数据分析

浏览数据处理、可视化和分析的 agent skills。使用强大工具从数据中提取洞察。

social-media-dashboard

nexu-io/open-design

Creator-facing social media analytics dashboard in a single HTML file. A platform switcher (X / LinkedIn / YouTube / Instagram), a row of KPI cards (followers, engagement rate, likes, reposts), a follower-growth chart, a "top post this week" preview, and a trending topics / top comments side panel. Use when the brief mentions a "social media dashboard", "creator analytics", "social analytics", or names specific platforms (X, Twitter, LinkedIn, YouTube, Instagram, TikTok) together with metrics like followers, engagement, likes, reposts.

social-media-matrix-tracker-template

nexu-io/open-design

社媒矩阵数据追踪面板模板（Social Media Matrix Tracker）。 Use when users ask for a cinematic, data-dense social media analytics dashboard with multi-platform metrics, interactive charts, hover insights, range compare, and dark/light theme switching in a single HTML artifact.

social-media-dashboard

nexu-io/open-design

Creator-facing social media analytics dashboard in a single HTML file. A platform switcher (X / LinkedIn / YouTube / Instagram), a row of KPI cards (followers, engagement rate, likes, reposts), a follower-growth chart, a "top post this week" preview, and a trending topics / top comments side panel. Use when the brief mentions a "social media dashboard", "creator analytics", "social analytics", or names specific platforms (X, Twitter, LinkedIn, YouTube, Instagram, TikTok) together with metrics like followers, engagement, likes, reposts.

social-media-matrix-tracker-template

nexu-io/open-design

社媒矩阵数据追踪面板模板（Social Media Matrix Tracker）。 Use when users ask for a cinematic, data-dense social media analytics dashboard with multi-platform metrics, interactive charts, hover insights, range compare, and dark/light theme switching in a single HTML artifact.

video-template-frame-nyt-graph

nexu-io/open-design

Use this plugin when the user wants a "NYT Graph" HyperFrames motion video — Animated data chart in print editorial style

video-template-frame-pentagram-stat

nexu-io/open-design

Use this plugin when the user wants a "Pentagram Stat Frame" HyperFrames motion video — Swiss-grid statistic anchor — giant number, red accent, growing bars, black data bar. Rational and editorial.

understand-knowledge

Egonex-AI/Understand-Anything

Analyze a Karpathy-pattern LLM wiki knowledge base and generate an interactive knowledge graph with entity extraction, implicit relationships, and topic clustering.

check-forecast-signals

koala73/worldmonitor

Retrieve probabilistic forecasts and their scorecard context. Use when the user asks what World Monitor is forecasting, how probabilities shifted, or how calibrated the forecasts are.

datawhalechina/hello-agents

基于东方财富权威数据库的金融数据查询工具，支持行情、财务及关联关系数据。

Run the corpus benchmark — booster locally, optional Gemini/Sonnet/Opus baselines — and persist a verifiable measured-vs-claimed table

cost-compact-context

Wrap getTokenOptimizer().getCompactContext() to retrieve compacted ReasoningBank context for cost-analysis queries; report bridge-reported tokensSaved

Extract entities and relations from source files to build a knowledge graph

Ingest and normalize market data into OHLCV vectors with HNSW indexing

observe-metrics

Aggregate and display system metrics with anomaly detection for a time period

SOTA semantic search — hybrid (sparse+dense), Graph RAG multi-hop, MMR diversity reranking, recency weighting

Hmbown/CodeWhale

Choose and produce an appropriate chart/dashboard/visual explanation from data, with legible encodings and source/assumption notes.

K-Dense-AI/scientific-agent-skills

Low-level plotting library for full customization. Use when you need fine-grained control over every plot element, creating novel plot types, or integrating with specific scientific workflows. Export to PNG/PDF/SVG for publication. For quick statistical plots use seaborn; for interactive plots use plotly; for publication-ready multi-panel figures with journal styling, use scientific-visualization.

scientific-visualization

K-Dense-AI/scientific-agent-skills

Create and audit truthful, accessible, publication-ready scientific figures with Matplotlib, Seaborn, or Plotly. Use for figure design, multi-panel layouts, uncertainty and missing-data displays, color/contrast review, image metadata validation, and journal export planning.

K-Dense-AI/scientific-agent-skills

Statistical visualization with pandas integration. Use for quick exploration of distributions, relationships, and categorical comparisons with attractive defaults. Best for box plots, violin plots, pair plots, heatmaps. Built on matplotlib. For interactive plots use plotly; for publication styling use scientific-visualization.

K-Dense-AI/scientific-agent-skills

Explain and audit machine-learning predictions with SHAP. Use for selecting SHAP explainers and maskers, computing and validating feature attributions, handling multi-output explanations, and producing local or global SHAP visualizations.

statistical-analysis

K-Dense-AI/scientific-agent-skills

Guided statistical analysis for research data - test selection, assumption checking, effect sizes, power analysis, Bayesian alternatives, and APA-formatted reporting. Use whenever a user wants to compare groups, test a hypothesis, analyze experimental or survey data, check statistical assumptions, compute required sample sizes, or write up results - even if they never name a specific test. Covers t-tests, ANOVA, chi-square, correlation, regression, non-parametric and Bayesian methods. For low-level model APIs, see the statsmodels and pymc skills.

statistical-power

K-Dense-AI/scientific-agent-skills

Sample-size and statistical power calculations for planning studies. Use whenever someone asks "how many subjects/samples/replicates do I need", wants an a priori power analysis, a minimum detectable effect (MDE), a power curve, or needs to justify a sample size for a grant, IRB protocol, or pre-registration. Covers closed-form power for t-tests, ANOVA, proportions, correlations, chi-square, and regression, plus simulation-based (Monte Carlo) power for designs with no formula — logistic/Poisson regression, mixed models, cluster-randomized trials, survival, and interactions. Use this skill even when the request only mentions an effect size, alpha, or "80% power" without saying "power analysis" explicitly. For laying out the study (randomization, blocking, factorial/DOE, crossover, sequential designs) use experimental-design; for analyzing data already collected and reporting it use statistical-analysis.

K-Dense-AI/scientific-agent-skills

Statistical models library for Python. Use when you need specific model classes (OLS, GLM, mixed models, ARIMA) with detailed diagnostics, residuals, and inference. Best for econometrics, time series, rigorous inference with coefficient tables. For guided statistical test selection with APA reporting use statistical-analysis.

Yuan1z0825/nature-skills

Create, revise, audit, and export submission-grade scientific figures for Nature-family and other high-impact venues in Python (matplotlib/seaborn) or R (ggplot2/patchwork/ComplexHeatmap), including multi-panel plots, figures4papers-style work, and journal-ready SVG/PDF/TIFF outputs. Use for paper or scientific plots, manuscript data visualization, 论文配图、学术写作配图、科研绘图、科研作图、画图、作图、出图、论文图表、可视化. Define the conclusion, evidence logic, data integrity, template compatibility, export needs, and reviewer risks before plotting; honor or persist the Python/R backend choice. Also use the separate OpenRouter GPT Image 2 route for explicit AI-generated graphical abstracts, mechanism diagrams, concept schematics, 论文示意图、机制示意图、图形摘要; this route skips backend choice and treats outputs as drafts. Do not use for interactive dashboards, statistics-only analysis, data cleaning, literature review, code debugging, pure photo editing, or Illustrator/Figma-first infographics without manuscript-figure intent.

datacommons-client

davila7/claude-code-templates

Work with Data Commons, a platform providing programmatic access to public statistical data from global sources. Use this skill when working with demographic data, economic indicators, health statistics, environmental data, or any public datasets available through Data Commons. Applicable for querying population statistics, GDP figures, unemployment rates, disease prevalence, geographic entity resolution, and exploring relationships between statistical entities.

davila7/claude-code-templates

Interactive scientific and statistical data visualization library for Python. Use when creating charts, plots, or visualizations including scatter plots, line charts, bar charts, heatmaps, 3D plots, geographic maps, statistical distributions, financial charts, and dashboards. Supports both quick visualizations (Plotly Express) and fine-grained customization (graph objects). Outputs interactive HTML or static images (PNG, PDF, SVG).

scientific-visualization

davila7/claude-code-templates

Create publication figures with matplotlib/seaborn/plotly. Multi-panel layouts, error bars, significance markers, colorblind-safe, export PDF/EPS/TIFF, for journal-ready scientific plots.

davila7/claude-code-templates

Statistical visualization. Scatter, box, violin, heatmaps, pair plots, regression, correlation matrices, KDE, faceted plots, for exploratory analysis and publication figures.

statistical-analysis

davila7/claude-code-templates

Statistical analysis toolkit. Hypothesis tests (t-test, ANOVA, chi-square), regression, correlation, Bayesian stats, power analysis, assumption checks, APA reporting, for academic research.

speckit-git-feature

pmndrs/react-spring

Create a feature branch with sequential or timestamp numbering

getting-started

Create an Angular TanStack Table v9 table with injectTable inside injection context, explicit stable tableFeatures and columns, signal-backed data, and FlexRender structural directives or helpers.

Use Angular-signal-backed table.atoms, direct template reads, computed selectors, controlled signals, value-or-updater callbacks, and external Angular Store atoms while accounting for injectTable initializer reruns.

with-tanstack-query

Compose Svelte Query with Svelte Table manual filtering, sorting, and pagination using reactive query inputs, query-result data getters, server counts, and a single source of server-data truth.

Aggregate TanStack Table columns independently of grouping, including grand totals, caller-selected row totals, multiple keyed aggregations, custom context-based definitions, grouped merges, manual values, and worker constraints.

correlation-regime

HKUDS/Vibe-Trading

Correlation-regime detection and crisis attribution — edge-density regime states with hysteresis, causal (no look-ahead) smoothing, regime-aware exposure context, first-mover crisis attribution with honest NAME / MACRO / AMBIGUOUS / ABSTAIN verdicts, and a correlation-rewiring leaderboard that catches slow bleed-outs

quant-statistics

HKUDS/Vibe-Trading

Quantitative statistical methods: ADF unit-root / cointegration tests, GARCH volatility modeling, regression diagnostics (heteroskedasticity / autocorrelation), Bootstrap, and hypothesis testing.

technical-basic

HKUDS/Vibe-Trading

Core technical indicator collection (trend EMA/ADX + mean-reversion BB/RSI + volume-price OBV/volume ratio), generates a composite signal via three-dimensional voting. Pure pandas implementation for any OHLCV data.

recharts/recharts

Create visual regression tests

analyzing-apt-group-with-mitre-navigator

mukul975/Anthropic-Cybersecurity-Skills

Analyze advanced persistent threat (APT) group techniques using MITRE ATT&CK Navigator to create layered heatmaps of adversary TTPs for detection gap analysis and threat-informed defense.

analyzing-threat-landscape-with-misp

mukul975/Anthropic-Cybersecurity-Skills

Analyze the threat landscape using MISP (Malware Information Sharing Platform) by querying event statistics, attribute distributions, threat actor galaxy clusters, and tag trends over time. Uses PyMISP to pull event data, compute IOC type breakdowns, identify top threat actors and malware families, and generate threat landscape reports with temporal trends.

rohitg00/agentmemory

Search agentmemory for past observations, sessions, and learnings about a topic using hybrid BM25 plus vector plus graph search. Use when the user says "recall", "what did we do about", "did we ever", "have we seen", or needs context from past sessions.

anthropics/knowledge-work-plugins

Answer data questions -- from quick lookups to full analyses. Use when looking up a single metric, investigating what's driving a trend or drop, comparing segments over time, or preparing a formal data report for stakeholders.

build-dashboard

anthropics/knowledge-work-plugins

Build an interactive HTML dashboard with charts, filters, and tables. Use when creating an executive overview with KPI cards, turning query results into a shareable self-contained report, building a team monitoring snapshot, or needing multiple charts with filters in one browser-openable file.

anthropics/knowledge-work-plugins

Create publication-quality visualizations with Python. Use when turning query results or a DataFrame into a chart, selecting the right chart type for a trend or comparison, generating a plot for a report or presentation, or needing an interactive chart with hover and zoom.

data-visualization

anthropics/knowledge-work-plugins

Create effective data visualizations with Python (matplotlib, seaborn, plotly). Use when building charts, choosing the right chart type for a dataset, creating publication-quality figures, or applying design principles like accessibility and color theory.

statistical-analysis

anthropics/knowledge-work-plugins

Apply statistical methods including descriptive stats, trend analysis, outlier detection, and hypothesis testing. Use when analyzing distributions, testing for significance, detecting anomalies, computing correlations, or interpreting statistical results.

anthropics/knowledge-work-plugins

Reconcile accounts by comparing GL balances to subledgers, bank statements, or third-party data. Use when performing bank reconciliations, GL-to-subledger recs, intercompany reconciliations, or identifying and categorizing reconciling items.

officecli-data-dashboard

iOfficeAI/OfficeCLI

Use this skill to build a multi-element Excel dashboard — Dashboard sheet on open, multiple formula-driven KPI cards, multiple charts, sparklines, and conditional formatting — from CSV or tabular input. Trigger on: 'dashboard', 'KPI dashboard', 'analytics dashboard', 'executive dashboard', 'metrics dashboard', 'CSV to dashboard', 'data visualization'. Output is a single .xlsx. Scene-layer on officecli-xlsx: inherits every xlsx hard rule. DO NOT invoke for: a single budget tracker / one-sheet CSV-with-formatting (use xlsx), a 3-statement / DCF / LBO financial model (use financial-model), a weekly report with ≤ 1 chart and < 10 rows (use xlsx).