一个技能，一个新的可能。找到适合你的 AI 工作流。
agent-hiring-panel
【效率与协作】Hire an AI agent the way you'd hire an employee — a role spec with success criteria, a structured work-sample interview run on your real tasks, reference checks (what do actual users report), probation KPIs, and termination criteria written before day one. Use when choosing between AI agents/tools/copilots for a job, formalizing an AI pilot, or 'whic…
agent-ui
【效率与协作】Batteries-included agent component for React/Next.js from ui.inference.sh. One component with runtime, tools, streaming, approvals, and widgets built in. Capabilities: drop-in agent, human-in-the-loop, client-side tools, form filling. Use for: building AI chat interfaces, agentic UIs, SaaS copilots, assistants. Triggers: agent component, agent ui, ch…
agent-ui
【效率与协作】Batteries-included agent component for React/Next.js from ui.inference.sh. One component with runtime, tools, streaming, approvals, and widgets built in. Capabilities: drop-in agent, human-in-the-loop, client-side tools, form filling. Use for: building AI chat interfaces, agentic UIs, SaaS copilots, assistants. Triggers: agent component, agent ui, ch…
agent-ui
【效率与协作】"Batteries-included agent component for React/Next.js from ui.inference.sh. One component with runtime, tools, streaming, approvals, and widgets built in. Capabilities: drop-in agent, human-in-the-loop, client-side tools, form filling. Use for: building AI chat interfaces, agentic UIs, SaaS copilots, assistants. Triggers: agent component, agent ui, c…
ai-chat
【设计与创意】AI chat interface patterns for Angular 21.x and Flutter 3.41.x. Use when building streaming chat UI, conversational AI assistants, copilots, token context indicators, feedback loops, multi-modal inputs, tool visualization, or AI-specific error handling. Covers streaming markdown, auto-scroll heuristics, memoized rendering, token limit UI, regeneratio…
ai-engineer
【设计与创意】Guides production AI engineering—LLM apps, RAG, agents, eval harnesses, observability, cost/latency, and safe deployment. Use when building chatbots, copilots, retrieval, agent workflows, model routing, or LLM API integration—not research synthesis (ai-researcher), AI policy (ai-risk-governance), red-team (ai-redteam), prompt-only work (prompt-engine…
ai-memory-developer
【文档与办公】Guides design and implementation of AI agent and application memory—short-term conversation state, long-term user/tenant memory, episodic vs semantic stores, consolidation, retrieval, forgetting, privacy retention, and eval of memory quality. Use when building persistent memory for copilots, designing memory APIs, choosing vector or graph stores, imp…
ai-redteam
【设计与创意】Guides adversarial testing of AI systems—prompt injection, jailbreaks, tool abuse, data exfiltration, bias and harmful output probes, multi-turn attacks, and automated red-team harnesses for LLM applications. Use when red-teaming chatbots, agents, RAG systems, or copilots before launch, designing safety eval suites, reproducing reported vulnerabiliti…
applied-ai-architect-commercial-enterprise
【设计与创意】Guides applied AI solution architecture for commercial (B2B SaaS, multi-tenant product) and enterprise (internal copilots, regulated corp data) contexts—reference patterns for RAG, agents, and copilots, platform and model selection, data boundaries, identity, observability, cost at scale, and POC-to-production hardening with security and governance g…
building-ai-chat
【设计与创意】Builds AI chat interfaces and conversational UI with streaming responses, context management, and multi-modal support. Use when creating ChatGPT-style interfaces, AI assistants, code copilots, or conversational agents. Handles streaming text, token limits, regeneration, feedback loops, tool usage visualization, and AI-specific error patterns. Provide…
building-ai-chat
【设计与创意】Builds AI chat interfaces and conversational UI with streaming responses, context management, and multi-modal support. Use when creating ChatGPT-style interfaces, AI assistants, code copilots, or conversational agents. Handles streaming text, token limits, regeneration, feedback loops, tool usage visualization, and AI-specific error patterns. Provide…
building-ai-chat
【设计与创意】Builds AI chat interfaces and conversational UI with streaming responses, context management, and multi-modal support. Use when creating ChatGPT-style interfaces, AI assistants, code copilots, or conversational agents. Handles streaming text, token limits, regeneration, feedback loops, tool usage visualization, and AI-specific error patterns. Provide…
building-ai-chat
【设计与创意】Builds AI chat interfaces and conversational UI with streaming responses, context management, and multi-modal support. Use when creating ChatGPT-style interfaces, AI assistants, code copilots, or conversational agents. Handles streaming text, token limits, regeneration, feedback loops, tool usage visualization, and AI-specific error patterns. Provide…
copilotkit
【设计与创意】Build AI copilots, chatbots, and agentic UIs in React and Next.js using CopilotKit. Use this skill when the user wants to add an AI assistant, copilot, chat interface, AI-powered textarea, or agentic UI to their app. Covers setup, hooks (useCopilotAction, useCopilotReadable, useCoAgent, useAgent), chat components (CopilotPopup, CopilotSidebar, Copilo…
copilots
【效率与协作】Grounds an assistant in your app with assistant-ui copilots. Use when steering behavior with useAssistantInstructions, feeding send-time app state through useAssistantContext({ getContext }), exposing components with makeAssistantVisible(Component, { clickable, editable }), giving the model two-way component state through interactables (unstable_useI…
engineering-manager-vertical-ai-products
【设计与创意】Guides engineering managers leading vertical AI product teams—industry or domain-specific copilots and AI features (not horizontal platform)—org design, hiring, roadmap with PM and GTM, vertical launch governance (eval, safety, cost), squad capacity, and escalation across shared AI platform and domain experts. Use when managing engineers shipping ver…
prompt-engineer-agent-prompts-evals
【设计与创意】Guides prompt engineering for tool-using agents—system and developer prompts, tool schemas, handoffs and subagents, golden datasets, offline eval harnesses, regression CI, LLM-as-judge rubrics, and release gates for prompt changes. Use when authoring agent prompts, building eval suites for agents or copilots, debugging tool-selection failures, design…