Skill UI

This skill is intended for managing the Japanese translation and localization of the core nanoclaw-repl module. The current content serves as a placeholder, indicating that the Japanese translation is actively under development. Users are advised to refer to the original English source file for the full and functional version of the skill.

This skill generates a complete, opinionated, modern full-stack Rails application boilerplate. It sets up a robust tech stack including Rails 8, PostgreSQL, React, Inertia.js, Vite, Tailwind CSS, Sidekiq, and Redis. Designed for developers who need a starting point that adheres to best practices for database structure (UUIDs, JSONB), background job processing, comprehensive testing, and modern frontend development (TSX). Ideal for bootstrapping complex, production-grade web services.

This skill outlines a comprehensive methodology for designing, building, and deploying robust LLM-powered applications. It covers assessing task-model fit, designing modular pipelines (acquire -> prepare -> process -> parse -> render), and managing state using file systems to ensure scalability and reliability in AI systems.

This skill formalizes successful, recurring patterns discovered in auto-memory (MEMORY.md) and graduates them into permanent, enforced rules within the project's core instruction set (CLAUDE.md or scoped rules). It ensures that learned best practices become mandatory project conventions, significantly improving adherence and consistency across all future AI interactions and development cycles. Use this when a temporary note proves to be a vital, repeatable guideline.

This advanced pipeline orchestrates complex feature development based on Request for Comments (RFCs). It breaks down monolithic changes into small, independently verifiable work units, managing dependencies through a Directed Acyclic Graph (DAG). It includes multiple quality gates, dedicated unit testing, and a safe merge queue to ensure robust integration and controlled deployment.

Varlock provides secure, default environment variable management, ensuring that sensitive secrets (like API keys and passwords) are never exposed in logs, terminal output, or the AI context. It validates environments, reads schemas, and executes commands in a secure manner, promoting best practices for handling secrets in modern development workflows.

A set of behavioral guidelines derived from Andrej Karpathy's observations to help users writing, reviewing, or refactoring code with Large Language Models (LLMs). It guides developers to avoid overcomplication, make surgical changes, explicitly surface assumptions, and define verifiable success criteria, promoting clean, simple, and robust code development.

A deep expert system for Anthropic's Claude Code CLI. This skill maximizes productivity by managing advanced features like hooks, persistent context via CLAUDE.md, memory management, sub-agent orchestration, and integrating with local development ecosystems. Ideal for complex coding tasks, debugging, and advanced workflow automation.

This skill monitors the performance of Claude Code and the local operating system. It diagnoses slowdowns, measures CPU/RAM/Disk usage, checks API latency, and generates detailed system health reports. It helps determine if the bottleneck is local hardware or the remote API connection, providing actionable corrective suggestions to improve the development workflow.

This skill guides the development of EarLLM One, a complex Android application. The app captures real-time audio from Bluetooth earbuds, transcribes the voice using STT, sends the text input to a Large Language Model (LLM) via a robust pipeline, and plays the response back using TTS. It requires deep knowledge of Kotlin, Android development, Bluetooth profiles (A2DP/HFP), and advanced audio routing.

This skill guides users on setting up automated code quality gates directly at the Git level. It covers best practices using frameworks like Husky, lint-staged, and pre-commit. Users can enforce linting, formatting, type-checking, and standardized commit message conventions (e.g., Conventional Commits) before code is committed or pushed, significantly improving code hygiene and development workflow consistency.

This skill simulates a highly advanced 'Board of Experts,' consulting multiple specialized personas (e.g., Musk, Buffett, Jobs) simultaneously. It gathers distinct, multi-perspective analyses on any complex topic—from engineering feasibility to market strategy—and synthesizes them into a single, comprehensive, and actionable decision. Ideal for complex strategic planning, product development, and high-stakes investment decisions.