coaudit: AI-Powered Code Audits with GitHub Copilot CLI

This is a submission for the GitHub Copilot CLI Challenge

What I Built

coaudit is a command-line tool that performs structured code audits on any repository using GitHub Copilot CLI. Instead of implementing static analyzers, it orchestrates Copilot to analyze codebases across 6 critical dimensions:

1. Dead Code – Unused functions, variables, imports, unreachable code
2. Architectural Leaks – Layer violations, cyclic dependencies, improper coupling
3. Selector Fragility – Brittle CSS/DOM selectors prone to breaking with HTML changes
4. Routing Inconsistencies – Mismatched or missing route handlers, parameter naming mismatches
5. Missing Tests – Untested functions, uncovered error paths, integration gaps
6. Observability Gaps – Missing logging, error context, unmonitored operations

How It Works

# Audit any local project
coaudit ~/my-project

# Or audit directly from GitHub
coaudit owner/repo

# Full GitHub URL also works
coaudit https://github.com/owner/repo

The tool:

1. Collects source files from the target repository (multi-language support: JS, TS, Python, PHP, Go, Java, Rust)
2. Loads dimension-specific audit prompts from curated markdown templates
3. Chunks code context intelligently to stay within token limits
4. Invokes GitHub Copilot CLI in batch mode with prompt + context
5. Generates a structured Markdown report with findings across all dimensions

Why This Matters

Code audits typically require:

• Static analyzers – Language-specific, limited to syntactic rules
• Code review tools – Expensive, require human reviewers
• Manual analysis – Time-consuming, inconsistent

coaudit combines the intelligence of Copilot with the automation of batch processing. It provides semantic analysis that static tools can't do, at the speed of automation.

---

Demo

Repository: https://github.com/jonesrussell/coaudit

Quick Start

# Install
npm install
npm start

# Run audit on coaudit itself (meta!)
node bin/coaudit .

# Audit an external GitHub repo
node bin/coaudit facebook/react

Example Output

When you run coaudit on a repository, you get a Markdown report like:

# Copilot Pipeline Audit Report

**Repository:** facebook/react
**Timestamp:** 2026-02-16T01:45:59.842Z

## Summary
| Status | Count |
|--------|-------|
| Completed | 6 |
| Skipped | 0 |
| Errors | 0 |

## Findings

### Dead Code
**Status:** ✅ Completed
- Unused exports in `src/utils.js`
- Unreachable branches in error handling
- Deprecated function still exported...

### Architectural Leaks
**Status:** ✅ Completed
- Direct imports violating layer boundaries
- Cyclic dependency between modules A and B...

### Missing Tests
**Status:** ✅ Completed
- 14 functions with zero test coverage
- Error paths not tested...

Real Copilot Integration

This is not a mock – the tool makes real calls to Copilot CLI in batch mode:

// From src/runner.js
const output = execSync(
  `copilot -p '${prompt + context}' --allow-all --add-dir '${targetDir}'`,
  { encoding: 'utf8', timeout: 180000 }
);

Each audit dimension spawns a full Copilot analysis, giving you genuine semantic insights across your entire codebase.

---

My Experience with GitHub Copilot CLI

Why Copilot CLI Was Essential

Building coaudit was only possible because of Copilot CLI's non-interactive mode (-p flag). Here's why:

Problem: I needed to automate code analysis without manually running Copilot for each repo.

Solution: Copilot CLI's -p, --prompt flag enables batch execution:

copilot -p "analyze this code" --allow-all

This unlocked the entire project. Without it, coaudit would require:

• Manual prompt copying/pasting
• Interactive terminal sessions per repo
• No way to orchestrate 6 sequential analyses

The Development Journey

1. Initial Approach – Started with static analyzer rules. Too limiting – couldn't detect architectural patterns or semantic issues.

2. Pivot to Copilot – Realized Copilot CLI could do semantic analysis. But how to automate it?

3. Discovered Batch Mode – The -p flag was the breakthrough. Suddenly, I could:

   • Pass full code context as a single prompt
   • Run 6 audit dimensions in sequence
   • Parse Copilot's responses into structured reports
   • All without user interaction

4. Real-World Testing – Ran coaudit on itself (meta!). The 6 audit dimensions identified:

   • Architectural issue: Copilot integration logic duplicated in runner.js
   • Test coverage gap: No test framework yet
   • Observability gap: Silent failures in repo cloning
   • Dead code: Unused exports in integration module

These insights came from Copilot, not linters.

Key Features Enabled by Copilot CLI

Feature	Why It Works
Semantic Analysis	Copilot understands code intent, not just syntax
Multi-Language	One prompt works for JS, Python, PHP, Go, Java, Rust
Contextual	Can analyze architectural patterns across files
Extensible	Adding audit dimensions is just adding a markdown prompt
Batch Processing	Non-interactive mode enables automation

What I Learned

• Copilot CLI is a powerful automation engine – Not just for chat, but for building agentic workflows
• Prompts-as-code is elegant – Audit rules live in markdown, easy to version and modify
• Context windows are the lever – Intelligently chunking code context is more important than prompt engineering
• Batch mode is underrated – The -p flag transforms Copilot from interactive tool to orchestration platform

Challenges & Solutions

Challenge: Large codebases exceed token limits
Solution: Implemented smart chunking – limit context to 50KB per audit dimension, prioritize relevant files

Challenge: Copilot takes 30-180 seconds per dimension
Solution: Added progress indicators and timeout handling; parallel audits planned for v1

Challenge: Structuring Copilot's free-text output
Solution: Request JSON format in prompts; parse responses programmatically

The Meta Moment

I ran coaudit on coaudit itself. Copilot found legitimate issues that I missed:

• Unused exports in copilot-integration.js
• Architectural leak: Should use dedicated integration module instead of duplicating logic in runner.js
• Missing tests and observability logging

This validated the tool's value – even the author benefits from automated analysis.

---

Why coaudit Matters for Teams

1. Speed – Get insights from a full codebase audit in minutes, not days
2. Consistency – Same audit rules applied to every dimension
3. Scale – Works on any size repo, any language
4. Feedback Loop – Iterate on audit prompts to improve analysis
5. Learning – Copilot's findings teach you architectural patterns you might miss

What's Next

• Real-time audit feedback in GitHub PR comments
• Configurable audit dimensions via .copilot-audit.json
• JSON/HTML report formats for CI/CD integration
• Severity levels and risk scoring
• Parallel dimension audits for faster results

---

Thanks to GitHub Copilot CLI

This project wouldn't exist without the -p batch execution mode. Copilot CLI transformed from a chat interface into a powerful automation platform. Excited to see what else the community builds!

Try coaudit: https://github.com/jonesrussell/coaudit

---

Have thoughts on code auditing or Copilot CLI? Drop a comment below!