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.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionrepo-story-timeExecute the skills CLI command in your project's root directory to begin installation:
Fetches repo-story-time from github/awesome-copilot and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate repo-story-time. Access via /repo-story-time in your agent's command palette.
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 environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
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
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
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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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.
Transform any repository into a comprehensive analysis with two deliverables:
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.
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:
Create comprehensive technical inventory:
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 20Step 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 12Step 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 20Step 5: Collaboration Patterns - Run this command:
git log --since="1 year ago" --merges --oneline | Select-Object -First 20Step 6: Seasonal Analysis - Run this command:
git log --since="1 year ago" --format="%ai" | ForEach-Object { $_.Substring(5,2) } | Group-Object | Sort-Object NameImportant: 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.
Look for these narrative elements:
# 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 [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.
editFiles toolDO 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.
Make data-driven prioritization decisions faster
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
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ 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.
github/awesome-copilot
github/awesome-copilot
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
repo-story-time fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
repo-story-time fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
I recommend repo-story-time for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
We added repo-story-time from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Registry listing for repo-story-time matched our evaluation — installs cleanly and behaves as described in the markdown.
repo-story-time fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Solid pick for teams standardizing on skills: repo-story-time is focused, and the summary matches what you get after install.
We added repo-story-time from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
We added repo-story-time from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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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