vercel
Lets you deploy, manage, inspect and troubleshoot Vercel projects from the command line, covering deployments, build failures, environment variables and domains without leaving your terminal.
A Claude Code plugin with skills for building durable backend AI agents with the eve framework, plus skills to investigate issue reports, look up agent runs, and run security and correctness audits of code diffs.
Claude Code
$ npx -y skills add vercel/eve --agent claude-code
Codex
$ npx skills add vercel/eve -a codex
Cursor
$ npx skills add vercel/eve -a cursor
Gemini CLI
$ npx skills add vercel/eve -a gemini-cli
GitHub Copilot
$ npx skills add vercel/eve -a github-copilot
OpenCode
$ npx skills add vercel/eve -a opencode
Windsurf
$ npx skills add vercel/eve -a windsurf
eve is a filesystem-first framework for durable AI agents. Core agent capabilities live in conventional locations, so projects are easier to inspect, extend, and operate.
A typical eve agent has this structure:
my-agent/
└── agent/
├── agent.ts # Optional: model and runtime config
├── instructions.md # Required: the always-on system prompt
├── tools/ # Optional: typed functions the model can call
│ └── get_weather.ts
├── skills/ # Optional: procedures loaded on demand
│ └── plan_a_trip.md
├── channels/ # Optional: message channels (HTTP, Slack, Discord)
│ └── slack.ts
└── schedules/ # Optional: recurring cron jobs
└── weekly_recap.ts
Read the documentation for the full project layout and guides.
npx eve@latest init my-agent
This creates a new my-agent directory, installs its dependencies, initializes Git, and starts
the interactive terminal UI. The generated agent uses openai/gpt-6-luna-fast with high reasoning.
To start with another AI Gateway model, pass its model ID:
npx eve@latest init my-agent --model openai/gpt-5.6-terra
Passing --model without --reasoning uses the provider's default reasoning. Pass --reasoning to set it explicitly.
To add eve to an existing project, pass a path:
cd myapp
npx eve@latest init .
Note The
evepackage includes its full documentation, so coding agents can read it locally fromnode_modules/eve/docs.
The generated project includes an agent directory. Replace agent/instructions.md with:
You are a concise weather demo assistant. Tell users that the weather data is mocked.
Add a mock weather tool at agent/tools/get_weather.ts:
import { defineTool } from "eve/tools";
import { z } from "zod";
export default defineTool({
description: "Return mock weather data for a city.",
inputSchema: z.object({ city: z.string().min(1) }),
async execute({ city }) {
return { city, condition: "Sunny", temperatureF: 72 };
},
});
Choose the model in agent/agent.ts:
import { defineAgent } from "eve";
export default defineAgent({
model: "openai/gpt-6-luna-fast",
reasoning: "high",
});
For a new scaffold, start the agent again:
npm run dev
That's a working agent. Add human-in-the-loop prompts, subagents, and schedules as needed.
From your agent's directory, link a Vercel project and add Web Chat:
npx eve link
npx eve add channel/web
Choose a hosting layout, then Sign in with Vercel to provision authentication for members of the project's team.
You can also select Web Chat from the terminal UI's /add channel picker.
Run npx eve deploy when ready to publish. Local development works without browser sign-in.
See the Web Chat setup guide for permissions and recovery.
The eve community lives on GitHub Discussions, where you can ask questions, share ideas, and show what you've built.
Contributions are welcome. See CONTRIBUTING.md to get the repo running locally and land a change, and use issues and discussions to collaborate. By participating, you agree to our Code of Conduct.
Please do not open public issues for security vulnerabilities. Instead, follow SECURITY.md and report responsibly to responsible.disclosure@vercel.com.
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