Perform cohort analysis on user engagement data — retention curves, feature adoption trends, and segment-level insights. Use when analyzing user retention by cohort, studying feature adoption over time, investigating churn patterns, or identifying engagement trends.
dummy-dataset
dummy-dataset is an open-source data skill for Claude Code and compatible agents, published by phuryn. Its author describes it as: “Generate realistic dummy datasets for testing with customizable columns, constraints, and output formats (CSV, JSON, SQL, Python script). Use when creating test data, building mock datasets, or generating sample data…”. The project has 25k stars on GitHub and is available under the MIT license. Add it to your setup with `/plugin marketplace add phuryn/pm-skills`.
What dummy-dataset does
Generate realistic dummy datasets for testing with customizable columns, constraints, and output formats (CSV, JSON, SQL, Python script). Creates executable scripts or direct data files for immediate use.
Installation
Add dummy-dataset to your agent with:
/plugin marketplace add phuryn/pm-skillsAlways review a skill's source before installing it. This command comes from the skill's public repository; the linked repo is the source of truth for exact setup steps.
What's inside
The SKILL.md for dummy-dataset is organised into these sections:
- Step-by-Step Process
- Template: Python Script Output
- Example Dataset Specification
- Output Deliverables
- Output Formats
When to use it
Reach for dummy-dataset when you want data help from your agent without writing the same instructions every session. Load the skill and the agent picks it up automatically for relevant tasks.
Strengths
- Clear MIT license — safe to read and adapt
- Ships in phuryn/pm-skills, an established project with 25,392 GitHub stars
- Actively maintained (recent commits)
Topics
Frequently asked questions
- What does dummy-dataset do?
- Generate realistic dummy datasets for testing with customizable columns, constraints, and output formats (CSV, JSON, SQL, Python script). Use when creating test data, building mock datasets, or generating sample data for development and demos.
- How do I install dummy-dataset?
- Run /plugin marketplace add phuryn/pm-skills in your agent, then reload your skills. Review the source at https://github.com/phuryn/pm-skills before installing.
- Is dummy-dataset free to use?
- Yes. dummy-dataset is free and open source under the MIT license, so you can read, run, and adapt it within that license's terms.
- Where does dummy-dataset come from?
- dummy-dataset ships inside phuryn/pm-skills, a repository that contains 41 catalogued skills in total. The repository's 25,392 GitHub stars apply to that whole collection, not to this skill on its own.
Related skills
More Data →Analyze competitors with strengths, weaknesses, and differentiation opportunities. Identifies direct competitors and maps the competitive landscape. Use when doing competitive research, preparing a competitive brief, or finding differentiation opportunities.
Analyze user feedback data to identify segments with sentiment scores, JTBD, and product satisfaction insights. Use when analyzing user feedback at scale, running sentiment analysis on reviews or surveys, or identifying satisfaction patterns.
Set up, audit, and debug analytics tracking implementation — GA4, Google Tag Manager, event taxonomy, conversion tracking, and data quality. Use when building a tracking plan from scratch, auditing existing analytics for gaps or errors, debugging missing events, or setting up GTM. Trigger keywords: GA4 setup, Google Tag Manager, GTM, event tracking, analytics implementation, conversion tracking, tracking plan, event taxonomy, custom dimensions, UTM tracking, analytics audit, missing events, tracking broken. NOT for analyzing marketing campaign data — use campaign-analytics for that. NOT for BI dashboards — use product-analytics for in-product event analysis.
App Store Optimization (ASO) toolkit for researching keywords, analyzing competitor rankings, generating metadata suggestions, and improving app visibility on Apple App Store and Google Play Store. Use when the user asks about ASO, app store rankings, app metadata, app titles and descriptions, app store listings, app visibility, or mobile app marketing on iOS or Android. Supports keyword research and scoring, competitor keyword analysis, metadata optimization, A/B test planning, launch checklists, and tracking ranking changes.