VectorLint: Prompt it, Lint it!

VectorLint is a command-line tool that evaluates and scores content using LLMs. It uses LLM-as-a-Judge to catch terminology, technical accuracy, and style issues that require contextual understanding.

Installation

Option 1: Global Installation

Install globally from npm:

npm install -g vectorlint

Verify installation:

vectorlint --help

Option 2: Zero-Install with npx

Run VectorLint without installing:

npx vectorlint path/to/article.md

Enforce Your Style Guide

Define rules as Markdown files with YAML frontmatter to enforce your specific content standards:

• Check SEO Optimization - Verify content follows SEO best practices
• Detect AI-Generated Content - Identify artificial writing patterns
• Verify Technical Accuracy - Catch outdated or incorrect technical information
• Ensure Tone & Voice Consistency - Match content to appropriate tone for your audience

If you can write a prompt for it, you can lint it with VectorLint.

👉 Learn how to create custom rules →

Quality Scores

VectorLint scores your content using error density and a rubric-based system, enabling you to measure quality across documentation. This gives your team a shared understanding of which content needs attention and helps track improvements over time.

• Density-Based Scoring: For errors that can be counted, scores are calculated based on error density (errors per 100 words), making quality assessment fair across documents of any length.
• Rubric-Based Scoring: For more nuanced quality standards, like flow and completeness, scores are graded on a 1-4 rubric system and then normalized to a 1-10 scale.

Quick Start

1. Zero-Config Mode (Fastest)

If you just want to check your content against a style guide:

vectorlint init --quick

This creates a VECTORLINT.md file where you can paste your style guide.

Note: You must set up your credentials in ~/.vectorlint/config.toml (see Step 3) before running checks.

Then run:

vectorlint doc.md

2. Full Configuration

For a comprehensive setup (custom rule packs, specific targets), run:

vectorlint init

This creates:

• VectorLint Config (.vectorlint.ini): Project-specific settings.
• App Config (~/.vectorlint/config.toml): LLM provider API keys.

👉 Full configuration reference →

3. Configure API Keys

Open your global App Config (~/.vectorlint/config.toml) and uncomment the section for your preferred LLM provider (OpenAI, Anthropic, Gemini, or Azure).

[env]
LLM_PROVIDER = "openai"
OPENAI_API_KEY = "sk-..."

Note: You can also use a local .env file in your project, which takes precedence over the global config.

Run a check:

vectorlint doc.md

VectorLint is bundled with a VectorLint preset containing rules for AI pattern detection, directness, and more. The init command configures this automatically.

👉 Learn how to create custom rules →

Contributing

We welcome your contributions! Whether it's adding new rules, fixing bugs, or improving documentation, please check out our Contributing Guidelines to get started.

Resources

• Creating Custom Rules - Write your own quality checks in Markdown
• Configuration Guide - Complete reference for .vectorlint.ini