Transform raw data into compelling narratives that drive stakeholder decisions and action.
Run in your terminal
Three-pillar framework combining data evidence, narrative meaning, and visual clarity to structure insights for maximum impact
Includes five story templates (Problem-Solution, Trend, Comparison, Executive Summary, One-Page Dashboard) with ready-to-use structures for common business scenarios
Progressive reveal and annotation techniques to layer complexity, build understanding, and highlight key
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiondata-storytellingExecute the skills CLI command in your project's root directory to begin installation:
Package manager
npx skills add https://github.com/wshobson/agents --skill data-storytellingFetches data-storytelling from wshobson/agents 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 data-storytelling. Access via /data-storytellingin 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
Package manager
npx skills add https://github.com/wshobson/agents --skill data-storytellingWorks with
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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.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
ailabs-393/ai-labs-claude-skills
greedychipmunk/agent-skills
Useful defaults in data-storytelling — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Solid pick for teams standardizing on skills: data-storytelling is focused, and the summary matches what you get after install.
data-storytelling is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Keeps context tight: data-storytelling is the kind of skill you can hand to a new teammate without a long onboarding doc.
I recommend data-storytelling for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
We added data-storytelling from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
I recommend data-storytelling for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Keeps context tight: data-storytelling is the kind of skill you can hand to a new teammate without a long onboarding doc.
data-storytelling is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Useful defaults in data-storytelling — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
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