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Use when building custom chat UIs, rendering tool results, or troubleshooting AI response display issues.\nmetadata:\n priority: 4\n docs:\n - \"https:\u002F\u002Fnextjs.org\u002Fdocs\u002Fapp\u002Fapi-reference\u002Ffile-conventions\u002Froute\"\n sitemap: \"https:\u002F\u002Fnextjs.org\u002Fsitemap.xml\"\n pathPatterns:\n - 'components\u002Fchat\u002F**'\n - 'components\u002Fchat-*.tsx'\n - 'components\u002Fchat-*.ts'\n - 'src\u002Fcomponents\u002Fchat\u002F**'\n - 'src\u002Fcomponents\u002Fchat-*.tsx'\n - 'src\u002Fcomponents\u002Fchat-*.ts'\n - 'components\u002Fmessage*.tsx'\n - 'src\u002Fcomponents\u002Fmessage*.tsx'\n bashPatterns: []\n---\n\n# AI Chat Response Rendering\n\nYou are an expert in rendering AI SDK v6 chat responses — UIMessage parts, tool call results, streaming states, and structured data display in React applications.\n\n## The Problem\n\nWhen building chat interfaces with AI SDK v6, the raw message format includes multiple part types (text, tool calls, reasoning, images). Without proper rendering, responses appear as raw JSON or malformed output.\n\n## AI SDK v6 Message Format\n\nIn v6, messages use the `UIMessage` type with a `parts` array:\n\n```ts\ninterface UIMessage {\n id: string\n role: 'user' | 'assistant'\n parts: UIMessagePart[]\n}\n\n\u002F\u002F Part types:\n\u002F\u002F - { type: 'text', text: string }\n\u002F\u002F - { type: 'tool-\u003CtoolName>', toolCallId: string, state: string, input?: unknown, output?: unknown }\n\u002F\u002F state values: 'partial-call' | 'call' | 'output-available' | 'approval-requested' | 'approval-responded' | 'output-denied'\n\u002F\u002F - { type: 'reasoning', text: string }\n\u002F\u002F - { type: 'step-start' } \u002F\u002F internal, skip in rendering\n```\n\n## Recommended: Use AI Elements\n\nThe simplest approach is to use AI Elements, which handles all part types automatically:\n\n```tsx\nimport { Message } from '@\u002Fcomponents\u002Fai-elements\u002Fmessage'\nimport { Conversation } from '@\u002Fcomponents\u002Fai-elements\u002Fconversation'\n\n{messages.map((message) => (\n \u003CMessage key={message.id} message={message} \u002F>\n))}\n```\n\n⤳ skill: ai-elements — Full component library for AI interfaces\n\n## Manual Rendering Pattern\n\nIf you need custom rendering without AI Elements, follow this pattern:\n\n```tsx\n'use client'\nimport { useChat } from '@ai-sdk\u002Freact'\nimport { DefaultChatTransport } from 'ai'\n\nexport function Chat() {\n const { messages, sendMessage, status } = useChat({\n transport: new DefaultChatTransport({ api: '\u002Fapi\u002Fchat' }),\n })\n\n const isLoading = status === 'streaming' || status === 'submitted'\n\n return (\n \u003Cdiv>\n {messages.map((message) => (\n \u003Cdiv key={message.id}>\n {message.parts?.map((part, i) => {\n \u002F\u002F 1. Text parts — render as formatted text\n if (part.type === 'text' && part.text.trim()) {\n return (\n \u003Cdiv key={i} className={\n message.role === 'user'\n ? 'bg-primary text-primary-foreground rounded-lg px-3 py-2'\n : 'bg-muted rounded-lg px-3 py-2'\n }>\n {part.text}\n \u003C\u002Fdiv>\n )\n }\n\n \u002F\u002F 2. Tool parts — type is \"tool-\u003CtoolName>\"\n if (part.type.startsWith('tool-')) {\n const toolPart = part as {\n type: string\n toolCallId: string\n state: string\n input?: unknown\n output?: unknown\n }\n const toolName = toolPart.type.replace('tool-', '')\n\n if (toolPart.state === 'output-available' && toolPart.output) {\n return \u003CToolResultCard key={i} name={toolName} output={toolPart.output} \u002F>\n }\n\n if (toolPart.state === 'output-denied') {\n return (\n \u003Cdiv key={i} className=\"text-sm text-muted-foreground\">\n {toolName} was denied\n \u003C\u002Fdiv>\n )\n }\n\n if (toolPart.state === 'approval-requested') {\n return (\n \u003Cdiv key={i} className=\"text-sm text-yellow-500\">\n {toolName} requires approval\n \u003C\u002Fdiv>\n )\n }\n\n return (\n \u003Cdiv key={i} className=\"text-sm text-muted-foreground animate-pulse\">\n Running {toolName}...\n \u003C\u002Fdiv>\n )\n }\n\n \u002F\u002F 3. Reasoning parts\n if (part.type === 'reasoning') {\n return (\n \u003Cdetails key={i} className=\"text-xs text-muted-foreground\">\n \u003Csummary>Thinking...\u003C\u002Fsummary>\n \u003Cp className=\"whitespace-pre-wrap\">{(part as { text: string }).text}\u003C\u002Fp>\n \u003C\u002Fdetails>\n )\n }\n\n \u002F\u002F 4. Skip unknown types (step-start, etc.)\n return null\n })}\n \u003C\u002Fdiv>\n ))}\n \u003C\u002Fdiv>\n )\n}\n```\n\n## Rendering Tool Results as Cards\n\nInstead of dumping raw JSON, render structured tool output as human-readable cards:\n\n```tsx\nfunction ToolResultCard({ name, output }: { name: string; output: unknown }) {\n const data = output as Record\u003Cstring, unknown>\n\n \u002F\u002F Pattern: Check for known result shapes and render accordingly\n if (data?.success && data?.issue) {\n const issue = data.issue as { identifier?: string; title?: string }\n return (\n \u003Cdiv className=\"rounded border border-border bg-card p-2 text-sm\">\n \u003Cspan className=\"font-medium text-green-400\">\n {name === 'createIssue' ? 'Created' : 'Updated'} {issue.identifier}\n \u003C\u002Fspan>\n \u003Cp className=\"text-muted-foreground\">{issue.title}\u003C\u002Fp>\n \u003C\u002Fdiv>\n )\n }\n\n if (data?.items && Array.isArray(data.items)) {\n return (\n \u003Cdiv className=\"rounded border border-border bg-card p-2 text-sm\">\n \u003Cp className=\"font-medium\">{data.items.length} results\u003C\u002Fp>\n {data.items.slice(0, 5).map((item: Record\u003Cstring, unknown>, i: number) => (\n \u003Cp key={i} className=\"text-muted-foreground\">{String(item.name || item.title || item.id)}\u003C\u002Fp>\n ))}\n \u003C\u002Fdiv>\n )\n }\n\n if (data?.error) {\n return (\n \u003Cdiv className=\"rounded border border-destructive\u002F30 bg-destructive\u002F10 p-2 text-sm text-destructive\">\n {String(data.error)}\n \u003C\u002Fdiv>\n )\n }\n\n \u002F\u002F Fallback: simple completion message (not raw JSON)\n return (\n \u003Cdiv className=\"rounded border border-border bg-card p-2 text-xs text-muted-foreground\">\n {name} completed\n \u003C\u002Fdiv>\n )\n}\n```\n\n## Server-Side Requirements\n\nThe server route must use the correct v6 response format:\n\n```ts\n\u002F\u002F app\u002Fapi\u002Fchat\u002Froute.ts\nimport { streamText, convertToModelMessages, gateway } from 'ai'\n\nexport async function POST(req: Request) {\n const { messages } = await req.json()\n\n \u002F\u002F IMPORTANT: convertToModelMessages is async in v6\n const modelMessages = await convertToModelMessages(messages)\n\n const result = streamText({\n model: gateway('anthropic\u002Fclaude-sonnet-4.6'),\n messages: modelMessages,\n })\n\n \u002F\u002F Use toUIMessageStreamResponse for chat UIs (not toDataStreamResponse)\n return result.toUIMessageStreamResponse()\n}\n```\n\n## Client-Side Requirements\n\n```tsx\nimport { useChat } from '@ai-sdk\u002Freact'\nimport { DefaultChatTransport } from 'ai'\n\nconst { messages, sendMessage, status } = useChat({\n \u002F\u002F v6 uses transport instead of api\n transport: new DefaultChatTransport({ api: '\u002Fapi\u002Fchat' }),\n})\n\n\u002F\u002F v6 uses sendMessage instead of handleSubmit\nsendMessage({ text: inputValue })\n\n\u002F\u002F Status values: 'ready' | 'submitted' | 'streaming'\nconst isLoading = status === 'streaming' || status === 'submitted'\n```\n\n## Common Mistakes\n\n### 1. Raw JSON in chat responses\n\n**Cause**: Rendering `message.content` instead of iterating `message.parts`.\n\n**Fix**: Always iterate `message.parts` and handle each type:\n\n```tsx\n\u002F\u002F WRONG — shows raw JSON\n\u003Cdiv>{message.content}\u003C\u002Fdiv>\n\n\u002F\u002F RIGHT — renders each part type\n{message.parts?.map((part, i) => {\n if (part.type === 'text') return \u003Cspan key={i}>{part.text}\u003C\u002Fspan>\n \u002F\u002F ... handle other types\n})}\n```\n\n### 2. Tool results showing as JSON blobs\n\n**Cause**: Using `JSON.stringify(output)` as the display.\n\n**Fix**: Create structured card components for known tool output shapes.\n\n### 3. \"Invalid prompt: messages do not contain...\" error\n\n**Cause**: Not converting UI messages to model messages on the server.\n\n**Fix**: Use `await convertToModelMessages(messages)` — it's async in v6.\n\n### 4. Messages not appearing \u002F empty responses\n\n**Cause**: Using `toDataStreamResponse()` instead of `toUIMessageStreamResponse()`.\n\n**Fix**: Use `toUIMessageStreamResponse()` when the client uses `useChat` with `DefaultChatTransport`.\n\n### 5. useChat not working with v6\n\n**Cause**: Using the v5 `useChat({ api: '\u002Fapi\u002Fchat' })` pattern.\n\n**Fix**: Use `DefaultChatTransport`:\n\n```tsx\n\u002F\u002F v5 (old)\nconst { messages, handleSubmit, input } = useChat({ api: '\u002Fapi\u002Fchat' })\n\n\u002F\u002F v6 (current)\nconst { messages, sendMessage, status } = useChat({\n transport: new DefaultChatTransport({ api: '\u002Fapi\u002Fchat' }),\n})\n```\n\n## Decision Tree\n\n```\nBuilding a chat UI with AI SDK v6?\n └─ Want pre-built components?\n └─ Yes → Use AI Elements (⤳ skill: ai-elements)\n └─ No → Manual rendering with parts iteration\n └─ Tool results look like JSON?\n └─ Create ToolResultCard components for each tool's output shape\n └─ Text not rendering?\n └─ Check part.type === 'text' and use part.text\n └─ Server errors?\n └─ Check: await convertToModelMessages(), toUIMessageStreamResponse()\n```\n\n## Server-Side Message Validation\n\nUse `validateUIMessages` to validate incoming messages before processing:\n\n```ts\nimport { validateUIMessages, convertToModelMessages, streamText, gateway } from 'ai'\n\nexport async function POST(req: Request) {\n const { messages } = await req.json()\n const validatedMessages = validateUIMessages(messages)\n const modelMessages = await convertToModelMessages(validatedMessages)\n \u002F\u002F ...\n}\n```\n\n## Official Documentation\n\n- [AI SDK UI](https:\u002F\u002Fai-sdk.dev\u002Fdocs\u002Fai-sdk-ui)\n- [useChat Reference](https:\u002F\u002Fai-sdk.dev\u002Fdocs\u002Fai-sdk-ui\u002Fchatbot)\n- [UIMessage Types](https:\u002F\u002Fai-sdk.dev\u002Fdocs\u002Freference\u002Fai-sdk-core\u002Fui-message)\n- [AI Elements](https:\u002F\u002Fai-sdk.dev\u002Felements)\n",{"data":34,"body":50},{"name":4,"description":6,"metadata":35},{"priority":36,"docs":37,"sitemap":39,"pathPatterns":40,"bashPatterns":49},4,[38],"https:\u002F\u002Fnextjs.org\u002Fdocs\u002Fapp\u002Fapi-reference\u002Ffile-conventions\u002Froute","https:\u002F\u002Fnextjs.org\u002Fsitemap.xml",[41,42,43,44,45,46,47,48],"components\u002Fchat\u002F**","components\u002Fchat-*.tsx","components\u002Fchat-*.ts","src\u002Fcomponents\u002Fchat\u002F**","src\u002Fcomponents\u002Fchat-*.tsx","src\u002Fcomponents\u002Fchat-*.ts","components\u002Fmessage*.tsx","src\u002Fcomponents\u002Fmessage*.tsx",[],{"type":51,"children":52},"root",[53,62,68,75,80,86,108,313,319,324,543,548,554,559,2699,2705,2710,4007,4013,4018,4392,4398,4741,4747,4754,4780,4797,5046,5052,5069,5078,5084,5093,5110,5116,5139,5169,5175,5192,5206,5438,5444,5454,5460,5473,5716,5722,5769],{"type":54,"tag":55,"props":56,"children":58},"element","h1",{"id":57},"ai-chat-response-rendering",[59],{"type":60,"value":61},"text","AI Chat Response Rendering",{"type":54,"tag":63,"props":64,"children":65},"p",{},[66],{"type":60,"value":67},"You are an expert in rendering AI SDK v6 chat responses — UIMessage parts, tool call results, streaming states, and structured data display in React applications.",{"type":54,"tag":69,"props":70,"children":72},"h2",{"id":71},"the-problem",[73],{"type":60,"value":74},"The Problem",{"type":54,"tag":63,"props":76,"children":77},{},[78],{"type":60,"value":79},"When building chat interfaces with AI SDK v6, the raw message format includes multiple part types (text, tool calls, reasoning, images). 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var(--shiki-dark-text-decoration);}",{"items":5776,"total":5977},[5777,5798,5821,5838,5854,5873,5892,5904,5920,5934,5946,5961],{"slug":5778,"name":5778,"fn":5779,"description":5780,"org":5781,"tags":5782,"stars":5795,"repoUrl":5796,"updatedAt":5797},"prior-auth-packet-builder","build healthcare prior authorization packets","Build a concise prior authorization packet from local case files and payer policy docs.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[5783,5786,5789,5792],{"name":5784,"slug":5785,"type":15},"Documents","documents",{"name":5787,"slug":5788,"type":15},"Healthcare","healthcare",{"name":5790,"slug":5791,"type":15},"Insurance","insurance",{"name":5793,"slug":5794,"type":15},"Regulatory Compliance","regulatory-compliance",28169,"https:\u002F\u002Fgithub.com\u002Fopenai\u002Fopenai-agents-python","2026-04-16T05:11:39.180399",{"slug":5799,"name":5799,"fn":5800,"description":5801,"org":5802,"tags":5803,"stars":5818,"repoUrl":5819,"updatedAt":5820},"aspnet-core","build ASP.NET Core web applications","Build, review, refactor, or architect ASP.NET Core web applications using current official guidance for .NET web development. Use when working on Blazor Web Apps, Razor Pages, MVC, Minimal APIs, controller-based Web APIs, SignalR, gRPC, middleware, dependency injection, configuration, authentication, authorization, testing, performance, deployment, or ASP.NET Core upgrades.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[5804,5807,5809,5812,5815],{"name":5805,"slug":5806,"type":15},".NET","dotnet",{"name":5808,"slug":5799,"type":15},"ASP.NET Core",{"name":5810,"slug":5811,"type":15},"Blazor","blazor",{"name":5813,"slug":5814,"type":15},"C#","csharp",{"name":5816,"slug":5817,"type":15},"Web Development","web-development",23787,"https:\u002F\u002Fgithub.com\u002Fopenai\u002Fskills","2026-04-12T05:07:02.819491",{"slug":5822,"name":5822,"fn":5823,"description":5824,"org":5825,"tags":5826,"stars":5818,"repoUrl":5819,"updatedAt":5837},"chatgpt-apps","build ChatGPT Apps SDK applications","Build, scaffold, refactor, and troubleshoot ChatGPT Apps SDK applications that combine an MCP server and widget UI. Use when Codex needs to design tools, register UI resources, wire the MCP Apps bridge or ChatGPT compatibility APIs, apply Apps SDK metadata or CSP or domain settings, or produce a docs-aligned project scaffold. Prefer a docs-first workflow by invoking the openai-docs skill or OpenAI developer docs MCP tools before generating code.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[5827,5830,5833,5836],{"name":5828,"slug":5829,"type":15},"Apps SDK","apps-sdk",{"name":5831,"slug":5832,"type":15},"ChatGPT","chatgpt",{"name":5834,"slug":5835,"type":15},"MCP","mcp",{"name":9,"slug":8,"type":15},"2026-04-12T05:07:05.468097",{"slug":5839,"name":5839,"fn":5840,"description":5841,"org":5842,"tags":5843,"stars":5818,"repoUrl":5819,"updatedAt":5853},"cli-creator","build CLIs from API docs","Build a composable CLI for Codex from API docs, an OpenAPI spec, existing curl examples, an SDK, a web app, an admin tool, or a local script. Use when the user wants Codex to create a command-line tool that can run from any repo, expose composable read\u002Fwrite commands, return stable JSON, manage auth, and pair with a companion skill.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[5844,5847,5850],{"name":5845,"slug":5846,"type":15},"API Development","api-development",{"name":5848,"slug":5849,"type":15},"CLI","cli",{"name":5851,"slug":5852,"type":15},"Codex","codex","2026-04-12T05:07:04.132762",{"slug":5855,"name":5855,"fn":5856,"description":5857,"org":5858,"tags":5859,"stars":5818,"repoUrl":5819,"updatedAt":5872},"cloudflare-deploy","deploy projects to Cloudflare","Deploy applications and infrastructure to Cloudflare using Workers, Pages, and related platform services. Use when the user asks to deploy, host, publish, or set up a project on Cloudflare.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[5860,5863,5866,5869],{"name":5861,"slug":5862,"type":15},"Cloudflare","cloudflare",{"name":5864,"slug":5865,"type":15},"Cloudflare Pages","cloudflare-pages",{"name":5867,"slug":5868,"type":15},"Cloudflare Workers","cloudflare-workers",{"name":5870,"slug":5871,"type":15},"Deployment","deployment","2026-04-12T05:07:14.275118",{"slug":5874,"name":5874,"fn":5875,"description":5876,"org":5877,"tags":5878,"stars":5818,"repoUrl":5819,"updatedAt":5891},"define-goal","define and set measurable project goals","Help the user define a concrete, measurable goal before starting work, especially when they ask to use the goal tool, create a goal, set an objective, clarify success criteria, or turn a fuzzy intention into a quantitative outcome. Use this skill for goal creation and goal refinement only; it does not manage durable snapshots, decision logs, or long-running execution artifacts.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[5879,5882,5885,5888],{"name":5880,"slug":5881,"type":15},"Productivity","productivity",{"name":5883,"slug":5884,"type":15},"Project Management","project-management",{"name":5886,"slug":5887,"type":15},"Strategy","strategy",{"name":5889,"slug":5890,"type":15},"Task Management","task-management","2026-05-23T06:17:16.870838",{"slug":5893,"name":5893,"fn":5894,"description":5895,"org":5896,"tags":5897,"stars":5818,"repoUrl":5819,"updatedAt":5903},"figma","translate Figma designs into code","Use the Figma MCP server to fetch design context, screenshots, variables, and assets from Figma, and to translate Figma nodes into production code. Trigger when a task involves Figma URLs, node IDs, design-to-code implementation, or Figma MCP setup and troubleshooting.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[5898,5899,5901,5902],{"name":20,"slug":21,"type":15},{"name":5900,"slug":5893,"type":15},"Figma",{"name":17,"slug":18,"type":15},{"name":5834,"slug":5835,"type":15},"2026-04-12T05:06:47.939943",{"slug":5905,"name":5905,"fn":5906,"description":5907,"org":5908,"tags":5909,"stars":5818,"repoUrl":5819,"updatedAt":5919},"figma-code-connect-components","connect Figma designs to code components","Connects Figma design components to code components using Code Connect mapping tools. Use when user says \"code connect\", \"connect this component to code\", \"map this component\", \"link component to code\", \"create code connect mapping\", or wants to establish mappings between Figma designs and code implementations. For canvas writes via `use_figma`, use `figma-use`.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[5910,5911,5914,5915,5916],{"name":20,"slug":21,"type":15},{"name":5912,"slug":5913,"type":15},"Design System","design-system",{"name":5900,"slug":5893,"type":15},{"name":17,"slug":18,"type":15},{"name":5917,"slug":5918,"type":15},"UI Components","ui-components","2026-05-10T05:59:52.971881",{"slug":5921,"name":5921,"fn":5922,"description":5923,"org":5924,"tags":5925,"stars":5818,"repoUrl":5819,"updatedAt":5933},"figma-create-design-system-rules","generate design system rules from Figma","Generates custom design system rules for the user's codebase. Use when user says \"create design system rules\", \"generate rules for my project\", \"set up design rules\", \"customize design system guidelines\", or wants to establish project-specific conventions for Figma-to-code workflows. Requires Figma MCP server connection.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[5926,5927,5928,5931,5932],{"name":20,"slug":21,"type":15},{"name":5912,"slug":5913,"type":15},{"name":5929,"slug":5930,"type":15},"Documentation","documentation",{"name":5900,"slug":5893,"type":15},{"name":17,"slug":18,"type":15},"2026-05-16T06:07:47.821474",{"slug":5935,"name":5935,"fn":5936,"description":5937,"org":5938,"tags":5939,"stars":5818,"repoUrl":5819,"updatedAt":5945},"figma-implement-design","translate Figma designs into application code","Translates Figma designs into production-ready application code with 1:1 visual fidelity. Use when implementing UI code from Figma files, when user mentions \"implement design\", \"generate code\", \"implement component\", provides Figma URLs, or asks to build components matching Figma specs. For Figma canvas writes via `use_figma`, use `figma-use`.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[5940,5941,5942,5943,5944],{"name":20,"slug":21,"type":15},{"name":5900,"slug":5893,"type":15},{"name":17,"slug":18,"type":15},{"name":5917,"slug":5918,"type":15},{"name":5816,"slug":5817,"type":15},"2026-05-16T06:07:40.583615",{"slug":5947,"name":5947,"fn":5948,"description":5949,"org":5950,"tags":5951,"stars":5818,"repoUrl":5819,"updatedAt":5960},"hatch-pet","create animated pets for Codex","Create, repair, validate, visually QA, and package Codex-compatible animated pets and pet spritesheets from character art, generated images, company or prospect brand cues, or visual references. Use when a user wants a lightweight-worker Codex pet workflow, a non-pixel custom pet style, a prospect or company mascot pet, or a full 8x9 animated pet atlas with transparent unused cells, QA contact sheets, and pet.json packaging. This skill composes the installed $imagegen system skill for visual generation and uses bundled scripts for deterministic spritesheet assembly.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[5952,5955,5956,5959],{"name":5953,"slug":5954,"type":15},"Animation","animation",{"name":5851,"slug":5852,"type":15},{"name":5957,"slug":5958,"type":15},"Creative","creative",{"name":20,"slug":21,"type":15},"2026-05-02T05:31:48.48485",{"slug":5962,"name":5962,"fn":5963,"description":5964,"org":5965,"tags":5966,"stars":5818,"repoUrl":5819,"updatedAt":5976},"imagegen","generate and edit raster images","Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output should be a bitmap asset rather than repo-native code or vector. Do not use when the task is better handled by editing existing SVG\u002Fvector\u002Fcode-native assets, extending an established icon or logo system, or building the visual directly in HTML\u002FCSS\u002Fcanvas.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[5967,5968,5969,5972,5975],{"name":5957,"slug":5958,"type":15},{"name":20,"slug":21,"type":15},{"name":5970,"slug":5971,"type":15},"Image Generation","image-generation",{"name":5973,"slug":5974,"type":15},"Images","images",{"name":9,"slug":8,"type":15},"2026-05-15T06:23:24.312127",675,{"items":5979,"total":6093},[5980,5997,6013,6025,6043,6061,6081],{"slug":5981,"name":5981,"fn":5982,"description":5983,"org":5984,"tags":5985,"stars":22,"repoUrl":23,"updatedAt":5996},"accessibility-and-inclusive-visualization","make data visualizations accessible","Make data visualizations accessible and inclusive. Use when the user needs chart or diagram accessibility guidance, text alternatives for complex visuals, color and contrast review, keyboard support, reduced-motion behavior for animation or parallax, or an accessibility QA workflow for exported figures, UML-like diagrams, and dashboards.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[5986,5989,5992,5995],{"name":5987,"slug":5988,"type":15},"Accessibility","accessibility",{"name":5990,"slug":5991,"type":15},"Charts","charts",{"name":5993,"slug":5994,"type":15},"Data Visualization","data-visualization",{"name":20,"slug":21,"type":15},"2026-06-30T19:00:57.102",{"slug":5998,"name":5998,"fn":5999,"description":6000,"org":6001,"tags":6002,"stars":22,"repoUrl":23,"updatedAt":6012},"agent-browser","automate browser interactions for agents","Browser automation CLI for AI agents. Use when the user needs to interact with websites, verify dev server output, test web apps, navigate pages, fill forms, click buttons, take screenshots, extract data, or automate any browser task. Also triggers when a dev server starts so you can verify it visually.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[6003,6006,6009],{"name":6004,"slug":6005,"type":15},"Agents","agents",{"name":6007,"slug":6008,"type":15},"Browser Automation","browser-automation",{"name":6010,"slug":6011,"type":15},"Testing","testing","2026-04-06T18:41:03.44016",{"slug":6014,"name":6014,"fn":6015,"description":6016,"org":6017,"tags":6018,"stars":22,"repoUrl":23,"updatedAt":6024},"agent-browser-verify","verify dev server output with automated browser","Automated browser verification for dev servers. Triggers when a dev server starts to run a visual gut-check with agent-browser — verifies the page loads, checks for console errors, validates key UI elements, and reports pass\u002Ffail before continuing.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[6019,6020,6023],{"name":6007,"slug":6008,"type":15},{"name":6021,"slug":6022,"type":15},"Local Development","local-development",{"name":6010,"slug":6011,"type":15},"2026-04-06T18:41:17.526867",{"slug":6026,"name":6026,"fn":6027,"description":6028,"org":6029,"tags":6030,"stars":22,"repoUrl":23,"updatedAt":6042},"agents-sdk","build AI agents on Cloudflare Workers","Build AI agents on Cloudflare Workers using the Agents SDK. Load when creating stateful agents, durable workflows, real-time WebSocket apps, scheduled tasks, MCP servers, or chat applications. Covers Agent class, state management, callable RPC, Workflows integration, and React hooks. Biases towards retrieval from Cloudflare docs over pre-trained knowledge.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[6031,6032,6033,6036,6039],{"name":6004,"slug":6005,"type":15},{"name":5867,"slug":5868,"type":15},{"name":6034,"slug":6035,"type":15},"SDK","sdk",{"name":6037,"slug":6038,"type":15},"Serverless","serverless",{"name":6040,"slug":6041,"type":15},"WebSockets","websockets","2026-04-06T18:39:51.717063",{"slug":6044,"name":6044,"fn":6045,"description":6046,"org":6047,"tags":6048,"stars":22,"repoUrl":23,"updatedAt":6060},"ai-elements","build chat UIs with AI Elements","AI Elements component library guidance — pre-built React components for AI interfaces built on shadcn\u002Fui. Use when building chat UIs, message displays, tool call rendering, streaming responses, reasoning panels, or any AI-native interface with the AI SDK.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[6049,6050,6053,6056,6057],{"name":17,"slug":18,"type":15},{"name":6051,"slug":6052,"type":15},"React","react",{"name":6054,"slug":6055,"type":15},"shadcn\u002Fui","shadcn-ui",{"name":5917,"slug":5918,"type":15},{"name":6058,"slug":6059,"type":15},"Vercel","vercel","2026-04-06T18:40:59.619419",{"slug":6062,"name":6062,"fn":6063,"description":6064,"org":6065,"tags":6066,"stars":22,"repoUrl":23,"updatedAt":6080},"ai-gateway","configure Vercel AI Gateway","Vercel AI Gateway expert guidance. Use when configuring model routing, provider failover, cost tracking, or managing multiple AI providers through a unified API.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[6067,6070,6073,6076,6079],{"name":6068,"slug":6069,"type":15},"AI Infrastructure","ai-infrastructure",{"name":6071,"slug":6072,"type":15},"Cost Optimization","cost-optimization",{"name":6074,"slug":6075,"type":15},"LLM","llm",{"name":6077,"slug":6078,"type":15},"Performance","performance",{"name":6058,"slug":6059,"type":15},"2026-04-06T18:40:44.377464",{"slug":6082,"name":6082,"fn":6083,"description":6084,"org":6085,"tags":6086,"stars":22,"repoUrl":23,"updatedAt":6092},"ai-generation-persistence","implement persistence patterns for AI generations","AI generation persistence patterns — unique IDs, addressable URLs, database storage, and cost tracking for every LLM generation",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[6087,6088,6091],{"name":6071,"slug":6072,"type":15},{"name":6089,"slug":6090,"type":15},"Database","database",{"name":6074,"slug":6075,"type":15},"2026-04-06T18:41:08.513425",600]