/.pua/config.json`), it sets `always_on=false` and `feedback_frequency=0`. This function provides users with granular control, effectively turning off continuous monitoring or background feedback mechanisms managed by the AI assistant.

This tool is designed to validate the syntax, completeness, and correctness of network configuration files. It helps ensure that network devices are configured according to established standards and best practices, preventing deployment errors and ensuring reliable network operation. Ideal for network engineers and DevOps teams.

Provides comprehensive local SEO analysis, covering Google Business Profile (GBP) optimization, NAP consistency checks, review signal analysis, and local schema markup implementation. It detects business types (Brick-and-Mortar, SAB, Hybrid) and industry verticals (Healthcare, Legal, etc.) to provide actionable, up-to-date recommendations for improving local search rankings and visibility on Google Maps and local packs.

Design a persistent multi-agent operating system on Claude Code with kernel routing, specialist agents, slash commands, file-based memory, and scheduled automation for long-lived projects.

A comprehensive skill for handling PowerPoint (.pptx) files. This includes text extraction, deep content analysis via raw XML access (comments, notes, layouts, themes), and programmatic creation of new presentations from scratch. It guides users through design principles, color theory, and structured document generation workflows.

This file is designated as the Japanese localization resource for the Motion UI component. It is currently under active translation and implementation. Users should refer to the original skill file for the English version or the final functional skill.

This file is currently undergoing Japanese localization for MySQL patterns. It serves as a placeholder indicating that the Japanese translation is in progress. Users should refer to the original English skill file for implementation details.

This utility serves as a Command Line Interface (CLI) alias for specialized AI code models, specifically mapping to the Claude Code `/pua:yes` command structure. It facilitates structured code generation or interaction by adopting a specific 'yes skill' protocol. It ensures that while switching to an encouragement-first narration, the system maintains strict verification red lines and handles configuration file updates while preserving unknown fields. Ideal for developers needing consistent, protocol-driven AI code assistance.

This guide provides a comprehensive framework for authoring new, structured AI agent skills. It details a three-phase workflow, including gathering requirements, drafting the main instructions (SKILL.md), and ensuring optimal structure. It emphasizes best practices for descriptions, scripting, and file splitting to improve agent reliability and usability.

Generates a highly polished, self-contained single-page HTML landing page optimized for maximum conversion. It incorporates advanced features like 3D CSS animations, GSAP scroll effects, and mouse parallax depth. To ensure accuracy, the skill uses a structured intake process (product pitch, target audience, brand colors, and tone) to build a conversion-ready page that reflects the actual product, not generic boilerplate. Outputs a single, deployable HTML file.

This skill parses raw, verbose Simplicité log files from TXT format, filtering out noise and extracting only essential fields (e.g., timestamp, level, body). By converting logs into structured JSON, it significantly reduces the token size required for AI context optimization, making troubleshooting efficient and reliable.