Live Streaming Output

#!/usr/bin/env -S ai --sonnet --skip --live
Explore this repository and write a short summary of what it does,
its key features, and how to get started. Print your findings as you go.
Finally, generate a concise report in markdown format.

--live

./script.md
# (silence for 30 seconds)
# Then all output appears at once

./script.md
# (starts streaming immediately)
I'll explore the repository structure...
Found a Node.js project with TypeScript...
Looking at package.json to identify dependencies...
Now examining the main entry point...
# (output continues in real-time)

# Make it executable
chmod +x live-report.md

# Run it
./live-report.md

[AI Runner] Using: Claude Code + Claude Pro
[AI Runner] Model: Sonnet 5

I'll start by exploring the repository structure to understand the project.

This appears to be a Node.js project with TypeScript. I can see:
- Package.json indicating it's called "airun" 
- TypeScript configuration files
- A src/ directory with the main source code

Let me examine the key files to understand what it does...

(output continues streaming)

./live-report.md > report.md

[AI Runner] Using: Claude Code + Claude Pro
[AI Runner] Model: Sonnet 5

I'll explore the repository structure and key files...
Now let me look at the core scripts and provider structure.
Here's my report:
[AI Runner] Done (70 lines written)

# AIRun Project Summary

## Overview
AIRun is a tool for running AI prompts like programs...

## Key Features
- Executable markdown with shebang support
- Cross-cloud provider switching
- Unix pipe support
...

# Use Opus for deeper analysis
ai --opus live-report.md

# Use AWS Bedrock
ai --aws --sonnet live-report.md

# Use local Ollama
ai --ollama live-report.md

ai --quiet live-report.md > report.md

#!/usr/bin/env -S ai --sonnet --skip --live
Explore this repository and generate a comprehensive README.md:

1. Project overview and purpose
2. Installation instructions
3. Usage examples
4. API documentation
5. Contributing guidelines

Print a status update after examining each major directory.
Finally, output the complete README in markdown format.

chmod +x generate-readme.md
./generate-readme.md > README.md

#!/usr/bin/env -S ai --sonnet --skip --live
Create an onboarding guide for new developers:

1. Describe the codebase structure
2. Explain the development workflow
3. List the key technologies used
4. Identify the most important files to read first
5. Suggest a learning path

Narrate your exploration as you go through the codebase.
Finally, generate a structured onboarding document.

#!/usr/bin/env -S ai --opus --skip --live
Perform a security audit of this codebase:

1. Check for common vulnerabilities (OWASP Top 10)
2. Review authentication and authorization
3. Examine data validation
4. Check for exposed secrets or credentials
5. Review dependencies for known vulnerabilities

Report findings as you examine each area.
Finally, generate a prioritized security report.

#!/usr/bin/env -S ai --sonnet --skip --live
Run the full test suite including integration tests.

Print a status update after each test file completes:
- File name
- Pass/fail count
- Time taken

At the end, provide a summary with:
- Total pass/fail counts
- Slowest tests
- Root cause analysis for failures

#!/usr/bin/env -S ai --skip --chrome --live
Test the user registration flow:

1. Navigate to the signup page
2. Fill in the registration form
3. Submit and verify email sent
4. Follow email link to activate account
5. Login with new credentials

Narrate each step as you complete it.
Report any issues found.

chmod +x test-signup.md
./test-signup.md

Navigating to https://app.example.com/signup...
Filling in the registration form...
Submitting the form...
Checking for success message...
✓ Registration successful
Looking for confirmation email...

./live-report.md > report.md

./live-report.md > report.md 2>&1

./live-report.md > /dev/null

./live-report.md > report.md 2> progress.log

# macOS
brew install jq

# Ubuntu/Debian
sudo apt install jq

# Fedora
sudo dnf install jq

ai --live --quiet script.md > output.txt

#!/usr/bin/env -S ai --live --skip
---
vars:
  target: "authentication"
---
Audit the {{target}} system. Print findings as you discover them.

./audit.md --target "payment processing"

# Script has --live in shebang, override provider from CLI
ai --aws --opus script.md

- Explore this repository and write a summary.
+ Explore this repository. Print your findings as you go.
+ Finally, write a summary.

which jq

brew install jq  # macOS
sudo apt install jq  # Linux

#!/usr/bin/env -S ai --live --skip
Explore the repo. Print findings as you go.

Finally, generate a report in markdown format:
# Report Title
...