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Found 10,095 Skills
Monitor LLMs and agentic apps: performance, token/cost, response quality, and workflow orchestration. Use when the user asks about LLM monitoring, GenAI observability, or AI cost/quality.
Install and use the Edict (三省六部) multi-agent orchestration system with 12 specialized AI agents, real-time kanban dashboard, and audit trails
Install and use Marketing Skills for AI agents — CRO, copywriting, SEO, analytics, and growth engineering skills for Claude Code and other coding agents.
Update agent skills installed with the `skills` CLI. Use when asked to refresh installed skills, keep a project's skills current, or troubleshoot cases where `npx skills update` reports that everything is up to date. For project-scoped installs, a no-change update must immediately run the bundled reinstall script so tracked skills from `skills-lock.json` are reinstalled without extra investigation.
Professional prompt engineering, context engineering, and AI agent orchestration for coding agents (Claude Code, Codex, Cursor, Gemini CLI). Use when designing CLAUDE.md/AGENTS.md files, writing skills, planning multi-agent pipelines, optimizing token usage, managing session handoffs, or structuring any prompt for maximum agent performance. Do NOT use for general coding tasks or code review.
[Trigger] When PPT workflow needs SVG slide quality review via Gemini. [Output] Structured review assessment with scores, pass/fail, and fix suggestions. [Skip] For content authoring or SVG generation tasks (those are handled by Claude). [Ask] No user input needed; invoked by review-core agent. [Resource Usage] Use references/, scripts/ (`scripts/invoke-gemini-ppt.ts`).
CrewAI agent design and configuration. Use when creating, configuring, or debugging crewAI agents — choosing role/goal/backstory, selecting LLMs, assigning tools, tuning max_iter/max_rpm/max_execution_time, enabling planning/code execution/delegation, setting up knowledge sources, using guardrails, or configuring agents in YAML vs code.
AI agents on the Teneo Protocol network for real-time data queries.
Build and deploy AI agents with CloudBase Agent SDK (TypeScript & Python). Implements the AG-UI protocol for streaming agent-UI communication. Use when deploying agent servers, using LangGraph/LangChain/CrewAI adapters, building custom adapters, understanding AG-UI protocol events, or building web/mini-program UI clients. Supports both TypeScript (@cloudbase/agent-server) and Python (cloudbase-agent-server via FastAPI).
Trust Wallet CLI (`twak`) — install, create wallets, check balances, send tokens, swap, view history, set price alerts, manage ERC-20 approvals, check token risk, browse trending/DApps, and run x402 micropayments. Use whenever the user wants to use the twak CLI, manage a crypto wallet from the terminal, send or swap tokens via command line, check portfolio, create price alerts, approve ERC-20 spenders, or interact with Trust Wallet from a shell. Also covers MCP server setup for AI agents.
Use when the user explicitly asks to invoke another coding agent CLI as a subagent. Triggers include phrases like 'get a second opinion from Codex', 'have Gemini review this', 'run this through Claude Code', 'ask another agent', or 'use a different model for this'. Supports Claude Code, Codex CLI, and Gemini CLI. Never invoke autonomously.
General-purpose web search using DuckDuckGo and AI-synthesized search engines. Use this skill for web searches, current information, fact-checking, news, and research on any topic where live internet data is needed. Supports all languages. Three modes: fast web results, AI-synthesized answers (IAsk.ai, great for deep questions and academic research), and Monica AI synthesis. Trigger on: "search for", "look up", "find information about", "what is the latest", "search the web", "find out about", "what happened with", "current status of", "recent news", "is X still true", "查一下", "搜索", "查资料", "上网查", "検索して", "調べて", any question requiring real-time or post-training web data. Do NOT trigger for: code exploration, local file analysis, codebase-internal questions, or well-established facts fully covered by training knowledge. Note: if the `agent-reach` skill is also available, prefer `ddg-search` for pure web search tasks; prefer `agent-reach` when the task involves social platforms (Twitter, Reddit, YouTube, WeChat, Bilibili, etc.) or platform-specific APIs.