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Found 5,658 Skills
Deploy, configure, and integrate Sandbox Agent - a universal API for orchestrating AI coding agents (Claude Code, Codex, OpenCode, Amp) in sandboxed environments. Use when setting up sandbox-agent server locally or in cloud sandboxes (E2B, Daytona, Docker), creating and managing agent sessions via SDK or API, streaming agent events and handling human-in-the-loop interactions, building chat UIs for coding agents, or understanding the universal schema for agent responses.
Provides MoAI-ADK foundational principles including TRUST 5 quality framework, SPEC-First DDD methodology, delegation patterns, progressive disclosure, and agent catalog reference. Use when referencing TRUST 5 gates, SPEC workflow, EARS format, DDD methodology, agent delegation patterns, or MoAI orchestration rules. Do NOT use for context and token management (use moai-foundation-context instead) or strategic analysis (use moai-foundation-philosopher instead).
Tavily AI search API - Optimized search for AI agents. Use when searching the web for current information, news, facts, or any task requiring real-time data.
Build AI applications using the Azure AI Projects Python SDK (azure-ai-projects). Use when working with Foundry project clients, creating versioned agents with PromptAgentDefinition, running evaluations, managing connections/deployments/datasets/indexes, or using OpenAI-compatible clients. This is the high-level Foundry SDK - for low-level agent operations, use azure-ai-agents-python skill.
Give your AI agent eyes to see the entire internet. Read and search across Twitter/X, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu, RSS, and any web page — all from a single CLI. Use when: (1) reading content from URLs (tweets, Reddit posts, articles, videos), (2) searching across platforms (web, Twitter, Reddit, GitHub, YouTube, Bilibili, XiaoHongShu), (3) checking channel health or updating Agent Reach. Triggers: "search Twitter/Reddit/YouTube", "read this URL", "find posts about", "搜索", "读取", "查一下", "看看这个链接".
Jeffrey Emanuel's multi-agent implementation workflow using NTM, Agent Mail, Beads, and BV. The execution phase that follows planning and bead creation. Includes exact prompts used.
Initialize a comprehensive .agents/ folder structure for AI-first development. Use this skill when starting a new project that needs AI agent documentation, session tracking, task management, and coding standards. Generates full structure based on proven patterns from production projects.
Self-improving agent that can upgrade skills, learn new capabilities, and adapt to new tasks. Use when you need to evolve capabilities or handle unknown tasks.
Build stateful AI agents using the Cloudflare Agents SDK. Load when creating agents with persistent state, scheduling, RPC, MCP servers, email handling, or streaming chat. Covers Agent class, AIChatAgent, state management, and Code Mode for reduced token usage.
Azure AI Evaluation SDK for Python. Use for evaluating generative AI applications with quality, safety, agent, and custom evaluators. Triggers: "azure-ai-evaluation", "evaluators", "GroundednessEvaluator", "evaluate", "AI quality metrics", "RedTeam", "agent evaluation".
Use this skill when orchestrating multi-agent work at scale - research swarms, parallel feature builds, wave-based dispatch, build-review-fix pipelines, or any task requiring 3+ agents. Activates on mentions of swarm, parallel agents, multi-agent, orchestrate, fan-out, wave dispatch, research army, unleash, dispatch agents, or parallel work.
Manage shell hooks — user scripts that run at agent lifecycle points to block, rewrite, or warn on actions, via the /hooks command.