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Found 4,444 Skills
Give AI agents their own email inboxes using the AgentMail API. Use when building email agents, sending/receiving emails programmatically, managing inboxes, handling attachments, organizing with labels, creating drafts for human approval, or setting up real-time notifications via webhooks/websockets. Supports multi-tenant isolation with pods.
Manage OpenClaw bot configuration - channels, agents, security, and autopilot settings
Design and build AI agents for any domain. Use when users: (1) ask to "create an agent", "build an assistant", or "design an AI system" (2) want to understand agent architecture, agentic patterns, or autonomous AI (3) need help with capabilities, subagents, planning, or skill mechanisms (4) ask about Claude Code, Cursor, or similar agent internals (5) want to build agents for business, research, creative, or operational tasks Keywords: agent, assistant, autonomous, workflow, tool use, multi-step, orchestration
Optimize multi-agent systems with coordinated profiling, workload distribution, and cost-aware orchestration. Use when improving agent performance, throughput, or reliability.
Generate hierarchical AGENTS.md structures for codebases. Use when user asks to create AGENTS.md files, analyze codebase for AI agent documentation, set up AI-friendly project documentation, or generate context files for AI coding assistants. Triggers on "create AGENTS.md", "generate agents", "analyze codebase for AI", "AI documentation setup", "hierarchical agents".
Deep codebase initialization with hierarchical AGENTS.md documentation
This skill should be used for structured feature development with codebase understanding. Triggers on /do command. Provides a 5-phase workflow (Understand, Clarify, Design, Implement, Complete) using codeagent-wrapper to orchestrate code-explorer, code-architect, code-reviewer, and develop agents in parallel.
Production-grade AI agent patterns with MCP integration, agentic RAG, handoff orchestration, multi-layer guardrails, observability, token economics, ROI frameworks, and build-vs-not decision guidance (modern best practices)
Create and refine OpenCode agents via guided Q&A. Use proactively for agent creation, performance improvement, or configuration design. Examples: - user: "Create an agent for code reviews" → ask about scope, permissions, tools, model preferences, generate AGENTS.md frontmatter - user: "My agent ignores context" → analyze description clarity, allowed-tools, permissions, suggest improvements - user: "Add a database expert agent" → gather requirements, set convex-database-expert in subagent_type, configure permissions - user: "Make my agent faster" → suggest smaller models, reduce allowed-tools, tighten permissions
Complete guide to using @openserv-labs/client for managing agents, workflows, triggers, and tasks on the OpenServ Platform. Covers provisioning, authentication, x402 payments, ERC-8004 on-chain identity, and the full Platform API. IMPORTANT - Always read the companion skill openserv-agent-sdk alongside this skill, as both packages are required to build any agent. Read reference.md for the full API reference.
Dynamic tool selection, composition, and error handling patterns for AI agents. Use when you need to efficiently leverage available tools and handle failures gracefully.
Project setup wizard for AI agents. Use when user requests setup or when .agents/CONTEXT.md is missing or incomplete and setup recovery is needed. Generates .agents/CONTEXT.md with stack, structure, coding rules, and skill mapping.