Explore our collection of Agent Skills to enhance your AI workflow.
Automates the end-to-end GitHub issue lifecycle by spawning sub-agents to implement code fixes, open pull requests, and resolve review comments.
Manages Discord operations including messaging, reactions, and channel management directly through Claude.
Automates code formatting and linting checks to ensure code quality and CI compliance before committing.
Manages GitHub pull requests, issues, and CI/CD workflows directly through the command line using the GitHub CLI.
Manages and tracks Foodora delivery orders directly from the terminal with real-time status updates.
Delegates complex development tasks and feature builds to specialized background AI agents like Codex and Claude Code.
Integrates Google Workspace services like Gmail, Calendar, Drive, and Sheets directly into your terminal workflow.
Automates the creation of GitHub pull requests for the n8n repository while ensuring compliance with internal CI title validation rules.
Simplifies the creation of customizable widget plugins for the prompts.chat feed system to display sponsored content and interactive components.
Accesses, retrieves, and optimizes a vast library of community-sourced AI prompts directly within your terminal workflow.
Guides the localization and translation of 'The Interactive Book of Prompting' chapters and UI strings into new languages.
Discovers and installs modular AI capabilities from the prompts.chat community to extend Claude's task-specific expertise.
Accesses and optimizes a comprehensive library of community-curated AI prompts to enhance model performance and task accuracy.
Manages long-lived agent workloads with advanced observability, security boundaries, and lifecycle controls.
Manages and extends NanoClaw v2, a zero-dependency, session-aware REPL environment for persistent AI interactions.
Optimizes AI agent workflows through evaluation-first cycles, task decomposition, and cost-aware model routing.
Enforces real-time code quality and automated fixes through a multi-stage linting and formatting system for Claude Code.
Automates complex software development workflows using multi-stage, self-correcting agent loops with Claude Code.
Manages and extends NanoClaw v2, a lightweight, session-aware REPL environment for Claude-based agents.
Optimizes AI agent performance through eval-driven execution, task decomposition, and cost-aware model routing.
Orchestrates complex software development tasks using an RFC-driven multi-agent DAG execution model with integrated quality gates.
Optimizes AI agent tool definitions and observation formatting to increase task completion rates and reliability.
Manages long-running AI agent workloads with enterprise-grade observability, security boundaries, and lifecycle management.
Orchestrates autonomous AI agent cycles with built-in quality gates, evaluation frameworks, and recovery mechanisms for complex development tasks.
Establishes an operational framework for software engineering teams where AI agents drive the majority of code implementation.
Establishes a modern engineering operating model optimized for teams where AI agents generate the majority of code implementation.
Implements robust, autonomous execution loops with built-in quality gates and recovery mechanisms for reliable agentic workflows.
Orchestrates complex development tasks through RFC-driven decomposition, Directed Acyclic Graph (DAG) execution, and automated quality gates.
Optimizes AI agent action spaces, tool definitions, and observation formats to maximize task completion rates and reliability.
Synchronizes Next.js documentation with code changes through automated impact analysis and standardized MDX templates.
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