Cupid-Commit 💘 - Finding the Code That Completes You

*This is a submission for the [GitHub Copilot CLI Challenge](https://dev.to/challenges/github-2026-01-21)* ## What I Built **Cupid-Commit** is a custom GitHub Copilot CLI extension that acts as a "Couples Counselor for Code." With Valentine's Day upon us, I wanted to build something fun but technically complex. I recently built a project called [Codebase Cartographer](https://github.com/dev-jash15/codebase-cartographer) to visually map out codebase dependencies, which got me thinking about how different repositories "communicate." What if we could use AI to figure out if two different tech stacks would make a good match? I built a Node.js CLI tool that accepts any two remote GitHub repositories as arguments. It uses the GitHub CLI (`gh repo view`) to dynamically scrape their languages, descriptions, and popularity. It then feeds this "DNA" into a custom GitHub Copilot Agent (`.agent.md`) using programmatic mode. The AI categorizes the repositories into archetypes (like The Romantic, The Stoic, or The Socialite), analyzes their tech-stack compatibility, and outputs a perfectly formatted Markdown file containing a **Compatibility Report** and a **Love Letter** from Repo A to Repo B. ## Demo GitHub Repository: https://github.com/dev-jash15/cupid-commit ## My Experience with GitHub Copilot CLI Working with the Copilot CLI ecosystem was an incredible learning experience, especially when pushing the boundaries of non-interactive automation. **1. Taming the Custom Agent (`.agent.md`):** I learned that you can enforce incredibly strict personas using the .agent.md framework. By defining "Core Directives" and "Tone Constraints," I was able to force the LLM to completely abandon standard coding assistance and strictly act as a witty relationship counselor, outputting beautifully formatted markdown instead of raw JSON or code snippets. **2. Bypassing the Programmatic Sandbox:** The biggest technical hurdle I faced was the CLI's security sandbox. I wanted to use programmatic mode (`copilot -p`) to fully automate the pipeline. However, in this mode, Copilot strictly restricts access to files outside the current working directory. To solve this, I engineered a "Drop and Clean" strategy using Node.js. My orchestrator script: - Fetches the remote repository data using `gh` commands. - Writes that data to a hidden `.temp-dna.json` file directly inside the user's current directory. - Copies my `.cupid.agent.md` file into the same directory. - Executes the Copilot CLI using the `@file` operator to read those local temp files. - Captures the output, strips the CLI telemetry, and automatically deletes the temporary files to leave the user's workspace perfectly clean. This combination of standard Node orchestration and Copilot's `@file` context mapping allowed me to build a highly dynamic, multi-repo tool that feels completely native to the terminal. <!-- Don't forget to add a cover image (if you want). --> <!-- Team Submissions: Please pick one member to publish the submission and credit teammates by listing their DEV usernames directly in the body of the post. --> <!-- Thanks for participating! -->