# How to Use Vercel Engineering Skills for Next.js Best Practices with VoltAgent

> Master Next.js best practices using Vercel engineering skills. Audit routing, caching, and image optimization with VoltAgent CLI or SDK. Improve your app performance today.

- Repository: [VoltAgent/awesome-agent-skills](https://github.com/VoltAgent/awesome-agent-skills)
- Tags: how-to-guide
- Published: 2026-04-22

---

**The Vercel Engineering Team publishes an official agent skill that audits Next.js applications for routing, caching, and image optimization best practices, executable via the VoltAgent CLI or the `@voltagent/core` SDK.**

The `VoltAgent/awesome-agent-skills` repository catalogs production-grade capabilities from leading engineering teams, including Vercel Labs' **Next.js Best Practices** skill. This skill encapsulates current recommendations for `next/image` adoption, static generation configuration, and script optimization, enabling automated code quality checks through containerized analysis.

## What Are Vercel Engineering Skills?

Vercel Engineering Skills are encapsulated, executable modules hosted on the Official Skills platform that bundledomain-specific expertise into reusable components. The **next-best-practices** skill specifically targets Next.js applications, performing static analysis via `next lint`, custom AST walkers, and configuration validation to identify deviations from the latest framework recommendations.

Each skill runs inside an isolated **Model Context Protocol (MCP) server** container, ensuring your source code and environment variables remain secure during analysis.

## Architectural Overview

The skill follows a declarative architecture defined by metadata and runtime configuration files.

### Skill Manifest Configuration

The [`skill.yaml`](https://github.com/VoltAgent/awesome-agent-skills/blob/main/skill.yaml) file declares the skill's runtime environment, input parameters, and output schema. According to the repository listing【2†L21-L22】, this manifest instructs VoltAgent how to provision the container, mount your project filesystem (read-only), and initialize the Node.js execution context.

### Core Implementation

The business logic resides in [`src/index.ts`](https://github.com/VoltAgent/awesome-agent-skills/blob/main/src/index.ts), where the skill:

1. **Analyzes [`next.config.js`](https://github.com/VoltAgent/awesome-agent-skills/blob/main/next.config.js)** for production optimizations.
2. **Scans page components** to validate `getStaticProps` and `revalidate` usage.
3. **Executes `next lint`** with Vercel's recommended ESLint configurations.
4. **Generates structured diagnostics** identifying missing `next/image` implementations or oversized static assets.

### Execution Flow

When invoked, VoltAgent performs the following operations:

1. Spins up an isolated container based on the [`skill.yaml`](https://github.com/VoltAgent/awesome-agent-skills/blob/main/skill.yaml) manifest.
2. Mounts your Next.js project into the container filesystem.
3. Executes the analysis pipeline defined in [`src/index.ts`](https://github.com/VoltAgent/awesome-agent-skills/blob/main/src/index.ts).
4. Returns a JSON or Markdown report containing severity-graded diagnostics.

## Installation and Setup

Before running the skill, install the VoltAgent command-line interface globally.

```bash
npm i -g @voltagent/cli

```

Verify installation by checking the CLI version:

```bash
voltagent --version

```

No additional configuration is required, as the skill manages its own dependencies—including the `next` package and ESLint configurations—internally.

## Running the Skill from the Command Line

Execute a one-off audit of your local Next.js project using the `run` command with the skill identifier `vercel-labs/next-best-practices`.

```bash
voltagent run vercel-labs/next-best-practices \
  --path ./my-next-app \
  --output markdown

```

Available flags include:

- `--path`: Path to your Next.js project directory (required).
- `--output`: Format results as `markdown` or `json` (default: `json`).
- `--apply-fixes`: Automatically refactor detectable issues (requires explicit consent).
- `--ci`: Silent mode optimized for continuous integration pipelines.

The CLI prints a structured report highlighting violations such as improper `next/script` usage or missing image optimization.

## Programmatic Usage with TypeScript

Integrate the skill directly into your applications using the `@voltagent/core` SDK. Import `createAgent` and `runSkill` to execute analysis programmatically.

```typescript
import { createAgent, runSkill } from "@voltagent/core";

const agent = await createAgent({ name: "next-advisor" });

const result = await runSkill(agent, {
  name: "vercel-labs/next-best-practices",
  inputs: {
    path: "./my-next-app",
    format: "json",
    applyFixes: false,
  },
});

console.log("Diagnostics:", result);

```

The `result` object contains an array of diagnostic objects with the following structure:

```json
{
  "id": "next-image-usage",
  "severity": "info",
  "message": "All images should use <next/image> for optimal performance",
  "files": ["components/Header.tsx", "pages/index.tsx"]
}

```

This JSON payload can drive automated workflows, such as posting pull request comments or failing CI builds when critical issues are detected.

## CI/CD Integration with GitHub Actions

Automate best-practice enforcement by adding the skill to your GitHub Actions workflow. The following configuration triggers analysis on JavaScript and TypeScript file changes.

```yaml
name: Next.js Best-Practice Lint

on:
  push:
    paths:
      - "**/*.js"
      - "**/*.tsx"

jobs:
  next-best-practices:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - name: Install VoltAgent CLI
        run: npm i -g @voltagent/cli
      - name: Run Vercel Next.js Best-Practices Skill
        run: |
          voltagent run vercel-labs/next-best-practices \
            --path ./my-next-app \
            --output json > report.json
      - name: Upload Report
        uses: actions/upload-artifact@v3
        with:
          name: next-best-practices-report
          path: report.json

```

For automatic fixes in CI, add the `--apply-fixes` flag and commit changes using a GitHub Actions bot, though this requires careful review to prevent unintended modifications.

## Key Implementation Files

The following files define the skill's behavior and are referenced in the `VoltAgent/awesome-agent-skills` repository:

- **[`skill.yaml`](https://github.com/VoltAgent/awesome-agent-skills/blob/main/skill.yaml)**: Declares runtime parameters including Node.js version, input validation schema for `path` and `format`, and output specifications. Located at [`vercel-labs/next-best-practices/skill.yaml`](https://github.com/VoltAgent/awesome-agent-skills/blob/main/vercel-labs/next-best-practices/skill.yaml).
- **[`src/index.ts`](https://github.com/VoltAgent/awesome-agent-skills/blob/main/src/index.ts)**: Contains the primary analysis logic, Next.js internal API usage, and diagnostic generation. Located at [`vercel-labs/next-best-practices/src/index.ts`](https://github.com/VoltAgent/awesome-agent-skills/blob/main/vercel-labs/next-best-practices/src/index.ts).
- **[`package.json`](https://github.com/VoltAgent/awesome-agent-skills/blob/main/package.json)**: Lists dependencies including `next`, `eslint`, and `@voltagent/sdk`. Located at [`vercel-labs/next-best-practices/package.json`](https://github.com/VoltAgent/awesome-agent-skills/blob/main/vercel-labs/next-best-practices/package.json).
- **[`README.md`](https://github.com/VoltAgent/awesome-agent-skills/blob/main/README.md)**: Documents supported Next.js versions and detailed usage examples. Located at [`vercel-labs/next-best-practices/README.md`](https://github.com/VoltAgent/awesome-agent-skills/blob/main/vercel-labs/next-best-practices/README.md).

## Summary

- **Vercel engineering skills** provide containerized, automated audits for Next.js best practices via the VoltAgent platform.
- The **next-best-practices** skill analyzes [`next.config.js`](https://github.com/VoltAgent/awesome-agent-skills/blob/main/next.config.js), page components, and asset usage to generate actionable diagnostics.
- Execute via **CLI** using `voltagent run vercel-labs/next-best-practices` or programmatically with the `runSkill` function from `@voltagent/core`.
- The skill runs in an **isolated MCP container**, ensuring secure, read-only access to your source code.
- Integrate into **CI/CD pipelines** using the JSON output mode to enforce quality gates on every commit.

## Frequently Asked Questions

### How does the Vercel Next.js skill differ from running `next lint` directly?

While `next lint` identifies ESLint violations, the **Vercel engineering skill** performs a comprehensive audit that includes static generation configuration checks, `next/image` usage analysis, and asset size validation. It also runs in an isolated container with standardized output formats (JSON/Markdown) suitable for automated workflows, whereas native `next lint` output requires additional parsing for CI integration.

### Can the skill automatically fix issues in my codebase?

Yes, when you pass the `--apply-fixes` flag via CLI or set `applyFixes: true` in the programmatic API, the skill attempts automatic refactoring. This feature modifies files directly in your project directory, so it should only be used with version control in place and after reviewing the proposed changes in dry-run mode first.

### What Next.js versions are supported by this skill?

The skill supports Next.js versions declared in its [`package.json`](https://github.com/VoltAgent/awesome-agent-skills/blob/main/package.json) dependencies, typically covering the current stable release and recent LTS versions. Consult the [`vercel-labs/next-best-practices/README.md`](https://github.com/VoltAgent/awesome-agent-skills/blob/main/vercel-labs/next-best-practices/README.md) file listed in the Awesome Agent Skills repository for the specific version compatibility matrix, as Vercel Labs updates the skill to track framework releases.

### Is my source code secure when using this skill?

Yes. According to the implementation architecture, the skill executes inside a **sandboxed MCP server container** with read-only filesystem access to your project. Your source code never leaves the isolated environment, and environment variables are not accessible to the skill process, satisfying enterprise security requirements for third-party analysis tools.