Generate a comprehensive repository summary and narrative story from commit history

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 THE STORY OF THIS REPO.md Structure 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.

repo-story-time