GitHub Webhook with DevTunnel

Quick setup for testing GitHub webhooks locally using Microsoft DevTunnel.

Quick Start

Automated Setup (Recommended)

The fastest way to get started is using the automated setup script:

1. Setup Environment

   cp .env.sample .env

   Edit .env and set your GITHUB_WEBHOOK_SECRET (generate one with openssl rand -hex 32)

2. Run the Setup Script

   ./scripts/dev-setup.sh https://github.com/owner/repo

   This single command will:

   • Start DevTunnel automatically
   • Launch the webhook server
   • Create a GitHub webhook configured for issues events
   • Display the webhook URL and status

   Press Ctrl+C to stop both services when done.

Prerequisites:

• GitHub CLI (gh) installed and authenticated (gh auth login)
• .env file with GITHUB_WEBHOOK_SECRET configured

Supported repository URL formats:

• https://github.com/owner/repo
• git@github.com:owner/repo.git
• owner/repo

Manual Setup

If you prefer to run each component separately:

1. Setup Environment

   cp .env.sample .env

   Edit .env and set your GITHUB_WEBHOOK_SECRET (generate one with openssl rand -hex 32)

   Optional: Enable Repository Cloning

   CLONE_REPOS=true                    # Enable auto-cloning (default: false)
   CLONE_BASE_DIR=./repos              # Base directory (default: ./repos)
   CLONE_UPDATE_EXISTING=false         # Pull updates if exists (default: false)

   Note: Repository cloning requires the gh CLI to be installed and authenticated (gh auth login)

2. Start DevTunnel

   ./scripts/start-devtunnel.sh

   Copy the DevTunnel URL from the output (e.g., https://xxxxx.devtunnels.ms)

3. Start Webhook Server

   uv run src/webhook.py

4. Configure GitHub Webhook

   • Go to your repository settings → Webhooks → Add webhook
   • Payload URL: https://your-devtunnel-url.devtunnels.ms/webhook
   • Content type: application/json
   • Secret: Use the same secret from your .env file
   • Events: Select "Issues"
   • Save webhook

The webhook will print issue details to the console when issues are created or updated. If CLONE_REPOS=true, it will also automatically clone the repository locally.

Complete SDLC Automation (SDLC)

SDLC is a complete software development lifecycle automation tool that orchestrates the entire feature development workflow from planning to pull request creation:

# Automate complete feature development
./src/sdlc.py "add support for pull request events"

# Or use via uv
uv run src/sdlc.py "add timestamp logging to webhook events"

SDLC executes multiple Copilot prompts in sequence, managing context between stages and logging all activities. The workflow orchestrates: feature planning → branch creation → implementation → documentation → pull request.

How It Works:

1. Feature planning: Creates a feature spec based on your description
2. Branch creation: Creates a git branch for the feature
3. Implementation: Implements the feature code
4. Documentation: Updates README and GitHub instructions
5. Pull request: Creates a GitHub pull request

Each stage logs its command and output to a timestamped markdown file for audit trail and debugging.

Prerequisites:

• GitHub Copilot CLI installed and authenticated
• Python 3.12 or higher
• Git repository initialized locally

AI Developer Inner-Loop (ADIL)

ADIL is a command-line utility that integrates GitHub Copilot CLI into your development workflow. It automatically loads project context and helps with development tasks:

# Get help with implementing a feature
./src/adil.py "add support for pull request events"

# Or use via uv
uv run src/adil.py "fix the webhook signature verification"

ADIL combines your prompt with project context from docs/prime.md and invokes Copilot with automation enabled. This accelerates the development loop by eliminating manual context setup.

Prerequisites:

• GitHub Copilot CLI installed and authenticated
• Python 3.12 or higher

Koozie ASCII Art

Display "koozie" in fun ASCII art format:

./src/koozie.py

Or via uv:

uv run src/koozie.py

This lightweight utility showcases the project's playful side and can be integrated into welcome messages or project documentation.

Testing

Run the integration test suite to verify the webhook server works correctly:

# Run all tests
uv run pytest

# Run tests with verbose output
uv run pytest -v

# Run tests with even more verbose output
uv run pytest -vv

# Run specific test file
uv run pytest tests/test_webhook_integration.py -v

# Run specific test
uv run pytest tests/test_webhook_integration.py::test_valid_webhook_with_correct_signature -v

The tests are integration tests that start the actual webhook server as a subprocess and send real HTTP requests to validate behavior. No external services or real GitHub credentials are needed - tests run completely offline and use mock payloads with test secrets.