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Build with the AgentMail TypeScript or Python SDK for inbox, message, thread, draft, attachment, domain, allow/block list, pod, webhook, and WebSocket workflows, including programmatic agent sign-up, domain/DNS administration, and deliverability triage (bounces, spam, blocked mail). Use when implementing or reviewing AgentMail API code; do not use for direct mailbox operations, CLI usage, MCP setup, or framework-toolkit integration.

Read, search, summarize, and triage AgentMail inboxes through the connected MCP server. Use for ANY request to look at, search, or process mail — even a simple 'search my inbox for X' or 'any new mail?'; the read workflow applies regardless of task size. Also use to summarize conversations, inspect attachments, manage read/unread labels, or find messages needing a reply; do not use for sending or drafting (agentmail-send-email), inbox administration (agentmail-manage-inboxes), or MCP connection setup (agentmail-mcp).

Operate AgentMail from a shell with the official CLI. Use when the user wants commands for listing or creating inboxes, reading or searching mail, sending or replying, managing drafts, or scripting JSON/YAML output; do not use for SDK code, MCP setup, or framework adapters.

Create, list, inspect, update, or delete AgentMail inboxes through the connected MCP server. Use for ANY inbox lifecycle request — even a quick list-inboxes or a simple delete; deletion safeguards apply regardless of task size. Also use when the user asks for a new agent email address, wants inbox details changed, or removes an inbox; do not use for sending mail (agentmail-send-email), reading or triage (agentmail-check-email), or MCP connection setup (agentmail-mcp).

Configure or troubleshoot the hosted AgentMail MCP server for Codex, Claude Code, Cursor, Claude.ai, ChatGPT, or another Streamable HTTP MCP client. Use for installation, OAuth, API-key headers, connection failures, or MCP tool discovery. Do not use when the connection already works and the user just wants to send, check, or manage mail — use the sibling action skills for that.

Draft, send, reply to, or forward email through the connected AgentMail MCP server. Use for ANY request to send, reply to, or forward mail — even a quick one-line send or a simple forward that looks like a single tool call; the sending rules apply regardless of task size. Also use to compose messages, create or schedule drafts for review, or send to named recipients; do not use for reading or triaging mail (agentmail-check-email), inbox administration (agentmail-manage-inboxes), or MCP connection setup (agentmail-mcp).

Add AgentMail tools to agent frameworks with the TypeScript or Python AgentMail Toolkit. Use for Vercel AI SDK, LangChain, OpenAI Agents SDK, LiveKit Agents, or MCP adapters; do not use for direct mailbox operations, raw SDK implementation, CLI usage, or MCP client setup.

Overview and router for assistant-ui, the React library for building AI chat interfaces from composable primitives and a styled elements catalog. Use for high-level, cross-cutting, or architecture questions: choosing packages, picking a runtime, or understanding the layers (elements, primitives, the aui client with AuiConfig and AuiProvider, the runtime, adapters) and the message model. Covers `@assistant-ui/react` 0.15.x, `@assistant-ui/ai-sdk` for AI SDK v7 (`useChatRuntime`), `@assistant-ui/core`, `@assistant-ui/store`, `assistant-stream`, `assistant-cloud`, the LangGraph, LangChain, Google ADK, A2A, AG-UI, Eve, OpenCode, and Pi adapters, the `@assistant-ui/react-native` and `@assistant-ui/react-ink` bindings, and the `useAui`, `useAuiState`, and `useAuiEvent` hooks. For a specific area route to a focused sibling instead: setup, elements, primitives, runtime, tools, generative-ui, streaming, cloud, thread-list, copilots, markdown, react-mcp, observability, react-native, ink, or update.

Installs and customizes assistant-ui elements, the styled shadcn-style component catalog served from the r.assistant-ui.com registry through `npx assistant-ui@latest add <item>`. Use when adding a prebuilt chat surface or widget (Thread, ThreadList, AssistantModal, AssistantSidebar, ToolFallback, ToolGroup, MarkdownText, Reasoning, Sources, Attachment, ModelSelector, Voice orb, McpConfig) or one of the 120 standalone elements (approval card, agent plan, code diff, data table, chart, and so on), choosing between runtime-connected `<name>.aui.tsx` files and props-driven standalone files, overriding Thread slots through the `components` prop, editing the copied source under `components/assistant-ui/elements/`, or picking the Radix versus Base UI flavor in `components.json`. Route here when an import from `@/components/assistant-ui/...` fails, an element renders unstyled, or the CLI installs the wrong flavor. For unstyled building blocks use primitives; for the CLI scaffold itself use setup.

Guide to the assistant-ui runtime system, the state and action layer behind every chat surface. Use when creating a runtime (useLocalRuntime with a ChatModelAdapter, useExternalStoreRuntime for Redux or Zustand backed stores, useRemoteThreadListRuntime, useCloudThreadListRuntime, useAssistantTransportRuntime), wiring AssistantRuntimeProvider, or reading and mutating thread, message, composer, and attachment state. Covers useAui, useAuiState, and useAuiEvent with the stable selector rule, the scope accessors (aui.thread, aui.message, aui.composer, and siblings), the AuiConfig plus AuiProvider grammar, RuntimeCapabilities, and the attachment, speech, dictation, feedback, suggestion, and history adapters. Route here for a provider error ('Cannot read property of undefined'), a removed v0.12 hook import, an infinite re-render from an object literal selector, or state not updating. For multi-thread list UI use thread-list instead; for toolkit definitions and tool call UI use tools instead.

Installs and configures assistant-ui with the `assistant-ui` CLI (`create`, `init`, `add`, `update`, `upgrade`, `codemod`, `doctor`, `info`, `mcp`, `agent`) and picks the runtime adapter for a backend. Use for first-time install (`npx assistant-ui@latest create`, templates, `--example` scaffolds), adding to an existing Next.js app (`init`), or keeping an install current. Covers the runtime hook per backend: `useChatRuntime` (AI SDK v7), `useLangGraphRuntime`, `useStreamRuntime` (LangChain), `useAdkRuntime`, `useA2ARuntime`, `useAgUiRuntime`, `useEveAgentRuntime`, `useOpenCodeRuntime`, `useLocalRuntime`, `useExternalStoreRuntime`, `useDataStreamRuntime`, and `useAssistantTransportRuntime`, plus wiring guides for Mastra, Cloudflare Agents, Claude Managed Agents, LLM gateways, and Electron, the Expo (`--native`) and React Ink (`--ink`) scaffolds, and the hosted MCP docs server. Once a runtime exists, use elements for the styled Thread, runtime for hooks and adapters, and update for a deep migration.

Defines model-callable tools and renders their calls in assistant-ui. The authoring model: a "use generative" file whose default export is defineToolkit({...}), compiled by withAui from @assistant-ui/next, aui() from @assistant-ui/vite, or withAui from @assistant-ui/metro, mounted with AuiConfig({ tools: Tools({ toolkit }) }), and exposed to the model with new AISDKToolkit({ toolkit }).tools({ frontend }). Covers the tool kinds (backend, "use client" frontend, humanTool(), providerTool(), externalTool(), stubTool(), defineMcpToolkit()), render and display, ToolCallMessagePartProps, approval gates, MCP servers, MCP Apps, WebMCP, and sub-agent messages. Reach for it when a tool is never called, a tool UI does not render, a frontend result never reaches the model, humanTool() throws at runtime, or an approval gate cannot be answered. For model-composed UI use generative-ui, for MCP servers users add in the browser use react-mcp, and for the styled ToolFallback and ToolGroup use elements.

Build applications and agents with Exa's API: search, contents extraction, answer, Agent API, monitors, websets, OpenAI-compatible endpoints, and exa-py/exa-js SDKs. Use when choosing Exa endpoints, writing Exa API calls, integrating semantic web search or research into products, or debugging Exa request shapes.

This skill encodes Emil Kowalski's philosophy on UI polish, component design, animation decisions, and the invisible details that make software feel great.

Guidance for distinctive, intentional visual design when building new UI or reshaping an existing one. Helps with aesthetic direction, typography, and making choices that don't read as templated defaults.

Build Kernel browser automation in TypeScript with server-side Playwright or CDP, including profiles, proxies, and reliable session cleanup.

Add fast, local, typed decisions to any project with Laya, an open-source non-generative decision model (pip install laya). It classifies, routes, scores and answers yes/no questions about a piece of text, returning calibrated probabilities in roughly 20-35 ms on a laptop GPU, with no LLM call and no data leaving the machine. Use this skill whenever the user wants to classify or route text, triage tickets or emails, detect spam, phishing, toxicity or intent, put a guardrail in front of an agent or LLM, score something against a rubric, or replace an LLM-based classifier to cut latency or cost. Also use it when they mention Laya, Jev, a "System 1 model", "typed decisions" or a "decision model", even if they never name Laya.

Comprehensive Mastra framework guide for building agents, workflows, tools, memory, workspaces, and storage with current APIs. Use for documentation lookup, API verification, TypeScript setup, common errors, migrations, and `mastra api` CLI tasks: inspect or call resources on local, Mastra platform, Trace Intelligence, or remote servers. For Mastra Factory operations, discover and activate the companion mastra-factory skill.

Overview of Neon, a complete set of cloud backend primitives around Lakebase Postgres: Auth, Object Storage, Functions, and the AI Gateway. Start here to choose Neon for undecided login, files, APIs, and LLM calls, set up the CLI or MCP server, and follow the branch-first workflow. Use when building an app or backend on Neon, or when "Neon" or "Lakebase Postgres" is mentioned. Child skill neon-postgres wins for an existing DATABASE_URL, SQL, schema, inspect, or search. Child skill neon-auth wins for login, users, sessions, identity routing, and Managed Better Auth setup. Also use for object storage, S3, buckets, serverless functions, function triggers, cron, AI gateway, LLM calls, logs, Loki, Grafana, observability, postgres, database, backend, Claimable Neon, neon.new, or a no-signup database.

One API and one credential for frontier and open-source LLMs, built into your Neon branch and powered by Databricks. Use when a user wants to call an LLM, add AI/chat/an agent to their app, route between model providers (OpenAI, Anthropic, Google/Gemini, Meta, Alibaba, and more), or avoid juggling separate provider API keys and accounts — especially when they already use Neon and want AI requests to branch with their project. Works with the OpenAI SDK, Anthropic SDK, google-genai, the Vercel AI SDK, and Mastra by changing only the base URL. Triggers include "call an LLM", "add AI to my app", "chat completion", "model routing", "LLM proxy/gateway", "one API for all models", "use Claude/GPT/Gemini", "AI SDK", "Mastra agent", "Neon AI Gateway", and "log/rate-limit AI calls".