Skill UI

This skill enforces highly efficient coding practices, guiding the AI to write the simplest, most direct code possible. It strictly follows an 'Efficiency Ladder' (YAGNI, reusing existing code, standard library, etc.) to prevent over-engineering, unnecessary abstractions, and boilerplate. Use this when the goal is maximum efficiency with minimal code.

This guide explains how to register custom model slugs (variants) within the Pi Agent's configuration files. It is essential for ensuring that specialized OpenRouter variants or brand-new provider models, which are not part of the static bundled registry, resolve correctly and are available for accurate agent model invocation.

This skill guides the secure management and operation of Virtual Private Servers (VPS) and deployed server-side agents. Use it when SSH access, system restarts, log inspection, or complex workflow automation (like n8n or custom agents) is required on authorized remote hosts. It emphasizes following strict operational protocols and obtaining explicit user permission for sensitive actions.

This skill fetches raw text transcripts from any YouTube video. It prioritizes using the DeepAPI service for reliable, server-side scraping, which bypasses local bot detection issues. If DeepAPI fails or the API key is unavailable, it gracefully falls back to using the local `yt-dlp` tool. The output is always saved as a clean, unformatted .txt file.

This tool verifies the consistency and integrity of the Architecture Decision Records (ADR) graph, which is populated by `adr-index`. It checks for common data corruption issues such as dangling references (broken links), supersedure cycles (circular dependencies), and status mismatches. It is ideal for post-import validation and use as a strict CI/CD gate.

A lightweight CLI tool for systematically comparing various coding AI agents (such as Claude Code, Aider, and Codex) head-to-head. It measures crucial metrics—pass rate, API cost, execution time, and consistency—on reproducible tasks defined via YAML manifests. Use this to objectively select the best agent for your codebase or to validate model updates before production deployment.

Generates a precise, evidence-based installation plan for a project's component catalog (ECC). Instead of loading a full, noisy bundle, this skill analyzes the repository's actual code structure, dependencies, and CI/CD evidence to classify skills, rules, and commands into 'DAILY' (essential) and 'LIBRARY' (referenceable) buckets. It ensures only necessary components are active, optimizing the development environment.

This comprehensive guide outlines a rigorous, human-in-the-loop engineering workflow for leveraging advanced AI agents to complete complex implementation tasks. It mandates defining clear completion criteria, decomposing work into manageable units, and strategically routing models (Haiku, Sonnet, Opus) based on task complexity. The workflow emphasizes continuous evaluation, regression testing, security review of invariants and edge cases, and strict cost discipline to ensure robust and reliable software development using AI assistance.

This model provides an engineering operational framework for teams that leverage AI agents to generate large volumes of code. It shifts the focus from simple syntax to process quality, robust architecture design, rigorous testing, and systematic risk control, ensuring the development of highly stable and reliable systems in AI-assisted environments.

A comprehensive strategy for regression testing in AI-assisted development. It focuses on identifying systematic blind spots, such as schema inconsistencies between sandbox and production paths, and integrating automated bug checks into the development workflow. This guide teaches how to build robust, database-free API tests to ensure code quality when AI models contribute to the codebase.

A comprehensive guide to implementing Clean Architecture patterns for both Android and Kotlin Multiplatform (KMP) projects. It covers robust module structuring, dependency inversion rules, defining UseCases and Repositories, and designing the data layer using technologies like Room, SQLDelight, and Ktor. Learn how to separate concerns, maintain platform independence, and manage complex data flows.

This comprehensive guide covers best practices for building modern Angular applications. It provides detailed instructions on component architecture, state management using Signals, advanced routing, dependency injection, handling forms (prioritizing Signal Forms), and implementing accessibility (ARIA). It also details setup procedures for new projects and modern rendering strategies like SSR.