Explore our collection of Agent Skills to enhance your AI workflow.
Automates the creation of isolated Git worktrees for parallel epic development within the ArcForge ecosystem.
Configures Tailwind CSS v4 with NativeWind v5 and react-native-css for high-performance universal styling in Expo apps.
Streamlines the creation and deployment of server-side API routes within Expo Router applications using EAS Hosting.
Enforces a rigorous evidence-based mindset to ensure AI coding tasks are objectively verified before completion.
Analyzes coding diaries to extract recurring patterns, user preferences, and rule violations across multiple AI development sessions.
Optimizes React and Next.js application performance using 57 high-impact engineering rules curated by Vercel.
Enforces strict workflow discipline and skill routing for AI-driven development tasks.
Analyzes and clusters accumulated AI behavioral patterns into reusable skills, commands, and autonomous agents.
Enforces a rigorous four-phase workflow to identify root causes and ensure reliable fixes before modifying code.
Transforms high-level design documents into structured, authoritative XML specifications with rigorous validation and acceptance criteria.
Enforces a rigorous Red-Green-Refactor Test-Driven Development cycle for AI-assisted coding tasks.
Manages and corrects Claude Code's learning evaluations to improve system accuracy and autonomy scores.
Restores your repository to its last clean state by discarding uncommitted changes and removing untracked artifacts during AI development loops.
Guides the development of standardized AI agent skills following the open agent-skills specification.
Captures and saves manual coding patterns and insights as reusable AI instincts during development sessions.
Manages the final stages of feature development by verifying tests and automating branch integration or cleanup.
Orchestrates large-scale project implementations by automatically expanding epics into executable features and tasks.
Implements a Test-Driven Development (TDD) workflow for creating, testing, and optimizing reusable AI agent skills.
Decomposes complex features into granular, executable tasks with exact implementation code and TDD-driven test commands.
Temporarily disables the Learning Memory System evaluation and playbook injection to streamline standard workflows.
Optimizes your Claude Code configuration by analyzing usage patterns and applying targeted improvements to rules, hooks, and skills.
Orchestrates multi-epic development workflows through automated Git worktree management and DAG-based task coordination.
Guides AI-driven project exploration and architectural design while preventing scope creep and premature implementation.
Standardizes the processing of code review feedback by prioritizing technical verification and codebase reality over performative agreement.
Streamlines the completion of complex coding epics by verifying tests and automating git worktree integration workflows.
Exports Claude Code Learning Memory System (ALM) playbooks into clean, shareable Markdown files for documentation and version control.
Stages changes and generates standardized conventional commit messages to maintain a professional project history.
Executes structured task lists using a TDD-driven workflow with mandatory human checkpoints and atomic commits.
Orchestrates and executes multiple independent coding tasks simultaneously using automated dependency analysis and sub-agent management.
Reactivates the Claude Code Learning Memory (ALM) system to re-enable automated evaluation and playbook injection.
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