Data Analytics Skills

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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

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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.

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🗺️ Skill Map

Open interactive version on Excalidraw

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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.

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📚 Skill Categories

<details> <summary><b>🔍 01 &nbsp;·&nbsp; Data Quality & Validation</b> &nbsp;&nbsp; <code>3 skills</code></summary> <br>

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

</details> <details> <summary><b>📝 02 &nbsp;·&nbsp; Documentation & Knowledge</b> &nbsp;&nbsp; <code>7 skills</code></summary> <br>

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

</details> <details> <summary><b>📊 03 &nbsp;·&nbsp; Data Analysis & Investigation</b> &nbsp;&nbsp; <code>7 skills</code></summary> <br>

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

</details> <details> <summary><b>🎨 04 &nbsp;·&nbsp; Data Storytelling & Visualization</b> &nbsp;&nbsp; <code>5 skills</code></summary> <br>

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

</details> <details> <summary><b>🤝 05 &nbsp;·&nbsp; Stakeholder Communication</b> &nbsp;&nbsp; <code>5 skills</code></summary> <br>

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

</details> <details> <summary><b>⚙️ 06 &nbsp;·&nbsp; Workflow Optimization</b> &nbsp;&nbsp; <code>4 skills</code></summary> <br>

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

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📐 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.

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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

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📖 How skills work

Each skill follows the same on-demand context pattern:

1. Request minimum viable context — your agent asks only what's essential to start
2. Execute the workflow — structured, step-by-step analytical process
3. Surface assumptions — anything uncertain is flagged, not silently assumed
4. 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.

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🛠️ 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.

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🎓 Suggested ramp-up

Week 1 — Get comfortable

• Run programmatic-eda on a familiar dataset
• Practice providing context when your agent asks
• Use analysis-planning at the start of your next project

Week 2–3 — Add your core toolkit

• Set up semantic-model-builder for your key metrics (saves time forever)
• Add query-validation to 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

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