repo-story-time▌
github/awesome-copilot · updated Apr 8, 2026
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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.
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, DirectoryName -
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 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
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
- Be Specific: Use actual file names, commit messages, and contributor names
- Find Stories: Look for interesting patterns, not just statistics
- Context Matters: Explain why patterns exist (holidays, releases, incidents)
- Human Element: Focus on the people and teams behind the code
- Technical Depth: Balance narrative with technical accuracy
- Evidence-Based: Support observations with actual git data
Success Criteria
- Both markdown files are ACTUALLY CREATED with complete, comprehensive content using the
editFilestool - 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.
How to use repo-story-time on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add repo-story-time
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches repo-story-time from GitHub repository github/awesome-copilot and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate repo-story-time. Access the skill through slash commands (e.g., /repo-story-time) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★59 reviews- ★★★★★Aditi Chawla· Dec 28, 2024
repo-story-time fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Ama Thomas· Dec 28, 2024
repo-story-time fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Charlotte Thomas· Dec 24, 2024
I recommend repo-story-time for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Pratham Ware· Dec 8, 2024
We added repo-story-time from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Lucas Gonzalez· Dec 4, 2024
Registry listing for repo-story-time matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Yash Thakker· Nov 27, 2024
repo-story-time fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Aarav Harris· Nov 23, 2024
Solid pick for teams standardizing on skills: repo-story-time is focused, and the summary matches what you get after install.
- ★★★★★Ama Khanna· Nov 19, 2024
We added repo-story-time from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Omar Jackson· Nov 19, 2024
We added repo-story-time from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Charlotte Bansal· Nov 15, 2024
Useful defaults in repo-story-time — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
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