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Found 25 Skills
Control Chrome browser with AI using MCP protocol. Use when users want to automate browser tasks, take screenshots, fill forms, click elements, navigate pages, search browsing history, manage bookmarks, or perform any browser-based automation. Works with your existing Chrome browser and login sessions.
Official Puppeteer Model Context Protocol Server for browser automation.
Manage AI coding agents on a visual Kanban board. Run parallel agents through a To Do→In Progress→Review→Done flow with automatic git worktree isolation and GitHub PR creation.
AI agents: autonomous agents, multi-agent systems, LangChain, LlamaIndex, MCP.
Use the local SupeRISE wallet through its MCP endpoint. Use this whenever the user expects the agent to operate, inspect, manage, or use the Superise wallet, including MCP connectivity, available wallet capabilities, or wallet tasks such as current wallet, wallet fingerprint, wallet status, wallet address or public key (`钱包地址`, `公钥`), balances (`余额`) for `CKB`, `ETH`, `USDT`, or `USDC`, transfer progress, transaction status, address-book lookups, signing, or transfers. When wallet intent is present, first discover the live MCP capabilities with `initialize -> notifications/initialized -> tools/list`, then choose the matching tool instead of guessing.
Build tools that agents can use effectively, including architectural reduction patterns
MCP server implementation with Express.js and TypeScript.
Build AI agents on Cloudflare Workers with MCP integration, tool use, and LLM providers.
Use when working with AI agent protocols, standards, and interoperability specifications. Covers MCP, A2A, ACP, Agent Skills, AGENTS.md, ADL, x402, AP2, MCP Apps, and cagent. USE FOR: agent protocol selection, comparing MCP vs A2A vs ACP, understanding agent standards ecosystem, choosing payment protocols DO NOT USE FOR: specific protocol implementation details (use the sub-skills: mcp, a2a, acp, x402, etc.)
AI-powered research skill with five workflows - chat (single-model conversation), consensus (multi-model synthesis), thinkdeep (systematic investigation), ideate (creative brainstorming), and deep (multi-phase web research). Supports persistent threads and research sessions.
Playwright MCP server: browser automation via MCP protocol, page interaction, form filling
Build AI agents and agentic workflows. Use when designing/building/debugging agentic systems: choosing workflows vs agents, implementing prompt patterns (chaining/routing/parallelization/orchestrator-workers/evaluator-optimizer), building autonomous agents with tools, designing ACI/tool specs, or troubleshooting/optimizing implementations. **PROACTIVE ACTIVATION**: Auto-invoke when building agentic applications, designing workflows vs agents, or implementing agent patterns. **DETECTION**: Check for agent code (MCP servers, tool defs, .mcp.json configs), or user mentions of "agent", "workflow", "agentic", "autonomous". **USE CASES**: Designing agentic systems, choosing workflows vs agents, implementing prompt patterns, building agents with tools, designing ACI/tool specs, troubleshooting/optimizing agents.