Updated 3w ago
by nimrodfisher
data-analytics-skills
A comprehensive list of Claude & Codex skills for a wide range of data analytics tasks
478 GitHub stars (478)
+27 in 20 days
| Period | New stars |
|---|---|
| Sep 27 | +2 |
| Sep 28 | +1 |
| Sep 29 | 0 |
| Sep 30 | +2 |
| Oct 1 | 0 |
| Oct 2 | +1 |
| Oct 3 | +1 |
| Oct 4 | +1 |
| Oct 5 | +2 |
| Oct 6 | +1 |
| Oct 7 | +3 |
| Oct 8 | 0 |
| Oct 9 | +1 |
| Oct 10 | +3 |
| Oct 11 | +1 |
| Oct 12 | +1 |
| Oct 13 | +1 |
| Oct 14 | +2 |
| Oct 15 | +2 |
| Oct 16 | +2 |
- 30 skills (30 skills found in its SKILL.md files)
- 84 forks (84 forks)
- 3w ago last update (Last updated 3w ago)
Install
Skills CLI
npx skills add nimrodfisher/data-analytics-skills
Asks which skills and agents to install. Just one: npx skills add nimrodfisher/data-analytics-skills --skill data-quality-audit — add -g for every project.
Claude Code
git clone https://github.com/nimrodfisher/data-analytics-skillscp -r "data-analytics-skills/01-data-quality-validation/data-quality-audit" ~/.claude/skills/
Copies the data-quality-audit skill into ~/.claude/skills/ for every project (use .claude/skills/ for one project). Repeat for the other skills listed below.
Plugin
/plugin marketplace add nimrodfisher/data-analytics-skills
Run inside Claude Code if the repository ships a plugin marketplace, then pick plugins from /plugin.
Skills can run code on your machine — read the SKILL.md first.
What it does
In the author's own words, from each skill's SKILL.md — showing the first 30 of 31 files.
-
data-quality-audit
Comprehensive data quality assessment against business rules, schema constraints, and freshness expectations. Activate when validating data pipeline outputs before production use, auditing a dataset against defined business rules, or producing a quality scorecard for a data asset.
01-data-quality-validation/data-quality-audit/SKILL.md on GitHub (opens in a new tab) -
programmatic-eda
Systematic exploratory data analysis. Activate when a dataset needs profiling — structure check, nulls, outliers, distributions, correlations — before deeper analysis begins.
01-data-quality-validation/programmatic-eda/SKILL.md on GitHub (opens in a new tab) -
query-validation
SQL query review for correctness, performance, and best practices. Activate when a query needs review before production use, shows unexpected results, or runs too slowly.
01-data-quality-validation/query-validation/SKILL.md on GitHub (opens in a new tab) -
analysis-assumptions-log
Track and document analytical assumptions and decisions. Use when making analytical choices, documenting trade-offs, ensuring transparency, or creating audit trails for analytical work.
02-documentation-knowledge/analysis-assumptions-log/SKILL.md on GitHub (opens in a new tab) -
analysis-documentation
Structured, reproducible analysis documentation. Use when documenting analysis findings, creating analysis notebooks, ensuring reproducibility, or building analysis archives for future reference.
02-documentation-knowledge/analysis-documentation/SKILL.md on GitHub (opens in a new tab) -
data-catalog-entry
Create standardized metadata for data assets. Use when documenting new datasets, building data catalogs, improving data discoverability, or creating data dictionaries for teams.
02-documentation-knowledge/data-catalog-entry/SKILL.md on GitHub (opens in a new tab) -
metric-reconciliation
Trace and resolve discrepancies when the same metric shows different values in two or more sources. Use before reporting, after pipeline changes, or when stakeholders question a number.
02-documentation-knowledge/metric-reconciliation/SKILL.md on GitHub (opens in a new tab) -
schema-mapper
Document column-level mappings between source and target schemas. Use when integrating data from multiple systems, designing ETL transformations, or documenting how raw fields become analytical assets.
02-documentation-knowledge/schema-mapper/SKILL.md on GitHub (opens in a new tab) -
semantic-model-builder
Build structured semantic layer documentation for metrics, dimensions, and entities. Activate when you need to define a business metric, document a data model, or create YAML definitions compatible with dbt Semantic Layer or similar frameworks.
02-documentation-knowledge/semantic-model-builder/SKILL.md on GitHub (opens in a new tab) -
sql-to-business-logic
Translate SQL queries into plain language business logic. Use when documenting queries, explaining analysis to non-technical stakeholders, code reviewing for correctness, or building a query catalog.
02-documentation-knowledge/sql-to-business-logic/SKILL.md on GitHub (opens in a new tab) -
ab-test-analysis
Rigorous A/B test statistical analysis. Use when analyzing experiment results, calculating statistical significance, checking for sample ratio mismatch, or validating test design before launch.
03-data-analysis-investigation/ab-test-analysis/SKILL.md on GitHub (opens in a new tab) -
business-metrics-calculator
Standard business metric calculation with industry benchmarks. Use when calculating SaaS metrics (MRR, churn, LTV, CAC), e-commerce KPIs, or product analytics metrics with proper definitions.
03-data-analysis-investigation/business-metrics-calculator/SKILL.md on GitHub (opens in a new tab) -
cohort-analysis
Time-based cohort analysis with retention and behaviour tracking. Activate when you need to measure how groups of users/customers behave over time — retention rates, revenue by cohort, or feature adoption curves.
03-data-analysis-investigation/cohort-analysis/SKILL.md on GitHub (opens in a new tab) -
funnel-analysis
Conversion funnel analysis with drop-off investigation. Use when analyzing multi-step processes, identifying conversion bottlenecks, comparing segments through a funnel, or optimizing user journeys.
03-data-analysis-investigation/funnel-analysis/SKILL.md on GitHub (opens in a new tab) -
root-cause-investigation
Systematic investigation of metric changes and anomalies. Use when a metric unexpectedly changes, investigating business metric drops, explaining performance variations, or drilling into aggregated metric drivers.
03-data-analysis-investigation/root-cause-investigation/SKILL.md on GitHub (opens in a new tab) -
segmentation-analysis
Customer/user segmentation with actionable insights. Use when identifying distinct customer groups, analyzing segment-specific behavior, profiling high-value segments, or testing segmentation hypotheses.
03-data-analysis-investigation/segmentation-analysis/SKILL.md on GitHub (opens in a new tab) -
time-series-analysis
Temporal pattern detection and forecasting. Use when analyzing trends over time, detecting seasonality, identifying anomalies in time series, or building simple forecasting models for planning.
03-data-analysis-investigation/time-series-analysis/SKILL.md on GitHub (opens in a new tab) -
dashboard-specification
Design specifications for effective dashboards. Use when planning new dashboards, improving existing ones, or documenting dashboard requirements before development starts.
04-data-storytelling-visualization/dashboard-specification/SKILL.md on GitHub (opens in a new tab) -
data-narrative-builder
Build compelling data-driven narratives. Use when presenting analysis results, creating stakeholder reports, or transforming a set of findings into a story that drives a specific decision or action.
04-data-storytelling-visualization/data-narrative-builder/SKILL.md on GitHub (opens in a new tab) -
executive-summary-generator
Create concise executive summaries from detailed analysis. Use when preparing board decks, executive briefings, or condensing complex analysis into decision-ready formats for senior audiences.
04-data-storytelling-visualization/executive-summary-generator/SKILL.md on GitHub (opens in a new tab) -
insight-synthesis
Transform data findings into compelling insights. Use when converting analysis results into actionable insights, connecting findings to business impact, or preparing insights for stakeholder communication.
04-data-storytelling-visualization/insight-synthesis/SKILL.md on GitHub (opens in a new tab) -
visualization-builder
Create effective, publication-ready data visualizations. Use when choosing chart types, designing presentation visuals, building dashboard charts, or applying visual design best practices to data output.
04-data-storytelling-visualization/visualization-builder/SKILL.md on GitHub (opens in a new tab) -
analysis-qa-checklist
Pre-delivery quality assurance for analysis work. Use when reviewing analysis before sharing with stakeholders, checking for completeness, validating assumptions, or ensuring clarity of recommendations.
05-stakeholder-communication/analysis-qa-checklist/SKILL.md on GitHub (opens in a new tab) -
impact-quantification
Estimate and communicate business impact of insights. Use when sizing opportunities discovered in analysis, calculating ROI of recommended actions, or prioritizing initiatives by potential impact.
05-stakeholder-communication/impact-quantification/SKILL.md on GitHub (opens in a new tab) -
methodology-explainer
Explain analysis methodology to diverse audiences. Use when documenting 'how we did this' sections, building trust through transparency, or teaching analytical approaches to stakeholders.
05-stakeholder-communication/methodology-explainer/SKILL.md on GitHub (opens in a new tab) -
stakeholder-requirements-gathering
Structured requirements elicitation for analysis requests. Use when scoping new analysis projects, clarifying ambiguous business questions, or documenting analysis acceptance criteria with stakeholders.
05-stakeholder-communication/stakeholder-requirements-gathering/SKILL.md on GitHub (opens in a new tab) -
technical-to-business-translator
Translate technical analysis into business language. Use when explaining statistical concepts to non-analysts, simplifying technical findings, or bridging communication between data teams and business stakeholders.
05-stakeholder-communication/technical-to-business-translator/SKILL.md on GitHub (opens in a new tab) -
analysis-planning
Structure analysis approach before starting work. Use when receiving new analysis requests, breaking down complex questions into steps, or planning iterative analysis workflows.
06-workflow-optimization/analysis-planning/SKILL.md on GitHub (opens in a new tab) -
analysis-retrospective
Post-analysis learning and process improvement. Use when completing major analysis projects, documenting lessons learned, or improving team analytical practices.
06-workflow-optimization/analysis-retrospective/SKILL.md on GitHub (opens in a new tab) -
context-packager
Efficiently package context for AI-assisted analysis. Use when preparing to work with Claude on analysis, organizing context documents, or structuring prompts for complex analytical tasks.
06-workflow-optimization/context-packager/SKILL.md on GitHub (opens in a new tab)
No skill matches that filter.
Review before you install
A skill is a set of instructions and scripts your agent will follow, and it can run code on your machine. Read the SKILL.md and any scripts first — this listing is not a security review.
Similar skills
-
agent-skillsby addyosmani Production-grade engineering skills for AI coding agents.
-
reaby morluto Reverse engineer anything with agents, from app behavior down to native binaries.
-
ui-ux-pro-max-skillby nextlevelbuilder An AI skill that provides design intelligence for building professional UI/UX across multiple platforms.
-
taste-skillby Leonxlnx Agent skills that give coding agents taste: art direction, reference images and a browser check instead of generic AI pages
-
Understand-Anythingby Egonex-AI Graphs that teach > graphs that impress. Turn any code into an interactive knowledge graph you can explore, search, and ask questions about…
-
archifyby tt-a1i Turn any idea, plan, or codebase into a beautiful interactive diagram. An agent skill for Claude Code, Codex, and more.