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Found 1,685 Skills
Access 1200+ AI Agent tools via Model Context Protocol (MCP)
Multi-agent orchestration using dmux (tmux pane manager for AI agents). Patterns for parallel agent workflows across Claude Code, Codex, OpenCode, and other harnesses. Use when running multiple agent sessions in parallel or coordinating multi-agent development workflows.
Form a committee of two high-reasoning agents to step back, do root cause analysis, and produce a plan. Use when stuck, looping, tunnel-visioning, or facing a hard planning problem.
Curate a Chinese reading digest from a fixed bundle of RSS and Atom feeds, with a strong preference for AI agent thinking, frontier AI commentary, deep interviews, and non-boring high-signal essays. Use when Codex needs to pull the latest week's posts by default, or a specific day's posts when explicitly requested, summarize them, score each article on a 10-point scale, and output only the posts scoring above 7 in a concise Chinese daily-brief style.
Agent skill for swarm-pr - invoke with $agent-swarm-pr
Agent skill for code-review-swarm - invoke with $agent-code-review-swarm
macOS native app automation CLI for AI agents. Use when the user needs to interact with macOS desktop applications, including opening apps, clicking buttons, toggling settings, filling forms, reading UI state, automating System Settings, controlling Finder, Safari, or any native app.
Core standards for all GitHub workflow agents. Covers authentication, smart defaults, repository discovery, dual MD+HTML output, screen-reader-compliant HTML accessibility standards, safety rules, progress announcements, parallel execution, and output quality. Apply when building any GitHub workflow agent - issues, PRs, briefings, analytics, community reports, team management.
Phone numbers for AI agents with calls, SMS, and sybil resistance via World ID
Fetches issue context, auto-detects task type, maps to branch prefix, presents brief.
Agente que simula Andrej Karpathy — ex-Director of AI da Tesla, co-fundador da OpenAI, fundador da Eureka Labs, e o maior educador de deep learning do mundo.
AST-based semantic code search skill for AI agents. Teaches agents to use sqry's 34 MCP tools for finding symbols by structure (functions, classes, types), tracing relationships (callers, callees, imports, inheritance), analyzing dependencies, and detecting code quality issues. Unlike embedding-based search, sqry parses code like a compiler. Supports 37 languages. Uses tiered discovery: start with Quick Tool Selection below, load reference files only when you need parameter details or advanced workflows.