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github avatar

Repo Story Time

github/awesome-copilotOfficial

Ever wondered what the real story is behind a codebase you just inherited or stumbled across? This one digs through git history and repository structure to generate two concrete files: a technical summary breaking down architecture and components, plus a narrative that reveals who's actually building what and when. It runs specific git commands to analyze commit patterns, contributor behavior, and seasonal development cycles, then writes actual markdown files you can read or share. Perfect for onboarding to unfamiliar repos, documenting legacy projects, or just satisfying curiosity about how a codebase evolved. Turns archaeological detective work into readable stories with real data backing every claim.

installs
8.9K
GitHub stars
40.5K
last updated
Aug 21, 2026
View on GitHubSave

Install

$ npx -y skills add github/awesome-copilot --skill repo-story-time --agent claude-code

Installs into .claude/skills of the current project.

Files

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:

  1. REPOSITORY_SUMMARY.md - Technical architecture and purpose overview
  2. 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:

  1. Get repository overview by running: Get-ChildItem -Recurse -Include "*.md","*.json","*.yaml","*.yml" | Select-Object -First 20 | Select-Object Name, DirectoryName

  2. Understand 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 50
  • git 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
Who maintains different parts of the codebase.

THE_STORY_OF_THIS_REPO.md Structure

# The Story of [Repo Name]

## The Chronicles: A Year in Numbers
Statistical overview of the past year's activity.

## Cast of Characters
Profiles of main contributors with their specialties and impact.

## Seasonal Patterns
Monthly/quarterly analysis of development activity.

## The Great Themes
Major categories of work and their significance.

## Plot Twists and Turning Points
Notable events, major changes, or interesting patterns.

## The Current Chapter
Where the repository stands today and future implications.

Key Instructions

  1. Be Specific: Use actual file names, commit messages, and contributor names
  2. Find Stories: Look for interesting patterns, not just statistics
  3. Context Matters: Explain why patterns exist (holidays, releases, incidents)
  4. Human Element: Focus on the people and teams behind the code
  5. Technical Depth: Balance narrative with technical accuracy
  6. Evidence-Based: Support observations with actual git data

Success Criteria

  • Both markdown files are ACTUALLY CREATED with complete, comprehensive content using the editFiles tool
  • NO markdown content should be output to chat - all content must be written directly to the files
  • Technical summary accurately represents repository architecture
  • Narrative story reveals human patterns and interesting insights
  • Git commands provide concrete evidence for all claims
  • Analysis reveals both technical and cultural aspects of development
  • Files are ready to use immediately without any copy/paste from chat dialog

Critical Final Instructions

DO NOT output markdown content in the chat. DO use the editFiles tool to create both files with complete content. The deliverables are the actual files, not chat output.

Remember: Every repository tells a story. Your job is to uncover that story through systematic analysis and present it in a way that both technical and non-technical audiences can appreciate.

SKILL.md on GitHub

Sponsors

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Details

Repository
github.com/github/awesome-copilot
Categories
Git & Pull Requests, AI & Agent Building

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