Introduction

Vow

Trust, verified. Locally.

A local-first AI output verification engine that helps you detect hallucinations, security issues, and quality problems in AI-generated code and text.

What is Vow?

Vow is a high-performance command-line tool that analyzes files, directories, or stdin input to identify potential issues in AI-generated content. It uses a combination of advanced analysis techniques to ensure the reliability and security of AI outputs across 20+ programming languages.

🔒 Privacy-First

All analysis runs locally - no data leaves your machine. Your code and content stay completely private.

⚡ Lightning Fast

Parallel processing engine analyzing 35+ files/sec with optimized HashSet lookups and smart file filtering.

🎯 Accurate Detection

Advanced heuristics with improved false positive handling and precision-tuned detection algorithms.

🔧 Extensible

YAML-based rules system with .vowignore support for project-specific customization.

🏗️ CI/CD Ready

JSON, SARIF, and HTML output formats with detailed performance summaries for automated workflows.

📊 Trust Scoring

Quantified confidence metrics to guide decision-making and review priorities.

How It Works

Vow uses a sophisticated multi-stage analysis pipeline with parallel processing:

  1. Input Processing: Intelligently reads files, directories, or stdin with .vowignore filtering support
  2. AI Content Detection: Identifies likely AI-generated sections using advanced heuristics across 20+ languages
  3. Multi-Analyzer Pipeline:
    • Code analyzer for syntax, API validation, and import verification
    • Text analyzer for factual consistency and hallucination detection
    • Security scanner for dangerous patterns and vulnerabilities
  4. Rule Engine: Applies custom YAML rules for domain-specific requirements
  5. Trust Scoring: Calculates confidence metrics using multiple signals and improved false positive handling
  6. Performance Summary: Provides detailed timing and processing statistics
  7. Output: Structured results in JSON, SARIF, table, or HTML formats

Use Cases

🔍 Software Development

  • Validate AI-generated code before committing to version control
  • Check for hallucinated function calls, imports, or API endpoints
  • Detect security vulnerabilities in generated code
  • Integrate into CI/CD pipelines for automated quality gates

📝 Content Creation

  • Verify factual accuracy in AI-written documentation
  • Check for fabricated references, citations, or sources
  • Validate technical explanations and tutorials for correctness

👥 Code Review

  • Augment human code review with automated AI output verification
  • Flag potentially problematic AI-generated sections
  • Provide trust scores to guide review priorities and focus areas

Quick Install

Get started with Vow in seconds:

curl -sSL https://getvow.dev/install.sh | sh
Get Started

Core Features

🧠 Advanced Analysis

  • Multi-language support: Python, JavaScript, TypeScript, Java, Go, Ruby, C, C++, C#, PHP, Swift, Kotlin, R, Scala, Perl, Lua, Dart, Haskell, MQL5, Rust, Shell
  • Static code analysis to detect hallucinated APIs and imports
  • Text analysis to identify potential fabricated information
  • Security scanning to catch dangerous patterns
  • Custom rule engine for domain-specific checks
  • Improved false positive handling with precision-tuned algorithms

⚡ High Performance

  • Parallel processing with rayon for optimal CPU utilization
  • 35+ files per second analysis speed on typical hardware
  • Optimized data structures with HashSet lookups for fast package verification
  • Smart filtering with .vowignore support to skip unnecessary files
  • Configurable limits for file size, directory depth, and issue count

🛡️ Security & Privacy

  • 100% local processing - no cloud dependencies
  • Open source with transparent algorithms
  • Minimal attack surface with single binary distribution
  • No telemetry or data collection

🚀 Developer Experience

  • Zero configuration to get started
  • Flexible CLI options: --quiet, --verbose, --max-file-size, --max-depth, --max-issues
  • Multiple output formats: JSON, SARIF, table, HTML with performance summaries
  • CI/CD integration with structured JSON output for automated workflows
  • Comprehensive documentation and examples

Ready to verify your AI outputs? Head over to the Installation Guide to get up and running in minutes, or check out the Quick Start for a rapid overview of basic usage.