commit abc1234
Author: Mayuresh Shitole
Date: Mon Feb 3
fixed bug

commit def5678
Author: Mayuresh Shitole
Date: Sun Feb 2
update

This is a submission for the GitHub Copilot CLI Challenge

What I Built

Have you ever looked at git log and thought, "This tells me nothing about my project’s journey"?

commit abc1234
Author: Mayuresh Shitole
Date: Mon Feb 3
fixed bug

commit def5678
Author: Mayuresh Shitole
Date: Sun Feb 2
update

Boring, right? Every repository has an incredible story hidden in its commits - the late-night breakthroughs, the major refactors, the "aha!" moments. But git logs don’t capture that narrative.

That’s why I built Terminal Time Machine - a CLI tool that transforms your git history into engaging stories with beautiful ASCII visualizations.

🎯 What It Does

Terminal Time Machine (ttm) analyzes your git repository and generates:

📖 Narrative Stories - Your commits become chapters in an epic tale:

═══════════════════════════════════════════════════
Chapter 2: The Great Refactoring
February 2026
═══════════════════════════════════════════════════

As the project matured, the team faced a critical decision.
The monolithic architecture that served us well in early days
now threatened to slow us down.

Over 23 commits across 8 intense days, the codebase was
reimagined. Sarah led the database migration effort, while
the team rallied around backward compatibility...

🎨 ASCII Timelines - Visual representations of your history:

2025  │
Jan   ├─●─────●──────────────●─ Project inception
│ │     │              └─ First working prototype
│ │     └─ Core architecture decided
│ └─ Initial commit "Hello, World!"
│
Feb   ├───────●──────●─────────● Major refactor begins
│       │      │         └─ Tests: 45% → 78%
│       │      └─ Database layer complete
│       └─ API endpoints redesigned
│
Mar   ├─●─────────●───────────── v1.0 Released! 🎉

👥 Contributor Spotlights - Beautiful analysis of who built what:

╔════════════════════════════════════════════════╗
║  CONTRIBUTOR SPOTLIGHT                        ║
╚════════════════════════════════════════════════╝

📊 Statistics:
• 234 commits (42% of total)
• 12,847 lines added
• Most active: February-March 2025
• Top expertise: Backend architecture

🔥 Activity Heatmap:
Jan  ████████░░░░░░░░
Feb  ████████████████
Mar  ████████░░░░░░░░
Apr  ████░░░░░░░░░░░░

⚡ Smart Features:

• 🎯 Milestone Detection - Automatically identifies releases, refactors, and key moments
• 📝 Release Notes Generator - Professional changelogs in seconds
• 💾 Multiple Export Formats - Markdown, HTML, JSON
• 🎨 Color Themes - Classic, Hacker, Sunset, Ocean
• 📊 Repository Statistics - Comprehensive analytics

💡 Why This Matters

As a developer and founder at Ambicube Limited in the UK, I’ve seen how important it is to communicate technical work to non-technical stakeholders. Git logs are great for developers, but they don’t tell the story of what we’ve built.

Terminal Time Machine bridges that gap. It helps:

• Teams onboard new members by showing project evolution
• Managers understand velocity and contribution patterns
• Maintainers generate beautiful release notes automatically
• Everyone appreciate the journey of building software

This tool turns technical data into human stories.

---

Demo

🎬 See It In Action

📦 Try It Yourself

# Install globally
npm install -g terminal-time-machine

# Navigate to any git repository
cd your-project

# Generate your story
ttm story

# Show timeline
ttm timeline

# Analyze contributors
ttm contributors

# Generate release notes
ttm release-notes v1.0.0..v2.0.0

🔗 Links

• npm Package: https://www.npmjs.com/package/terminal-time-machine
• GitHub Repository: https://github.com/mayureshsmitasuresh/terminal-time-machine
• Documentation: README.md

📸 Screenshots

Story Mode Output: ![Story Generation]

Narrative generation showing project evolution

My Experience with GitHub Copilot CLI

GitHub Copilot CLI was absolutely transformative for this project. As a solo developer working on this challenge, having an AI pair programmer available 24/7 made the difference between "good idea" and "shipped product."

🏗️ 1. Architecting the Core Story Generator

The Challenge: I needed to transform raw git commit data into coherent narrative text. How do you group commits into logical "chapters"? How do you identify meaningful patterns?

What I Did:

gh copilot suggest "What's the best approach to analyze git commits
and group them into logical chapters for a narrative story generator?"

Copilot’s Response: It suggested three key strategies:

1. Time-based clustering - Group by weeks/months
2. Semantic analysis - Analyze commit messages for themes
3. File-based grouping - Commits affecting similar files

This became the foundation of my commit-analyzer.js module. Copilot then helped me implement each strategy:

gh copilot suggest "Write a JavaScript function that groups git commits
by semantic similarity using commit message analysis"

Impact: What could have taken 3-4 days of research and experimentation took 6 hours. Copilot CLI helped me understand NLP approaches I’d never used before.

---

🐛 2. Debugging the "enrichedCommits" Error

The Bug: My code kept throwing "Cannot access 'enrichedCommits' before initialization" - a JavaScript temporal dead zone error.

What I Did:

gh copilot explain "Why am I getting 'Cannot access enrichedCommits
before initialization' in this async function?"

Then pasted my problematic code.

Copilot’s Analysis: It immediately identified that I was using the variable before declaring it due to incorrect async/await ordering. It showed me the exact line and explained the fix.

Impact: Debugged in 5 minutes instead of potentially hours. The explanation also taught me about JavaScript’s temporal dead zone, making me a better developer.

---

🎨 3. Creating ASCII Art Visualizations

The Challenge: I wanted beautiful ASCII timelines but had zero experience creating them.

What I Did:

gh copilot suggest "Create a Node.js function that generates an ASCII
timeline from an array of git commits with dates and descriptions"

Copilot’s Output: It generated a complete working implementation using Unicode box-drawing characters. I then iterated:

gh copilot suggest "How can I add branch points and merge indicators
to this ASCII timeline using Unicode characters?"

This led to the branching visualizations you see in the tool.

Impact: Went from "I have no idea how to do this" to a working, beautiful visualization in under an hour.

---

💡 4. Feature Ideation

Some of my best features came from asking Copilot "what if" questions:

gh copilot suggest "What are creative ways to visualize contributor
activity patterns in a terminal application?"

Result: Copilot suggested:

• Activity heatmaps (implemented! ✅)
• Contribution streaks (implemented! ✅)
• Time-of-day analysis (on roadmap)
• Collaboration graphs (future feature)

Impact: Added features I hadn’t even thought of. The contributor spotlight feature was directly inspired by this conversation.

---

🧪 5. Writing Tests

The Challenge: Testing git operations is complex - how do you mock git commands?

What I Did:

gh copilot suggest "How do I write unit tests for a function that
parses git log output without actually running git commands?"

Copilot’s Guidance: It explained:

• Using test fixtures (sample git output)
• Mocking the simple-git library
• Structuring tests for async operations

Then it generated example test cases I could adapt.

Impact: Got from 0% to 85% test coverage in one day. Would have taken 3-4 days without Copilot’s help.

---

🚀 6. Performance Optimization

The Problem: Processing 10,000+ commits was taking minutes.

What I Did:

gh copilot suggest "How can I optimize this Node.js code that processes
large arrays of git commits? Current implementation is too slow"

Copilot’s Suggestions:

• Streaming instead of loading everything into memory
• Lazy loading for enriched commit data
• Caching frequently accessed data
• Using Promise.all() for parallel processing

Impact: 10x performance improvement. The tool now handles massive repos like the Linux kernel gracefully.

---

📝 7. Documentation Generation

The Challenge: Writing comprehensive documentation is time-consuming.

What I Did:

gh copilot suggest "Generate comprehensive CLI usage documentation
for a tool with these commands: story, timeline, contributors,
release-notes, export, stats"

Result: Copilot created a well-structured documentation template with:

• Clear command descriptions
• Usage examples
• Common use cases
• Troubleshooting tips

I refined and personalized it, but the foundation saved hours of work.

Impact: Professional documentation completed in 2 hours instead of a full day.

---

🎯 Overall Impact of GitHub Copilot CLI

Time Saved: Estimated 2-3 weeks of development time

Quality Improved:

• Better architecture (learned new patterns)
• More features (ideas I wouldn’t have thought of)
• Higher test coverage (85% vs. my usual 60%)
• Better performance (learned optimization techniques)

Learning Accelerated:

• Discovered NLP techniques
• Learned advanced async/await patterns
• Understood Unicode box-drawing
• Improved testing practices

Confidence Boosted: I tackled complex problems I’d normally avoid because I had an expert available to guide me through them.

💬 The Conversational Difference

What made Copilot CLI special wasn’t just code generation - it was the conversation. Instead of:

1. Google search
2. Read Stack Overflow
3. Try solution
4. Fail
5. Repeat

I could just ask about my specific problem and get tailored guidance. It felt like pair programming with a senior developer who’s always available, never judgmental, and infinitely patient.

---

Technical Highlights

🛠️ Built With

• Node.js - Runtime environment
• Commander.js - CLI framework
• simple-git - Git operations
• chalk & gradient-string - Beautiful terminal colors
• boxen & cli-table3 - Elegant formatting
• inquirer - Interactive prompts
• ora - Loading spinners
• marked & marked-terminal - Markdown rendering
• asciichart - ASCII charts
• figlet - ASCII art text

📊 Project Stats

• Lines of Code: ~2,800
• Development Time: 10 days
• Test Coverage: 85%
• npm Downloads: [Growing!]
• GitHub Stars: [Give me one! ⭐]

🎨 Key Features Implementation

1. Smart Commit Analysis

// Groups commits by semantic similarity
// Detects patterns in file changes
// Identifies refactoring vs. new features

2. Milestone Detection

• First commit detection
• Version tag parsing (semantic versioning)
• Major refactor identification (high churn)
• Documentation update recognition
• Test coverage improvements

3. Beautiful Output

• 4 color themes (Classic, Hacker, Sunset, Ocean)
• Responsive terminal width detection
• Unicode support with ASCII fallbacks
• Progress indicators for long operations

---

What’s Next

I’m planning to add:

• 🤖 AI-powered commit quality scoring - Analyze commit message quality
• 📊 More visualization types - Dependency graphs, code churn heatmaps
• 🌐 Web version - Interactive timeline in the browser
• 🔌 GitHub/GitLab integration - Include issues and PRs in the story
• 🎤 Audio narration - Hear your git story read aloud
• 📱 Mobile companion app - View stories on mobile
• 🎓 Learning mode - Analyze successful open-source projects

---

Try It Today! 🚀

# Install
npm install -g terminal-time-machine

# Use it
cd your-favorite-project
ttm story

Links:

• 📦 npm: https://www.npmjs.com/package/terminal-time-machine
• 💻 GitHub: https://github.com/mayureshsmitasuresh/terminal-time-machine
• ⭐ Star it if you like it!
• 🐛 Report bugs or request features
• 💬 Share your git stories - I’d love to see them!

---

About Me

I’m Mayuresh Shitole, a solo founder at Ambicube Limited UK in the UK. I love building tools that make developers’ lives easier and help teams communicate better about technical work.

This project combines my passion for storytelling, developer tools, and beautiful terminal UIs. I believe every codebase has a story worth telling.

Connect with me:

• 📧 Email: mayureshshitole@gmail.com
• 💼 GitHub: @mayureshshitole
• 🏢 Company: Ambicube Limited, UK

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Acknowledgments

Huge thanks to:

• GitHub for sponsoring this challenge and building Copilot CLI
• DEV Community for providing this amazing platform
• You for reading this far! 🙏

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Final Thoughts

Building Terminal Time Machine taught me that the best tools solve problems people didn’t know they had. Everyone accepts that git logs are boring - but they don’t have to be!

GitHub Copilot CLI was instrumental in turning this idea into reality. It wasn’t just about writing code faster - it was about:

• Learning new techniques
• Exploring ideas I’d normally avoid
• Shipping a polished product
• Having fun while building

If you’ve ever wanted to see your git history come alive, give Terminal Time Machine a try. And if you’re participating in hackathons or challenges, definitely use Copilot CLI - it’s like having a senior developer on your team who never sleeps.

May your commits be meaningful and your git history epic! 🕰️✨