Data Analysis Claude Skills
2 409 data analysis skills from 443 authors. They crunch numbers, pivot tables and turn both into something readable. Half of them fit into 1 952 tokens or less — that is what one costs your context window when the agent loads it. 549 ship runnable scripts rather than instructions alone. 31 of them cannot work without an MCP server, most often rube. We also found 386 copies of these same skills sitting in other people's repositories — counted once here, not 386 times.
2 409 unique 443 authors 5 updated this month 241 from vendors
Create 3D visualizations of velocity fields and pump CFD results
> 🤖 Data Science & AI/ML skill suite derived from GetBindu/awesome-claude-code-and-skills. Data pipelines, model training, evaluation, MLOps and analytical reporting. Provides 10 specialised commands for data-science, machine-learning, analytics workflows.
当用户请求数据分析、报告、统计、趋势或绩效指标时使用此技能——包括销售数据、退货率、供应商绩效和运营 KPI。
Generate a daily analytics report of what GitHub Copilot helped accomplish. Shows tasks completed, human effort equivalent, token usage, and a narrative story. Sends a formatted email summary. Use when the user asks about their daily activity, what Copilot helped with today, or wants a digest of the day's work.
Score your Claude Code environment on a fun 0-10 ladder (Tourist → Swarm) calibrated to the quickstart's 4 systems — Context, Skills, Integrations, Orchestration. Two front doors - an interactive quiz (zero setup, shareable) or a silent scan of your repo. Outputs a next-level roadmap plus a branded HTML dashboard or a paste-anywhere ASCII card. The default mastery skill of this quickstart. Triggers - "level", "what's my claude code level", "claude code level quiz", "assess my setup", "how good is my setup", "claude code maturity
Create professional malware analysis reports for enterprise security teams and incident response. Use when you need to write, structure, or improve a malware analysis report, produce executive summaries, author YARA rules, or format IOCs and detection rules for professional delivery.
> 🛒 E-commerce & Retail skill suite derived from borghei/Claude-Skills. Product catalogue optimisation, conversion rate, customer journey and retail analytics. Provides 10 specialised commands for ecommerce, retail, shopify workflows.
Transform raw data into analytical assets using ETL/ELT patterns, SQL (dbt), Python (pandas/polars/PySpark), and orchestration (Airflow). Use when building data pipelines, implementing incremental models, migrating from pandas to polars, or orchestrating multi-step transformations with testing and quality checks.
Generate data visualizations, plots, and charts. Analyzes data structure to select optimal visualization types. supports bar charts, line graphs, and scatter plots for clarity.
Python best practices, FastAPI, Pandas ve veri bilimi kütüphaneleri kullanımı.
Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas
Build HTML data explorers for CSV, JSON, log, and event data — filterable tables, faceted search, inline charts, timeline scrubbing, A/B test result dashboards. Use whenever the user has a dataset to explore, browse, filter, chart, facet, or analyze — especially for ad-hoc analysis where opening a heavy BI tool is overkill. Reach for this when the user pastes data, mentions a CSV/JSON/log file, or asks to "look at" or "analyze" a dataset. Always runs a secret-redaction pass before embedding data — credential-shaped values (API keys, tokens, cookies, passwords) are replaced with placeholders unless the user explicitly opts in to embedding them.
> 🤖 Data Science & AI/ML skill suite derived from alirezarezvani/claude-code-skill-factory. Data pipelines, model training, evaluation, MLOps and analytical reporting. Provides 10 specialised commands for data-science, machine-learning, analytics workflows.
Query a running Convex app's logs + health in natural language (official MCP): failures, slow/expensive functions, deploy causality — scoped, evidence-backed, with a dashboard deep link.
Use this skill whenever the user asks to visualize, chart, plot, or graph data (bar, line, scatter, histogram, pie) from a CSV, table, or DataFrame. It gives the agent prebuilt, parameterized matplotlib functions so charts are produced faster and more reliably — with consistent styling and sane defaults — instead of hand-writing matplotlib each time.
Use this skill whenever the user asks to visualize a project schedule, timeline, Gantt chart, or phase/task breakdown over time. It gives the agent a prebuilt, parameterized gantt() function so Gantt charts are produced instantly and consistently — with colour-coded groups, completion overlays, a today reference line, and auto-scaled date axes — instead of hand-writing matplotlib each time.
Use this skill whenever the user asks to run a Monte Carlo simulation, model risk or uncertainty with random sampling, estimate P5/P50/P95 outcomes, or produce a probability distribution for project timelines, portfolio returns, downtime, costs, or similar uncertain variables. Trigger on phrases like 'run a Monte Carlo', 'simulate outcomes', 'probability chart for best and worst case', or when they give min/most-likely/max (or mean/std) and want thousands of iterations. Do NOT trigger for deterministic forecasts with no uncertainty, or for generic charts unrelated to simulation.
Use this skill whenever the user asks for an insights/reporting analysis of a SharePoint list from a connected SharePoint knowledge source; first validate the list exists, then generate and save a single-file interactive HTML report to a pre-approved SharePoint destination whose audience is no broader than the source list and items, and return its SharePoint URL.
Turns an uploaded dataset (.xlsx, .csv, .json, or PDF tables) into a self-contained, scroll-driven HTML data story with animated Plotly charts, counting stat cards, and narrative chapters. Use when the user asks for a data story, scrollytelling report, or an interactive narrative write-up of a dataset. If the user asks for a demo or example with no dataset of their own, build the story from the bundled sample workbook at assets/Basketball_Demo_Data.xlsx.
>- Provides Mermaid diagram syntax, best practices, and styling rules for technical visualizations. Use when creating diagrams, flowcharts, sequence diagrams, class diagrams, state diagrams, ER diagrams, architecture diagrams, C4 diagrams, visualizations, or any visual documentation in markdown. Always use this skill when generating or updating Mermaid code blocks.
>- Provides Mermaid diagram syntax, best practices, and styling rules for technical visualizations. Use when creating diagrams, flowcharts, sequence diagrams, class diagrams, state diagrams, ER diagrams, architecture diagrams, C4 diagrams, visualizations, or any visual documentation in markdown. Always use this skill when generating or updating Mermaid code blocks.
>- Provides Mermaid diagram syntax, best practices, and styling rules for technical visualizations. Use when creating diagrams, flowcharts, sequence diagrams, class diagrams, state diagrams, ER diagrams, architecture diagrams, C4 diagrams, visualizations, or any visual documentation in markdown. Always use this skill when generating or updating Mermaid code blocks.
Provides Mermaid diagram syntax, best practices, and styling rules for technical visualizations. Use when creating diagrams, flowcharts, sequence diagrams, class diagrams, state diagrams, ER diagrams, architecture diagrams, C4 diagrams, or any visual documentation in markdown.
>- Provides Mermaid diagram syntax, best practices, and styling rules for technical visualizations. Use when creating diagrams, flowcharts, sequence diagrams, class diagrams, state diagrams, ER diagrams, architecture diagrams, C4 diagrams, visualizations, or any visual documentation in markdown. Always use this skill when generating or updating Mermaid code blocks.
>- Provides Mermaid diagram syntax, best practices, and styling rules for technical visualizations. Use when creating diagrams, flowcharts, sequence diagrams, class diagrams, state diagrams, ER diagrams, architecture diagrams, C4 diagrams, visualizations, or any visual documentation in markdown. Always use this skill when generating or updating Mermaid code blocks.
Query and manage Grafana dashboards, alert rules, and data sources via HTTP API. Use when viewing dashboards, troubleshooting alerts, checking service metrics, finding data sources, or when Grafana, monitoring, alerts, dashboards, or observability is mentioned.
Query Prometheus monitoring metrics and alert rules. Use when the user needs to check CPU/memory/disk utilization, service health, audit alert rules, analyze capacity trends, or mentions Prometheus, PromQL, metrics monitoring, or targets.
Generate a Kafka consumer group lag dashboard. Use when the user asks to monitor lag, build a dashboard for consumer lag, or wire up Prometheus exporters for Kafka. Do NOT trigger for producer metrics, broker JMX, or Streams-specific monitoring.
>- Use when a store owner is doing bulk data work through the Matrixify (formerly "bulk edit metafields", CSV or Excel import, "my import deleted my metafields", "my import wiped my tags", MERGE vs REPLACE vs UPDATE, "how do I undo an import", building a Matrixify sheet by hand or programmatically, or a data migration between stores/platforms. Covers products, variants, metafields, collections, redirects, customers, and menus. Not for minting category (taxonomy) metafields, which Matrixify cannot do (use shopify-category-taxonomy); not for one-off single-record edits via the Admin API (use the relevant entity skill).
>- Use when you assign the Shopify Standard Product Taxonomy category, "set the product category", "categorize the catalog", or fill the category / taxonomy Caffeine content), a.k.a. product category attributes / taxonomy attributes, including the attributes a Google feed asks for. Covers bulk classification, discovering a category's attributes and allowed "category metafields show blank/null", "my Color attribute won't save". Not for bulk CSV data loads (Matrixify can't do this; see shopify-matrixify for bulk data).
Automate the grunt work of making research presentations — discovers experiments from git/output folders, collects images and metrics, and organizes them into slides. Creates a slide-by-slide script for user approval, then generates slide markdown and editable PPTX.
Audit a game feature, roadmap candidate, UX improvement, support system, connective-tissue feature, or quality-of-life change for KPI coverage bias and measurement blind spots. Use when a team is overvaluing only directly attributable metrics, neglecting foundational work that is hard to measure, or struggling to justify features whose value is real but not cleanly tied to one headline KPI.
Track game design prototype ideas, branching outcomes, dead ends, baselines, and next experiments, and optionally generate a simple SVG visualization of prototype evolution. Use when a prototype leads to several possible follow-up paths, when the team needs to backtrack without losing learned branches, when exploring unknowns through multiple iterations, or when you want both a written prototype log and a branch map of how the concept evolved over time.
Use when the user asks for a client report, a monthly or activity report, a case study draft, or says 'what did i ship this month'. Turns the site audit log into a written report in one of six framings: agency client report, case study, internal recap, testimonial draft, build-in-public, personal recap.
| 企業 PRD Writer — 受監管 / 金流 / 風控 / 跨職能團隊等級的產品需求文件撰寫與強化工具， 用於產出可直接進入 Refinement、Engineering Design、Development、QA 與 UAT 的 「施工藍圖」等級文件。相對於輕量版 prd-writer，此版本額外涵蓋權限矩陣、NFR、 依賴管理、合規、Analytics/Observability、Rollout/Migration/Rollback 與 UAT/Release Readiness。 預設以 interactive-html-report 規格輸出互動式 HTML（含常駐目錄側欄、捲動高亮）。 ⚠️ 版本選擇（重要）： 當使用者說「幫我寫 PRD」但未指明版本時，先問使用者要用「輕量版（prd-writer）」 還是「企業版（本 skill）」再開始。判斷提示：個人專案 / 單一功能 / 無合規需求 → 輕量版； 多團隊 / 金流 / 風控 / 合規 / 需上線維運全鏈路 → 企業版。使用者已明確指定版本時直接照做，不必再問。 當使用者提出以下需求時，應優先使用此 skill： 此 skill 的目標不是產出冗長文件，而是建立可執行、可測試、可追蹤、 可討論且邊界明確的產品規格，降低因需求模糊造成的返工與認知落差。 核心強制項目包含：
Implements Syncfusion .NET MAUI Cartesian Chart (SfCartesianChart) for data visualization with 20+ chart types including line, area, column, bar, financial, statistical, and stacked charts. Use when implementing cartesian charts, line charts, area charts, or financial charts (candle, OHLC). Covers chart axes, legends, tooltips, trackball, zooming and panning, and chart annotations.
Implements and customize Syncfusion .NET MAUI Funnel Charts (SfFunnelChart). Use when implementing funnel charts, sales funnel visualization, conversion funnel analysis, process stage visualization, or marketing funnel tracking. Covers funnel chart implementation, customization, data labels, legends, tooltips, segment spacing, and orientation.
Implements Syncfusion .NET MAUI Circular Charts (SfCircularChart) including pie, doughnut, and radial bar chart types. Use when implementing circular data visualization, pie charts, doughnut charts, or radial bar charts. Ideal for percentage breakdowns, category comparisons, part-to-whole relationships, or displaying proportional data in circular format.
Implements Syncfusion .NET MAUI Linear ProgressBar (SfLinearProgressBar) control. Use when working with progress bars, progress indicators, loading indicators, determinate/indeterminate progress, or buffer progress visualization. Covers progress tracking, multi-segment progress, animated progress, and gradient progress bars.
Implements Syncfusion .NET MAUI Polar Charts (SfPolarChart) for visualizing data in polar coordinates. Use when working with polar charts, radar charts, spider charts, web charts, or circular data visualization. Ideal for displaying data in terms of values and angles, creating line or area series in polar layouts, or comparing multiple data series radially.
Implements Syncfusion .NET MAUI Pyramid Chart (SfPyramidChart) for visually representing hierarchical, proportional, and parts-to-whole data using pyramid-shaped segments. Use this for pyramid charts, hierarchical data visualization, proportional data display, or segment-based charts. This skill covers installation, data binding, legends, tooltips, data labels, appearance customization, and gradients.
Implements Syncfusion .NET MAUI Sunburst Chart (SfSunburstChart) for hierarchical data visualization using a radial, multi-level circular layout. Use this for sunburst charts, radial hierarchical charts, multi-level pie charts. Ideal for visualizing organizational structures, file systems, or nested categorical data.
Use this skill ALWAYS when the user needs to implement Syncfusion MAUI Spark Charts. Triggers on spark chart, sparkline, micro-chart, trend visualization, data visualization in small spaces, chart types (line, area, column, win/loss), markers, range bands, axis configuration, data point styling. Also use immediately for chart customization, performance optimization, marker configuration, data binding patterns, accessibility needs.
Automates Microsoft Excel on macOS via JXA with AppleScript dictionary discovery. Use when asked to "automate Excel spreadsheets", "JXA Excel scripting", "Excel macOS automation", or "bulk Excel data operations". Focuses on workbooks, worksheets, ranges, 2D arrays, performance toggles, and VBA escape hatches.
Automates Apple Keynote using JXA with AppleScript dictionary discovery. Use when asked to "create Keynote presentations", "automate slide decks", "JXA Keynote scripting", or "generate presentations programmatically". Covers document lifecycle, slides, text, shapes, images, tables, charts, transitions, and UI scripting fallback.
Automates Apple Numbers via JXA with AppleScript dictionary discovery. Use when asked to "automate Numbers spreadsheets", "create spreadsheets programmatically", "JXA Numbers scripting", or "bulk data operations in Numbers". Focuses on sheets, tables, ranges, batch I/O, clipboard shim, and high-performance data workflows.
> data problem, explore and audit datasets, run defensible statistical analysis, build and validate predictive models, and turn results into decision-ready reports. Use this skill whenever the user asks to analyze, explore, or profile a dataset or CSV/Parquet/Excel file; asks what drives a metric or why a number changed ("why did churn go up?"); wants to test whether a difference is real (A/B tests, experiments, "is this significant?", "how many samples do I need?"); wants a predictive model (churn, forecast, scoring, segmentation, classification, regression); asks to review an existing analysis, notebook, or model for flaws; or needs analysis results written up for decision-makers — in any language ("phân tích dữ liệu", "xây model dự đoán", "kiểm định A/B"), even when they never say "data science" or "statistics".
> Investigate distributed traces and spans in OpenSearch. Use this skill when the user wants to analyze traces, investigate slow spans, find error spans, track agent invocations, measure token usage, reconstruct trace trees, query service maps, or debug distributed systems through trace data. Activate even if the user says traceId, spanId, OpenTelemetry, OTel, distributed tracing, latency, span duration, service map, or trace investigation without mentioning OpenSearch.