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
Expert-level Business Analyst skill covering requirements analysis, process modeling, data analysis, stakeholder management, and solution assessment. Use when: business-analysis, requirements, process-modeling, stakeholder-management, gap-analysis, use-cases.
Expert-level Data Analyst skill covering SQL analysis, Python/pandas data manipulation, statistical analysis, A/B test design and interpretation, business intelligence, dashboard design, and data storytelling
Expert Test Prep Instructor specializing in SAT, ACT, GRE, GMAT, LSAT, and professional certification exam preparation. Expert in test-taking strategies, content review, performance analytics, and score improvement methodologies. Use when: test-prep, sat, act, gre, gmat, lsat, exam-prep, test-strategies, score-improvement.
Create and manipulate Excel XLSX files programmatically. Use when the user needs to generate spreadsheets, modify XLSX templates, extract spreadsheet content, or automate Excel workflows. Supports both template-based generation (for branding compliance) and from-scratch creation. Keywords: Excel, XLSX, spreadsheet, workbook, worksheet, data, report, template, financial, analysis.
Maintain and debug the link-curator web dashboard (port 8090). Separate process from the official Hermes dashboard.
Analyzes CSV files and automatically generates comprehensive summaries with statistical insights, data quality checks, and visualizations using Python and pandas. No questions asked — just upload a CSV and get a full analysis immediately.
Create interactive, custom data visualizations using d3.js — including charts, graphs, network diagrams, and geographic maps. Use when you need fine-grained control over visual elements, transitions, or interactions beyond what standard charting libraries offer, in any JavaScript environment (vanilla JS, React, Vue, Svelte, etc.).
Generate candlestick price charts for any asset from existing OHLC data, without handling data fetching.
Transform data between JSON, CSV, and other formats with filtering, mapping, and flattening. Use when: (1) Converting API responses to CSV, (2) Processing data pipelines, (3) Extracting specific fields, or (4) Flattening nested structures.
Generate a clean white Tailwind CDN report page from user content, optionally password-gate viewing via client-side decryption, and deploy to Originless/IPFS.
Analyze Google Maps review data from CSV exports. Sentiment analysis, trend detection, competitor review comparison, and reputation insights — no API key needed.
Analyze local competitors from a Google Maps CSV export. Compare ratings, reviews, digital presence, and positioning. Find market gaps and opportunities without any API calls.
Export Google Maps business data to CSV, JSON, or CRM format (HubSpot, Pipedrive, Salesforce). Bulk export with custom field mapping and filtering.
>- Research and analyze urban design precedents systematically. Generates structured case study reports with quantitative metrics, design principles, lessons learned, and transferability assessment. Use when the user asks for precedents, case studies, reference projects, comparable developments, benchmarks from other cities, examples of similar projects, or best practice examples. Also use when the user names a specific urban project and wants it analyzed as a precedent.
>- Python computational tools for urban design metric calculations including density, FAR, walkability scoring, parking requirements, green space analysis, and block optimization. Use when the user asks to calculate density, compute FAR, score walkability, determine parking requirements, analyze green space provision, optimize block dimensions, run urban metrics, or perform any quantitative urban design calculation. Also use when precise numbers are needed for any urban design metric rather than rules of thumb.
Complete CoinGecko Solana API integration for token prices, DEX pool data, OHLCV charts, trades, and market analytics. Use for building trading bots, portfolio trackers, price feeds, and on-chain data applications.
Real-time smart money analytics API for Polymarket prediction markets, Hyperliquid perpetual futures, and Meteora Solana LP/AMM pools. 63 endpoints. Pay-per-request via x402 on Solana Mainnet USDC. No API keys.
Use for GEPA reflective optimization, ReAct agent optimization, feedback metrics, LLM reflection, and execution trajectories.
Use for evaluating DSPy programs with Evaluate, answer_exact_match, SemanticF1, custom metrics, baselines, and program comparisons.
Use when X Analytics CSV exports must be inspected, validated, normalized, imported, or compared through a repeatable private-by-default workflow.
Create, revise, and audit executive-ready strategy-consulting presentations as native, editable PowerPoint files. Use when turning topics, text, Markdown, Word, PDF, spreadsheets, CSV data, URLs, research, or an existing PPTX into a board, client, strategy, transformation, market-analysis, or McKinsey-style consulting deck; when applying a brand or PowerPoint template; or when checking a deck's storyline, evidence, charts, layout, and visual quality.
Work with Dynatrace dashboards - create, modify, query, and analyze dashboard JSON including tiles, layouts, DQL queries, variables, and visualizations.
Work with Dynatrace notebooks - create, modify, query, and analyze notebook JSON including sections, DQL queries, and visualizations.
>- Analyze dashboards and notebooks using Davis analyzers — anomaly detection, novelty scoring, and correlation. Use when the user references a specific Dynatrace dashboard or notebook (by URL, UUID, or name) and asks what it shows, which DQL queries it runs, whether a tile looks off, or wants to find anomalies, score novelty, or correlate its metrics. The trigger is a dashboard or notebook as the data source, not a general DQL question. This skill extracts timeseries queries efficiently without reading the full raw document JSON, then optionally runs Davis analyzers on the extracted metrics. "novelty score", "correlate metrics", "extract DQL from dashboard", "dashboard URL", "tile", "run-analyzer", "timeseries extraction", "Davis analyzer".
Core DQL syntax, pitfalls, query patterns, and query optimization. Load to write, build, fix, or OPTIMIZE a DQL query — prevents syntax errors and makes queries faster, more efficient, and cheaper (less data scanned = lower query consumption/cost per run). Covers fetch commands, data models, field namespaces, time alignment, entity/smartscape patterns, metric discovery, and performance/cost optimization (filter early, bucket filters, short time ranges, field selection, sampling, cardinality). Trigger: \"write/build/fix a DQL query\", \"DQL syntax\", \"query logs/spans/metrics\", \"create a timeseries\", \"optimize my DQL\", \"make my query faster/cheaper\", \"reduce DQL cost/consumption/scanned data\", \"keep DQL cost under control\". Do NOT use to explain an existing query or answer product questions. For MONITORING a tenant's ACTUAL query consumption/billing (how much queries cost, who scanned most, cost trends) use dt-platform-costs — this tunes the query text, not billing data.
Real User Monitoring (RUM) on Dynatrace — web and mobile frontends. Core Web Vitals, user sessions, page performance, mobile crashes, frontend errors, and frontend-backend linking. Query via `user.events`, `user.sessions`, and `dt.frontend.*` metrics. Does NOT cover synthetic monitoring (HTTP/browser/network checks) — that's a separate domain.
>- Analyzes observability signals from customer GenAI applications with DQL. Reads OpenTelemetry GenAI spans and LLM evaluation bizevents. (model, provider, tokens); cost/token analytics, usage attribution, and prompt caching; agent signals (tool calls, steps, failures, loop detection, Smartscape topology); conversation/session analytics; guardrails (blocked/truncated responses); and evaluation signals (quality, pass/fail). "cost per conversation", "who is driving token spend", "do I have prompt caching", "failing agent tool calls", "find runaway agents", "responses truncated or blocked", "failed evaluations", "am I hitting rate limits", "token throughput / TPM", "provider throttling or 429s". metrics (dt-obs-services), logs (dt-obs-logs), or non-GenAI tracing (dt-obs-tracing).
Predictive analytics for Dynatrace — time series forecasting with the timeseries-forecast tool, capacity saturation planning, trend and anomaly detection across hosts, services, and infrastructure.
>- Service performance monitoring with RED metrics (Rate, Errors, Duration) and runtime-specific telemetry for Java, .NET, Node.js, Python, PHP, and Go. Use when analyzing service health, SLA compliance, or runtime issues. "service mesh overhead", "JVM GC", "Java heap", "Node.js event loop", ".NET CLR", "Python threads", "PHP OPcache", "Go goroutines", "service performance", "p95 latency", "request failures", "database response time by name". Do NOT use for explaining existing queries, product documentation questions, infrastructure metrics (use dt-obs-hosts), log analysis (use dt-obs-logs), or distributed tracing workflows (use dt-obs-tracing).
This skill should be used when analyzing weekly price charts for stocks, stock indices, cryptocurrencies, or forex pairs. Use this skill when the user provides chart images and requests technical analysis, trend identification, support/resistance levels, scenario planning, or probability assessments based purely on chart data without consideration of news or fundamental factors.
> A standardized CLI wrapper for RDKit 3D/2D conformer generation that samples multiple conformers per molecule (ETKDGv3, default 10), optimizes each with a force field (MMFF94s/UFF), keeps the lowest-energy conformer, automatically falls back to 2D layout on total embedding failure with a printed warning, and writes results to SDF or XYZ format. USE WHEN you need to generate 3D (or 2D fallback) molecular geometries from SMILES datasets (.csv/.smi) for downstream tasks such as docking, visualization, or 3D-descriptor computation.
> A standardized CLI wrapper for RDKit molecular featurization workflows that handles physicochemical descriptor computation (outputs .csv) and molecular fingerprint extraction (outputs .npy or .csv), with built-in SMILES validation. USE WHEN you need to compute RDKit molecular descriptors or fingerprints from SMILES datasets (.csv/.smi), or when you want to list all available descriptor names and presets.
> Odoo 17 development reference for Python models and ORM (search, domain, read_group, compute fields), XML/CSV data and views, OWL/JS client code, QWeb reports, security (ACL, record rules, groups), cron and server actions, migrations and module upgrades, tests, i18n, and performance. Use this skill whenever work involves Odoo 17 or custom addons—even if the user only pastes a traceback, mentions addons/ or __manifest__.py, describes form/tree/kanban/XML errors, HTTP controllers, or business rules on models—including building features, fixing bugs, refactoring, or reviewing addon code.
> Odoo 16 development reference for Python models and ORM (search, domain, read_group, compute fields), XML/CSV data and views, OWL/JS client code, QWeb reports, security (ACL, record rules, groups), cron and server actions, migrations and module upgrades, tests, i18n, and performance. Use this skill whenever work involves Odoo 16 or custom addons—even if the user only pastes a traceback, mentions addons/ or __manifest__.py, describes form/tree/kanban/XML errors, HTTP controllers, or business rules on models—including building features, fixing bugs, refactoring, or reviewing addon code.
> Odoo 18 development reference for Python models and ORM (search, domain, read_group, compute fields), XML/CSV data and views, OWL/JS client code, QWeb reports, security (ACL, record rules, groups), cron and server actions, migrations and module upgrades, tests, i18n, and performance. Use this skill whenever work involves Odoo 18 or custom addons—even if the user only pastes a traceback, mentions addons/ or __manifest__.py, describes form/list/kanban/XML errors, HTTP controllers, or business rules on models—including building features, fixing bugs, refactoring, or reviewing addon code.
Generate charts: select type, extract data, render image.
Analyze Excel/CSV files with DuckDB SQL via bash.
Consulting-grade research reports: framework + final report.
Stand up the dashboard foundation (the platform layer — UI primitives, form system, charts, Repository + adapters, auth seam, theme, routing shell) into a new project as a zero-config runnable app. Run this FIRST when building a dashboard, then compose screens from the add-component catalogue's shapes (add-detail-page, add-kanban, …) and the add-backend operation skill.
Add a copy-ready admin UI building block to a dashboard built on the scaffold-dashboard base — forms (form, wizard, combobox, file upload, inline edit), lists & tables (CRUD list, card grid, infinite/virtual, column controls, filter panel, saved views, CSV export/import), rich views (kanban, calendar, tree, timeline, master-detail), detail & pages (detail/show, record tabs, related records, multi-column layout, settings, chart/dashboard), display & feedback (tags/metadata/progress, empty/loading/error states, notification center, audit trail), and platform features (RBAC, social/magic-link auth, ⌘K global search, i18n, billing, realtime). Each entry has a reference doc with the exact copy + rewire steps.
Turn rich agent answers and any file, folder, URL, or export into a polished single-file HTML page. Auto-picks a default route plus 17 concrete design systems (teaching, dashboard, atlas, timeline-story, document, …).
>- Runs real-user QA, manual test plans, UX bug hunts, build sign-off, bug filing, and bug triage for web or iOS/iPadOS apps. Use when asked "QA this", "is this ready to ship?", or similar. Produces P0/P1/P2 bug reports, YES/NO phase sign-off, tracker sync guidance, and an HTML QA dashboard; keeps Interactive BRB triage in a separate session.
| (1) User provides a Snowflake query_id (UUID format) to analyze or optimize (2) Task mentions "slow query", "optimize", "query history", or "query profile" with a query ID (3) Analyzing query performance metrics - bytes scanned, spillage, partition pruning (4) User references a previously run query that needs optimization Fetches query profile, identifies bottlenecks, returns optimized SQL with expected improvements.
| (1) User asks to find slow, expensive, or problematic queries (2) Task mentions "query history", "top queries", "most expensive", or "slowest queries" (3) Analyzing warehouse costs or identifying optimization candidates (4) Finding queries that scan the most data or have the most spillage Returns ranked list of queries with metrics and optimization recommendations.
Create testimonial and proof systems for websites. Use for testimonials, reviews, customer quotes, logo walls, metrics, press quotes, case-study excerpts, ratings, social proof, proof strips, trust sections, and copy that must be credible, approved, and specific.
Full health check of all your skills in one report. Use when the user wants to check for errors, find duplicates, detect broken skills, or get a complete overview of skill health. Pass --brief for inventory only. Trigger with '/janitor-report'.
Agent-callable Google Analytics 4 (GA4) tools — run analytics reports, discover the dimensions and metrics a property supports, navigate accounts and properties, manage key events and custom dimensions/metrics, and send Measurement Protocol events. Use when the user mentions Google Analytics or GA4, or wants website/app traffic, conversion, or reporting data — including requests that don't name GA4 explicitly, e.g. how many users visited last week, top pages by country.
Agent-callable Google Sheets tools — read and write spreadsheet data as rows or raw cells, manage worksheets and columns, and apply formatting, sorting, and validation. Use when the user mentions Google Sheets or wants to read, add, update, look up, or organize spreadsheet data, even if they don't name Sheets explicitly.