A UK-based developer has built a CLI tool that transforms git commit histories into narrative stories with ASCII visualizations, entering it in GitHub's Copilot CLI Challenge.
Terminal Time Machine (ttm) analyzes repository history and generates three outputs: narrative chapters that frame commits as project milestones, ASCII timelines showing activity patterns, and contributor analytics with heatmaps. The tool exports to markdown, HTML, and JSON.
The creator, Mayuresh Shitole from Ambicube Limited, positions it as a communication bridge. "Git logs are great for developers, but they don't tell the story of what we've built," he notes. The use case: onboarding teams, explaining velocity to managers, generating release notes.
The implementation leans heavily on GitHub Copilot CLI. Shitole describes using gh copilot suggest to architect the core story generator, which clusters commits by time, semantics, and affected files. The tool is available on npm as terminal-time-machine.
Context matters here. GitHub launched the Copilot CLI Challenge on January 22, closing February 15 (11:59 PM PST). Three winners get $1,000 plus GitHub Universe 2026 tickets; 25 runners-up receive one-year Copilot Pro+ subscriptions. Judging criteria: Copilot CLI usage, UX, and creativity. Teams up to four people allowed.
The challenge tests whether Copilot CLI - GitHub's terminal-based AI coding assistant - delivers on enterprise promises like GDPR compliance and security filters that block public code matches over 65 lexemes. Early submissions like this one showcase practical productivity gains.
Trade-offs are visible. The tool's narrative generation depends on commit message quality. Projects with messages like "fixed bug" and "update" won't produce compelling stories - garbage in, garbage out. The ASCII visualizations look sharp in demos but may not scale to large monorepos with thousands of commits.
Worth watching: whether enterprise teams adopt tools like this for compliance documentation. Git history cleanup is increasingly tied to audit requirements, and automated narrative generation could address that gap. The tool's ability to analyze contributor patterns also intersects with growing interest in git history visualization for code reviews.
Submissions close in two weeks. The real test: does this tool ship value beyond the contest, or is it optimized for demo aesthetics?