Skill UI

This skill guides the planning and review process for complex home or small-lab network changes. It covers creating staged migration plans for VLAN segmentation, implementing local DNS resolvers (like Pi-hole), setting up secure VPN access, and ensuring network safety through detailed inventory checks and rollback procedures. It emphasizes security best practices and trust zoning.

Pi-hole is a powerful, network-wide DNS ad blocker that runs on Linux hosts (like Raspberry Pi). It intercepts all DNS queries on your local network, blocking advertisements, trackers, and known malware domains before they reach your devices. This guide covers setup via Docker or bare metal, configuring network DNS, managing blocklists, and enabling secure DNS-over-HTTPS (DoH) for enhanced privacy.

This framework manages the ingestion, organization, synchronization, and search of knowledge across multiple storage layers, including local files, persistent memory, vector stores, and Git repositories. It provides a structured approach for ensuring knowledge durability, deduplication, and maintaining a 'single source of truth' across complex development and operational contexts.

Provides comprehensive configuration management for local LLM inference using RuVLLM. Users can select models, perform task-specific fine-tuning with MicroLoRA adapters, or implement continuous, real-time adaptation using SONA. This tool guides the entire advanced LLM workflow, covering status checks, configuration generation, and advanced adaptation loops.

This skill provides access to the Anthropic Claude Managed Agent runtime, which is a cloud-native, persistent environment for running complex, long-running, or asynchronous AI tasks. Unlike local WASM agents, the managed runtime provides a full container, persistent filesystem, and robust state management across multiple turns. It supports the entire agent lifecycle: creation, prompting, status inspection, event logging, and mandatory termination.

This memory bridge ingests Claude Code's local auto-memory markdown files and structures them into AgentDB. It generates high-fidelity ONNX embeddings, handles deduplication using cosine similarity, and indexes the memories in a scalable namespace. This enables seamless, unified semantic search across all historical sessions and projects, significantly enhancing RAG capabilities.

This skill provides operations for managing and processing messages, including translation and routing. It is designed for use in workflows that require message handling and localization.

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.

Pilot Protocol is an open-source overlay network providing AI agents with first-class network citizenship. It offers permanent virtual addresses, encrypted P2P communication, NAT traversal, and a structured app store. Use this skill when agents require stable networking across cloud changes, need direct, secure messaging without shared accounts, or must integrate structured external data services (e.g., live crypto prices) via local, typed capabilities.

Searches local, marketplace, GitHub, and web for existing skills before creating a new one. Helps avoid duplication, evaluates external skills, and recommends use, fork, or new creation.

This skill automates the Test-Driven Development (TDD) repair loop. Given a failing unit test, it spawns a bounded, headless LLM agent to automatically modify the source code until the test passes. It closes the development loop by treating the test's pass/fail status as the definitive fitness function, ideal for CI failure triage and local TDD workflows.

This skill guides users through evidence-based terminal operations. It is designed for scenarios requiring direct command execution, Git status checks, debugging CI/build failures, and pushing narrow, verified fixes. It emphasizes following a structured, minimal-scope workflow and accurately reporting the repository's current state (e.g., local changes vs. pushed code).