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 content quality issues that typically require human judgement.

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• Verify Technical Accuracy - Catch outdated or incorrect technical information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 subjective 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. Create Your First Rule:

   Create a directory named VectorLint and add a file grammar.md inside it:

   ---
   evaluator: base
   id: GrammarChecker
   description: Grammar Checker
   severity: error
   ---
   Check this content for grammar issues, spelling errors, and punctuation mistakes.

2. Configure VectorLint:

   Create a vectorlint.ini configuration file in your project root:

   # vectorlint.ini
   RulesPath=.
       
   # Run the "VectorLint" rule pack on all markdown files
   [**/*.md]
   RunRules=VectorLint

   👉 Full configuration reference →

3. Set An LLM Provider:

   Create a .env file in your project root with your API keys:

   # OpenAI (Default)
   OPENAI_API_KEY=sk-...
   LLM_PROVIDER=openai
   
   # - OR -
       
   # Anthropic
   ANTHROPIC_API_KEY=sk-ant-...
   LLM_PROVIDER=anthropic

4. Run a check:

   vectorlint path/to/article.md

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