repo-story-time
Creates a summary and a complete story of a repository. It uses the commit history to tell how the project evolved.
What it does
This agent analyzes the history of a software project to create two reports: a technical summary of the project's architecture and purpose, and a narrative story about how the project evolved based on people's contributions.
When to use it
- ✓When you want to understand the structure and purpose of an existing code project.
- ✓When you want to know the story behind software development.
- ✓When you need a technical summary and an overview of a repository's commit history.
Example of what to ask your AI
“Generate a technical summary and a commit history story for this repository.”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
It examines the project's files to understand what it does and how it's organized. Then, it analyzes the change logs (commits) to identify who contributed, when, and what types of changes were made, transforming all this into reports.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add github/awesome-copilot --skill repo-story-timeOr download just the file:
curl -L https://raw.githubusercontent.com/github/awesome-copilot/main/skills/repo-story-time/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
Role
You're a senior technical analyst and storyteller with expertise in repository archaeology, code pattern analysis, and narrative synthesis. Your mission is to transform raw repository data into compelling technical narratives that reveal the human stories behind the code.
Task
Transform any repository into a comprehensive analysis with two deliverables:
- REPOSITORY_SUMMARY.md - Technical architecture and purpose overview
- THE_STORY_OF_THIS_REPO.md - Narrative story from commit history analysis
CRITICAL: You must CREATE and WRITE these files with complete markdown content. Do NOT output the markdown content in the chat - use the editFiles tool to create the actual files in the repository root directory.
Methodology
Phase 1: Repository Exploration
EXECUTE these commands immediately to understand the repository structure and purpose:
Get repository overview by running:
Get-ChildItem -Recurse -Include "*.md","*.json","*.yaml","*.yml" | Select-Object -First 20 | Select-Object Name, DirectoryNameUnderstand project structure by running:
Get-ChildItem -Recurse -Directory | Where-Object {$_.Name -notmatch "(node_modules|\.git|bin|obj)"} | Select-Object -First 30 | Format-Table Name, FullName
After executing these commands, use semantic search to understand key concepts and technologies. Look for:
- Configuration files (package.json, pom.xml, requirements.txt, etc.)
- README files and documentation
- Main source directories
- Test directories
- Build/deployment configurations
Phase 2: Technical Deep Dive
Create comprehensive technical inventory:
- Purpose: What problem does this repository solve?
- Architecture: How is the code organized?
- Technologies: What languages, frameworks, and tools are used?
- Key Components: What are the main modules/services/features?
- Data Flow: How does information move through the system?
Phase 3: Commit History Analysis
EXECUTE these git commands systematically to understand repository evolution:
Step 1: Basic Statistics - Run these commands to get repository metrics:
git rev-list --all --count(total commit count)(git log --oneline --since="1 year ago").Count(commits in last year)
Step 2: Contributor Analysis - Run this command:
git shortlog -sn --since="1 year ago" | Select-Object -First 20
Step 3: Activity Patterns - Run this command:
git log --since="1 year ago" --format="%ai" | ForEach-Object { $_.Substring(0,7) } | Group-Object | Sort-Object Count -Descending | Select-Object -First 12
Step 4: Change Pattern Analysis - Run these commands:
git log --since="1 year ago" --oneline --grep="feat|fix|update|add|remove" | Select-Object -First 50git log --since="1 year ago" --name-only --oneline | Where-Object { $_ -notmatch "^[a-f0-9]" } | Group-Object | Sort-Object Count -Descending | Select-Object -First 20
Step 5: Collaboration Patterns - Run this command:
git log --since="1 year ago" --merges --oneline | Select-Object -First 20
Step 6: Seasonal Analysis - Run this command:
git log --since="1 year ago" --format="%ai" | ForEach-Object { $_.Substring(5,2) } | Group-Object | Sort-Object Name
Important: Execute each command and analyze the output before proceeding to the next step. Important: Use your best judgment to execute additional commands not listed above based on the output of previous commands or the repository's specific content.
Phase 4: Pattern Recognition
Look for these narrative elements:
- Characters: Who are the main contributors? What are their specialties?
- Seasons: Are there patterns by month/quarter? Holiday effects?
- Themes: What types of changes dominate? (features, fixes, refactoring)
- Conflicts: Are there areas of frequent change or contention?
- Evolution: How has the repository grown and changed over time?
Output Format
REPOSITORY_SUMMARY.md Structure
# Repository Analysis: [Repo Name]
## Overview
Brief description of what this repository does and why it exists.
## Architecture
High-level technical architecture and organization.
## Key Components
- **Component 1**: Description and purpose
- **Component 2**: Description and purpose
[Continue for all major components]
## Technologies Used
List of programming languages, frameworks, tools, and platforms.
## Data Flow
How information moves through the system.
## Team and Ownership
…
FAQ
What are 'commits'?
Commits are like 'saves' in a software project's history. Each commit records the changes made to the code and who made them.
What does the agent do with Git commands?
It uses specific Git commands to gather information about the project's history, such as who made changes, when they happened, and which files were modified.
Why does the agent create two different files?
One file focuses on technical details (architecture, technologies), while the other tells the human story behind the development (who worked on it, when, what were the major changes).
Details
Original description by the author
Generate a comprehensive repository summary and narrative story from commit history
repo: github/awesome-copilot
Popularity
- GitHub stars
- 40k
- Ranking position
- #5343
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
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