ai-elements
Build AI chat interfaces using ai-elements components — conversations, messages, tool displays, prompt inputs, and more. Use when the user wants to build a chatbot, AI assistant UI, or any AI-powered chat interface.
Supply asset profile
Coding and developer agents
Code review, repo analysis, testing, CI, GitHub, DevOps, and developer workflow skills.
Scenario
GitHub automation
I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add oomol-lab/wanta --skill ai-elements
Maintenance
fresh
Pushed today
Risk
Needs review
Dependency or permission surface needs review
GitHub quality
63
65/100 Quality · 64/100 Trust
Coverage tags
Review notes
Dependency or permission surface needs review · Permission surface may require sandboxing
Agent adoption scorecard
Trust, audit, and install readiness at a glance
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
PromisingUseful candidate, but compare it with alternatives before adopting.
Trust
Do not auto-installTrust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Human review before install
Choose a stronger alternative or inspect the source manually before any install attempt.
Stars
63 GitHub stars
Repo activity
63 stars, 11 forks
Maintenance
Pushed today
License
Apache-2.0
Install
npx skills add oomol-lab/wanta --skill ai-elements
Install safety
standard package or runtime install path
Permission surface
secrets or environment access, shell or command execution
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Review before production
- SKILL.md does not explicitly list limitations or safe operating boundaries (e.g., when not to use this skill, potential pitfalls with component customization).
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- GitHub adoption: 63 GitHub stars
Install readiness
Install path available
- Install path is available
- Repository evidence is available
- License is declared
- No Agent Proven outcome evidence yet
Agent-readable metadata
Machine-readable decision data for this skill.
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
- GitHub automation workflows
- Claude Code teams
- builders willing to evaluate younger projects
- Inspect repository metadata
Suited agents
Install decision
- Command
- npx skills add oomol-lab/wanta --skill ai-elements
- Policy
- block
- Human review
- yes
Trust and risk
- Trust
- 56/100
- Audit
- 74/100
- Risk level
- Needs review
Outcome loop
- Endpoint
- /api/agent/outcome
- Event ID
- resolve
- Outcomes
- 5
Install command
npx skills add oomol-lab/wanta --skill ai-elementsDo not use when
- teams that need a vendor-supported SLA
- production agents without a repository review
- SKILL.md does not explicitly list limitations or safe operating boundaries (e.g., when not to use this skill, potential pitfalls with component customization).
- No OpenAgentSkill engagement data yet
- High-risk permission hints: Shell or command execution, Secrets or environment access
Alternative
Frontend Design
170.9K Stars
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Agent safety v2
34/100 · Avoid automatic install
This skill should not be selected by an agent without explicit human security review.
Do not auto-install. Inspect the source, dependencies, and permission surface first.
high
Shell or command execution
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Network access
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Filesystem access
Skill may read or write project files, documents, generated artifacts, or local workspace state.
high
Secrets or environment access
Skill metadata references credentials, tokens, environment variables, or secret-bearing workflows.
- High-risk permission hints: Shell or command execution, Secrets or environment access
- Dependency or permission surface needs review
Install targets
Install this skill in your agent workflow
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
OpenAgentSkill CLI
Resolve policy, run the source installer safely, and report a verified install receipt.
$ npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install oomol-lab-ai-elementsAgent resolve plan
Let an agent verify fit before installing.
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20ai-elements%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20ai-elements%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/oomol-lab-ai-elements/install
Agent should check
- Task fit and alternatives from Resolve API.
- Audit score, trust score, and safety policy warnings.
- Install target compatibility for Codex, Claude Code, Cursor, or CLI.
Copy prompt
Task: Use ai-elements in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20ai-elements%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/oomol-lab-ai-elements/install
Install command: npx skills add oomol-lab/wanta --skill ai-elements
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Give an agent the install path, not another directory page.
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/oomol-lab-ai-elements/install
LLM text format
/api/skills/oomol-lab-ai-elements/install?format=text
Find alternatives
/api/skills/search?q=ai-elements&limit=3
Agent prompt
Use ai-elements for this task. Review https://www.openagentskill.com/api/skills/oomol-lab-ai-elements/install, then install with: npx skills add oomol-lab/wanta --skill ai-elementsRegistry metadata
Agent-readable profile for automatic skill selection.
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/oomol-lab-ai-elements
LLM text
/api/registry/manifest/oomol-lab-ai-elements?format=text
Install alias
/api/registry/install/oomol-lab-ai-elements
Recommend
/api/registry/recommend?task=Use%20ai-elements%20in%20an%20agent%20workflow&limit=3
Agent fit
GitHub automation
Use-case tags
Platforms
Claude Code
Audit report
Needs review · 74/100
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Fallback candidate for GitHub automation
Prototype with this skill first; keep a fallback candidate ready.
Role in stack
Fallback candidate
Primary fit
GitHub automation
Trust label
Prototype first
Install path
Command ready
Use when
- GitHub automation workflows
- Claude Code teams
- builders willing to evaluate younger projects
Evidence
- recent repository activity
- install command or GitHub repo available
- 65/100 quality profile
review first
- SKILL.md does not explicitly list limitations or safe operating boundaries (e.g., when not to use this skill, potential pitfalls with component customization).
- No OpenAgentSkill engagement data yet
Implementation path
- 1Install it in a sandbox agent and run one GitHub automation task end to end.
- 2Compare output quality, latency, and failure behavior against at least one alternative.
- 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.
Trust profile
Do not auto-install
Trust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
GitHub adoption
CHECK63 GitHub stars
Stars/forks activity
CHECK63 stars, 11 forks; issue activity unavailable in current metadata
Recent maintenance
PASSPushed today
License clarity
PASSApache-2.0
Good signals
- AI review approved
- Install path is available
- Repository evidence is available
- Recently maintained repository
- Install command has no obvious high-risk pattern
- Outcome loop is ready but needs first real agent run
Review before install
- SKILL.md does not explicitly list limitations or safe operating boundaries (e.g., when not to use this skill, potential pitfalls with component customization).
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- GitHub adoption: 63 GitHub stars
- Stars/forks activity: 63 stars, 11 forks; issue activity unavailable in current metadata
- Dependency/runtime risk: command execution surface, credential or environment access
- Permission surface: secrets or environment access, shell or command execution
- No real agent outcome reports yet
- Human review required before unattended installation
Recommended action
Choose a stronger alternative or inspect the source manually before any install attempt.
Quality profile
Promising candidate for agent workflows
Useful candidate, but compare it with alternatives before adopting.
Workflow fit
Use this skill in these scenarios
Manage repositories
GitHub automation
I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.
Operate local tools
Local desktop
I need my agent to operate local files and desktop apps in a repeatable workflow.
Build and ship code
Coding agents
I need a coding agent that can understand a repository, edit code, and review pull requests.
Workflow fit
Add it to a complete workflow
Design, build, test, and ship interfaces
Frontend and UI
A practical workflow for agents that turn product briefs or Figma designs into polished frontend code, review the result, test it in a browser, and prepare a safe deployment.
Inspect, patch, and verify code
Coding review agent
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Turn skills into distribution
Content growth agent
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Alternative shortlist
Compare before you install
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Overview
--- name: ai-elements description: Build AI chat interfaces using ai-elements components — conversations, messages, tool displays, prompt inputs, and more. Use when the user wants to build a chatbot, AI assistant UI, or any AI-powered chat interface. ---
# AI Elements
[AI Elements](https://www.npmjs.com/package/ai-elements) is a component library and custom registry built on top of [shadcn/ui](https://ui.shadcn.com/) to help you build AI-native applications faster. It provides pre-built components like conversations, messages and more.
Installing AI Elements is straightforward and can be done in a couple of ways. You can use the dedicated CLI command for the fastest setup, or integrate via the standard shadcn/ui CLI if you've already adopted shadcn's workflow.
> **IMPORTANT:** Run all CLI commands using the project's package runner: `npx ai-elements@latest`, `pnpm dlx ai-elements@latest`, or `bunx --bun ai-elements@latest` — based on the project's `packageManager`. Examples below use `npx ai-elements@latest` but substitute the correct runner for the project.
## Prerequisites
Before installing AI Elements, make sure your environment meets the following requirements:
- [Node.js](https://nodejs.org/en/download/), version 18 or later - A [Next.js](https://nextjs.org/) project with the [AI SDK](https://ai-sdk.dev/) installed. - [shadcn/ui](https://ui.shadcn.com/) installed in your project. If you don't have it installed, running any install command will automatically install it for you. - We also highly recommend using the [AI Gateway](https://vercel.com/docs/ai-gateway) and adding `AI_GATEWAY_API_KEY` to your `env.local` so you don't have to use an API key from every provider. AI Gateway also gives $5 in usage per month so you can experiment with models. You can obtain an API key [here](https://vercel.com/d?to=%2F%5Bteam%5D%2F%7E%2Fai%2Fapi-keys&title=Get%20your%20AI%20Gateway%20key).
## Installing Components
You can install AI Elements components using either the AI Elements CLI or the shadcn/ui CLI. Both achieve the same result: adding the selected component’s code and any needed dependencies to your project.
The CLI will download the component’s code and integrate it into your project’s directory (usually under your components folder). By default, AI Elements components are added to the `@/components/ai-elements/` directory (or whatever folder you’ve configured in your shadcn components settings).
After running the command, you should see a confirmation in your terminal that the files were added. You can then proceed to use the component in your code.
## Usage
Once an AI Elements component is installed, you can import it and use it in your application like any other React component. The components are added as part of your codebase (not hidden in a library), so the usage feels very natural.
## Example
After installing AI Elements components, you can use them in your application like any other React component. For example:
```tsx title="conversation.tsx" "use client";
import { Message, MessageContent, MessageResponse, } from "@/components/ai-elements/message"; import { useChat } from "@ai-sdk/react";
const Example = () => { const { messages } = useChat();
return ( <> {messages.map(({ role, parts }, index) => ( <Message from={role} key={index}> <MessageContent> {parts.map((part, i) => { switch (part.type) { case "text": return ( <MessageResponse key={`${role}-${i}`}> {part.text} </MessageResponse> ); } })} </MessageContent> </Message> ))} </> ); };
export default Example; ```
In the example above, we import the `Message` component from our AI Elements directory and include it in our JSX. Then, we compose the component with the `MessageContent` and `MessageResponse` subcomponents. You can style or configure the component just as you would if you wrote it yourself – since the code lives in your project, you can even open the component file to see how it works or make custom modifications.
## Extensibility
All AI Elements components take as many primitive attributes as possible. For example, the `Message` component extends `HTMLAttributes<HTMLDivElement>`, so you can pass any props that a `div` supports. This makes it easy to extend the component with your own styles or functionality.
## Customization
After installation, no additional setup is needed. The component’s styles (Tailwind CSS classes) and scripts are already integrated. You can start interacting with the component in your app immediately.
For example, if you'd like to remove the rounding on `Message`, you can go to `components/ai-elements/message.tsx` and remove `rounded-lg` as follows:
```tsx title="components/ai-elements/message.tsx" highlight="8" export const MessageContent = ({ children, className, ...props }: MessageContentProps) => ( <div className={cn( "flex flex-col gap-2 text-sm text-foreground", "group-[.is-user]:bg-primary group-[.is-user]:text-primary-foreground group-[.is-user]:px-4 group-[.is-user]:py-3", className )} {...props} > <div className="is-user:dark">{children}</div> </div> ); ```
## Troubleshooting
### Why are my components not styled?
Make sure your project is configured correctly for shadcn/ui in Tailwind 4 - this means having a `globals.css` file that imports Tailwind and includes the shadcn/ui base styles.
### I ran the AI Elements CLI but nothing was added to my project
Double-check that:
- Your current working directory is the root of your project (where `package.json` lives). - Your components.json file (if using shadcn-style config) is set up correctly. - You’re using the latest version of the AI Elements CLI:
```bash title="Terminal" npx ai-elements@latest ```
If all else fails, feel free to open an [issue on GitHub](https://github.com/vercel/ai-elements/issues).
### Theme switching doesn’t work — my app stays in light mode
Ensure your app is using the same data-theme system that shadcn/ui and AI Elements expect. The default implementation toggles a data-theme attribute on the `<html>` element. Make sure your tailwind.config.js is using class or data- selectors accordingly.
### The component imports fail with “module not found”
Check the file exists. If it does, make sure your `tsconfig.json` has a proper paths alias for `@/` i.e.
```json title="tsconfig.json" { "compilerOptions": { "baseUrl": ".", "paths": { "@/*": ["./*"] } } } ```
### My AI coding assistant can't access AI Elements components
1. Verify your config file syntax is valid JSON. 2. Check that the file path is correct for your AI tool. 3. Restart your coding assistant after making changes. 4. Ensure you have a stable internet connection.
### Still stuck?
If none of these answers help, open an [issue on GitHub](https://github.com/vercel/ai-elements/issues) and someone will be happy to assist.
## Available Components
See the `references/` folder for detailed documentation on each component.
Technical details
- Version
- 1.0.0
- License
- Apache-2.0
- Last updated
- Aug 22, 2026
- Published
- Aug 22, 2026
Decision snapshot
Fallback candidate
recent repository activity
Audit
Install review
Install and adoption review
- Security
- 71/100
- Maintenance
- 100/100
- Install
- 92/100
Agent-proven evidence
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
- Success rate
- —
- Recent failure
- —
- Outcomes
- 0
- Output quality
- —
- Failed
- 0
- Not relevant
- 0
- Installs
- 0
- Risk blocked
- 0
- Setup needed
- 0
- Production
- 0
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Add to agent workflow
Free and open source. Review the report before installing into production agents.
Growth loop
Share kit
Scenario-led draft for ai-elements, ready for a manual X post.
A practical pick for design or creative work: ai-elements: Build AI chat interfaces using ai-elements components — conversations, messages, tool displays, prompt inputs, and more. Us... 63 stars https://www.openagentskill.com/skills/oomol-lab-ai-elements?ref=x
Optional reply with install command
Listing + install path for ai-elements: https://www.openagentskill.com/skills/oomol-lab-ai-elements?ref=x Install: npx skills add oomol-lab/wanta --skill ai-elements
Listing source
Registry indexed
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
- Creator
- oomol-lab
- Source
- oomol-lab/wanta
- Indexed by
- OpenAgentSkill community index
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
Claim this skill listing
This Registry indexed listing is attributed to oomol-lab but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.
Creator backlink kit
Add the evidence badges to your README
Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
[](https://www.openagentskill.com/skills/oomol-lab-ai-elements)
[](https://www.openagentskill.com/skills/oomol-lab-ai-elements)
[](https://www.openagentskill.com/skills/oomol-lab-ai-elements/audit)
[](https://www.openagentskill.com/skills/oomol-lab-ai-elements)Author
oomol-lab
@oomol-lab
Tags
Platform fit
Health signals
- GitHub stars
- 63
- Quality score
- 36/100
- Last GitHub push
- Aug 22, 2026
- Framework hints
- Unknown
- OpenAgentSkill views
- 0
- Install copies
- 0
- Outbound clicks
- 0
Community signal
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Trust & safety
Do not auto-install
- GitHub adoption63 GitHub starsCHECK
- Stars/forks activity63 stars, 11 forks; issue activity unavailable in current metadataCHECK
- Recent maintenancePushed todayPASS
- License clarityApache-2.0PASS
- README/SKILL.md completenessMetadata includes enough usage and workflow contextPASS
- Dependency/runtime riskcommand execution surface, credential or environment accessCHECK
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