Discover Agent Skills for productivity & workflow. Browse 170 skills for Claude, ChatGPT & Codex.
Organizes messy directories and manages file clutter using intelligent structure suggestions and duplicate detection.
Optimizes Claude's operational behavior through specialized modes like brainstorm, implement, and debug to match specific task requirements.
Orchestrates multiple Claude agents to resolve independent debugging and testing tasks concurrently.
Empowers Claude to refine development patterns and retain project-specific knowledge through iterative learning cycles.
Orchestrates multiple local CLI agents using tmux sessions and automated scheduling for parallel task execution.
Orchestrates and manages multiple local CLI agents using tmux sessions for parallel task execution and background monitoring.
Optimizes AI responses by switching between specialized operational modes like brainstorming, debugging, and implementation based on task requirements.
Manages multiple local CLI agents via tmux sessions for parallel task execution, monitoring, and scheduling.
Adapts AI operational behavior and output styles to match specific development phases like planning, coding, or debugging.
Orchestrates the creation of full-stack applications from natural language prompts by determining project types, selecting tech stacks, and managing specialized agents.
Generates structured, atomic action plans for coding tasks to streamline development workflows and improve execution clarity.
Generates granular, test-driven implementation plans that break down complex features into bite-sized, executable tasks.
Provides a persistent, searchable memory bank for AI agents to manage architectural decisions, patterns, and long-term project knowledge.
Generates granular, step-by-step implementation plans using TDD and clean code principles to guide complex development tasks.
Configures and optimizes OpenClaw self-hosted AI gateways to connect LLMs with messaging platforms like Telegram, Discord, and WhatsApp.
Generates granular, test-driven implementation plans for complex software tasks before any code is written.
Orchestrates reliable background tasks, AI workflows, and long-running asynchronous processes with TypeScript-first design.
Manages persistent, searchable long-term memory and project knowledge for AI agents using the Model Context Protocol (MCP).
Automates the creation of reliable background tasks, complex AI workflows, and scheduled jobs using the Trigger.dev framework.
Provides a persistent, searchable knowledge management system for AI agents to store and retrieve long-term project context.
Generates targeted research questions to help AI agents understand the current state and architecture of a codebase before implementation.
Orchestrates complex development workflows by decomposing tasks and managing parallel Claude sub-agents with built-in messaging and file locking.
Builds custom productivity tools, CLI utilities, and local-first applications by focusing on solving personal pain points first.
Generates structured, phased development plans based on research findings and design decisions to ensure incremental, testable progress.
Refines code implementations and processes user feedback by analyzing task history, Git diffs, and project documentation.
Refines and updates technical research questions based on user feedback and ticket comments.
Enforces consistent behavior, tool protocols, and model-specific execution patterns across autonomous agent swarms.
Builds high-performance TypeScript command-line tools and developer utilities using the Bun runtime.
Implements automated feedback loops and pattern optimization to improve AI task decomposition quality based on historical outcomes.
Orchestrates multi-agent workflows to parallelize complex coding tasks and manage collaborative agent swarms.
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