完成数据分析全流程
覆盖数据清洗到业务洞察交付的完整过程。
使用前,准备这些
输入素材:研究问题、来源范围与输出要求
- 在下方原始文档中确认支持的 AI 工具、模型和运行依赖。
- 打开原仓库,按作者的安装说明完成配置;模型 API 或外部服务可能需要单独开通。
- 用自己的素材试运行,再检查事实、版式与输出文件。
许可证:未明确声明,请查看原仓库的使用条件。
来源快照:2026-09-15。README ↗
可以这样开始
Data Analytics Skills for Claude & Codex
31 portable AI-powered skills that turn Claude or Codex 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 Code or Codex 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. Skills follow the open Agent Skills standard (a plain SKILL.md format), so they also work with other compatible agents like Cursor and Windsurf.
🗺️ Skill Map
Open interactive version on Excalidraw
Why these skills are different
[!NOTE] 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 3 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 |
📝 02 · Documentation & Knowledge 7 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 |
| metric-reconciliation | Trace and resolve discrepancies when metric sources disagree |
| schema-mapper | Column-level mapping between source and target schemas |
📊 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 |
📐 Also by the maintainer
Caliboard — visual plan review for Claude Code and Codex. See what your agent plans before it writes code: review exact steps, challenge decisions, and approve the revision that becomes code.
Version: 1.2.0 · Maintainer: Nimrod Fisher · Last Updated: September 2026
🚀 Quick Start
Install
Each skill is a folder containing a SKILL.md (plus optional scripts/, references/, and assets/). Clone the repo and copy the skills you want into your agent's skills directory:
git clone https://github.com/nimrodfisher/data-analytics-skills.git
Claude Code: personal skills (all projects) go in ~/.claude/skills/, project skills in .claude/skills/ inside your project:
cp -r 01-data-quality-validation/programmatic-eda ~/.claude/skills/
Codex: user skills (all repos) go in ~/.agents/skills/, repo skills in .agents/skills/ at the repository root:
cp -r 01-data-quality-validation/programmatic-eda ~/.agents/skills/
New here? QUICKSTART.md walks you through your first skill in 5 minutes, and STRUCTURE.md explains how every skill is packaged.
[!TIP] Describe your task to Claude or Codex 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"
Agent: [activates root-cause-investigation, asks for metric data and context]
You: [provides data and business context]
Agent: [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 — your agent 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
[!NOTE] Skills degrade gracefully: if you can't provide everything, your agent 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.
Your agent 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 your agent 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