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Set up VectorLint and run your first content evaluation in under ten minutes. You install VectorLint, add your style instructions, connect an LLM (Large Language Model) provider, and see real output on a file you own.

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Before you begin

VectorLint requires Node.js 18 or later. Node.js 22 LTS is recommended. If you need to install or update Node.js, use nvm or download directly from nodejs.org. You will also need an API key for a supported LLM provider. VectorLint sends your content to the provider you configure for evaluation. Supported providers include: OpenAI, Anthropic, Google Gemini, Azure OpenAI, Amazon Bedrock.
VectorLint requires a configured LLM provider to produce output. Installing the package alone is not enough — if you skip provider configuration, running vectorlint against a file will return no results and no error. Complete Step 2 before running a check.

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Step 1: Install VectorLint

Install VectorLint globally from npm: 
npm install -g vectorlint
Verify the installation: 
vectorlint --help
You can also run VectorLint without installing it using npx vectorlint. See Installation for details on both options.

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Step 2: Configure your LLM provider

Open ~/.vectorlint/config.toml and add your provider and API key. This file is your global provider configuration and applies to all projects on your machine. For OpenAI: 
[env]
LLM_PROVIDER = "openai"
OPENAI_API_KEY = "sk-..."
For Anthropic: 
[env]
LLM_PROVIDER = "anthropic"
ANTHROPIC_API_KEY = "sk-ant-..."
You can also set provider values in a .env file in your project root. Project-level values take precedence over config.toml. For all supported providers and configuration options, see Configuring LLM providers.

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Step 3: Create your VECTORLINT.md

After you initialize VectorLint in your repository, the application generates a VECTORLINT.md file in your project root. After you copy your style standards as plain-language instructions into the file, VectorLint builds a “Style Guide Compliance” rule and applies it to your VectorLint evaluations. Run the quick-init command to create the file: 
npx vectorlint init --quick
Then open VECTORLINT.md and add your standards. A few clear instructions are enough to get meaningful output: 
## Voice and tone

- Write in second person. Address the reader as "you."
- Use active voice. Avoid passive constructions.
- Be direct. Remove filler phrases like "it is important to note that."

## Terminology

- Use "sign in" not "log in."
- Use "select" not "click" for UI actions.
- Avoid "easy," "simple," and "just" — these are subjective and dismissive.

## Sentence structure

- Keep sentences under 25 words.
- One idea per sentence.
- Spell out acronyms on first use.
You don’t need a comprehensive style guide to start. Add rules incrementally as you learn what your rules catch and what they miss.

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Step 4: Run a check

Point VectorLint at any Markdown file in your project: 
vectorlint path/to/doc.md
VectorLint reads your VECTORLINT.md, evaluates the file against it, and prints findings in your terminal. If the file is clean, VectorLint produces no output and exits with status 0. If the file has violations, VectorLint prints each finding with its location and a suggested fix.

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Next steps