data-analytics-skills
A comprehensive library of portable, on-demand AI skills for Claude, covering the entire data analytics workflow from quality checks to stakeholder communication.
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About this skill
Data Analytics Skills for Claude
31 portable AI-powered skills that turn Claude into a hands-on analytics partner. No setup required · Works for any company or industry.
What's in this repo?
A structured library of skills (reusable instruction sets) that Claude activates on demand to help with every stage of the analyst workflow: from data quality checks and deep-dive analysis, through documentation and dashboards, all the way to stakeholder communication.
Skill Map
The full skill map is available as an interactive diagram on Excalidraw:
Why These Skills Are Different
Traditional AI assistants require extensive upfront configuration — schemas, metric definitions, business rules — before they're useful. These skills work on-demand.
| Traditional approach | These skills |
|---|---|
| Needs prep before use | Zero setup required |
| Breaks when business rules change | Adapts naturally |
| Company-specific, hard to share | Portable across any org |
| Silent on assumptions | Teaches you what context matters |
Each skill asks targeted questions to gather exactly what it needs, then executes a complete, structured workflow.
Skill Categories
01 Data Quality & Validation (5 skills)
Foundation — start here whenever you're working with new data.
| Skill | What it does |
|---|---|
| programmatic-eda | Systematic exploratory data analysis with automated sanity checks |
| data-quality-audit | Comprehensive quality assessment against business rules and schema |
| query-validation | SQL review for correctness, performance, and edge cases |
| schema-mapper | Understand database relationships and table structures |
| metric-reconciliation | Investigate discrepancies between metric sources |
02 Documentation & Knowledge (5 skills)
Build reusable context so you never explain the same thing twice.
| Skill | What it does |
|---|---|
| semantic-model-builder | Create a shared semantic layer for key metrics and dimensions |
| analysis-documentation | Document findings with reproducible methodology |
| data-catalog-entry | Standardized metadata and descriptions for data assets |
| sql-to-business-logic | Translate complex SQL into plain business language |
| analysis-assumptions-log | Track every assumption and decision in an analysis |
03 Data Analysis & Investigation (7 skills)
Core workflows for the analytical heavy lifting.
| Skill | What it does |
|---|---|
| cohort-analysis | Time-based cohort tracking with retention curves |
| segmentation-analysis | Customer/user segmentation with actionable profiles |
| funnel-analysis | Conversion funnel with drop-off root-cause |
| time-series-analysis | Trend detection, seasonality, and forecasting |
| root-cause-investigation | Structured diagnosis of unexpected metric changes |
| ab-test-analysis | Rigorous experiment analysis with significance testing |
| business-metrics-calculator | Standard business metric calculation with benchmarks |
04 Data Storytelling & Visualization (5 skills)
Turn raw findings into insights that drive decisions.
| Skill | What it does |
|---|---|
| insight-synthesis | Structure analysis outputs into clear business insights |
| visualization-builder | Chart type selection, design guidance, and spec generation |
| executive-summary-generator | Concise executive-ready summaries of complex analysis |
| dashboard-specification | Full dashboard requirements with metrics and layout |
| data-narrative-builder | Craft a compelling story arc from analytical findings |
05 Stakeholder Communication (5 skills)
Bridge the gap between technical depth and business understanding.
| Skill | What it does |
|---|---|
| technical-to-business-translator | Reframe technical findings for a business audience |
| stakeholder-requirements-gathering | Structured elicitation to clarify what stakeholders actually need |
| analysis-qa-checklist | Pre-delivery quality gate before sharing results |
| methodology-explainer | Explain analysis approach to any audience level |
| impact-quantification | Estimate and frame the business impact of findings |
06 Workflow Optimization (4 skills)
Work smarter across every project.
| Skill | What it does |
|---|---|
| analysis-planning | Structure the approach before diving in |
| context-packager | Package context efficiently for AI-assisted analysis |
| peer-review-template | Structured peer review checklist for analytical work |
| analysis-retrospective | Post-analysis learning and process improvement |
Quick Start
Describe your task to Claude naturally — it will select and activate the right skill automatically. No slash commands needed.
Example:
You: "I need to understand why our activation rate dropped 12% last week"
Claude: [activates root-cause-investigation, asks for metric data and context]
You: [provides data and business context]
Claude: [runs structured investigation with hypothesis testing]
Which skill to start with?
| You need to... | Start here |
|---|---|
| Explore an unfamiliar dataset | programmatic-eda → data-quality-audit |
| Write or review SQL | query-validation + schema-mapper |
| Understand a metric drop/spike | root-cause-investigation |
| Analyze experiment results | ab-test-analysis |
| Build a dashboard | dashboard-specification + visualization-builder |
| Present to leadership | executive-summary-generator + insight-synthesis |
| Document your methodology | analysis-documentation + analysis-assumptions-log |
| Start a complex analysis | analysis-planning first, always |
How Skills Work
Each skill follows the same on-demand context pattern:
- Request minimum viable context — Claude asks only what's essential to start
- Execute the workflow — structured, step-by-step analytical process
- Surface assumptions — anything uncertain is flagged, not silently assumed
- Deliver a consistent output — templated result you can share or iterate on
Skills degrade gracefully: if you can't provide everything, Claude states what it's assuming and proceeds.
Customization
Skills work out-of-the-box. To make them company-specific, add a references/ folder inside any skill with:
skill-name/
├── SKILL.md
└── references/
├── company-schema.md ← your table/column definitions
├── metric-definitions.md ← standard metric formulas
└── business-rules.md ← thresholds, edge cases, etc.
Claude will pull this context automatically when the skill runs.
Suggested Ramp-Up
Week 1 — Get comfortable
- Run
programmatic-edaon a familiar dataset - Practice providing context when Claude asks
- Use
analysis-planningat the start of your next project
Week 2–3 — Add your core toolkit
- Set up
semantic-model-builderfor your key metrics (saves time forever) - Add
query-validationto your SQL workflow - Pick 2 analysis skills that match your domain
Week 4+ — Go advanced
- Chain 4–5 skills end-to-end on a full project
- Add company-specific references to the skills you use most
- Build team context documents for shared onboarding