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blockchain data analysis AI Skills

Discover blockchain data analysis skills, compare source repositories and read the instructions for each workflow.

Categories: blockchain data analysis

Showing 793–816 of 2,217

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GitHub

cfn-cerebras-mcp

masharratt

FAST code generation via mcp__cerebras-mcp__write tool using Z.ai glm-4.6. Use for rapid test generation, boilerplate creation, and bulk code tasks in main chat. Prompt must be SHORTER than output. Ideal for te...

GitHub

roi-calculator

dkyazzentwatwa

Calculate ROI for marketing campaigns, investments, and business decisions. Includes break-even analysis, payback period, and comparative ROI.

GitHub

territory-mapper

dkyazzentwatwa

Use when asked to visualize sales territories, coverage areas, service regions, or geographic boundaries on interactive maps.

GitHub

correlation-explorer

dkyazzentwatwa

Find and visualize correlations between variables in datasets. Use for data exploration, feature selection, or identifying relationships between columns.

GitHub

org-chart-generator

dkyazzentwatwa

Generate organizational hierarchy charts from CSV, JSON, or nested data. Supports multiple layouts, department coloring, and PNG/SVG/PDF export.

GitHub

geo-visualizer

dkyazzentwatwa

Create interactive maps with markers, heatmaps, routes, and choropleth layers. Use when visualizing geographic data, plotting locations, or creating map-based reports.

GitHub

statistical-analyzer

dkyazzentwatwa

Perform statistical hypothesis testing, regression analysis, ANOVA, and t-tests with plain-English interpretations and visualizations.

GitHub

financial-calculator

dkyazzentwatwa

Financial calculations: loans, investments, NPV/IRR, retirement planning, Monte Carlo simulations. Generates tables, charts, and exportable reports.

GitHub

outlier-detective

dkyazzentwatwa

Detect anomalies and outliers in datasets using statistical and ML methods. Use for data cleaning, fraud detection, or quality control analysis.

GitHub

sentiment-analyzer

dkyazzentwatwa

Analyze text sentiment (positive/negative/neutral) with confidence scores, emotion detection, and visualization. Supports single text, CSV batch, and trend analysis.

GitHub

sankey-diagram-creator

dkyazzentwatwa

Create interactive Sankey diagrams for flow visualization from CSV, DataFrame, or dict data. Supports node/link styling and HTML/PNG/SVG export.

GitHub

data-storyteller

dkyazzentwatwa

Transform CSV/Excel data into narrative reports with auto-generated insights, visualizations, and PDF export. Auto-detects patterns and creates plain-English summaries.

GitHub

dataset-comparer

dkyazzentwatwa

Compare two datasets to find differences, added/removed rows, changed values. Use for data validation, ETL verification, or tracking changes.

GitHub

report-generator

dkyazzentwatwa

Generate professional PDF/HTML reports with charts, tables, and narrative from data. Supports templates, branding, and automated report generation.

GitHub

ab-test-calculator

dkyazzentwatwa

Calculate statistical significance for A/B tests. Sample size estimation, power analysis, and conversion rate comparisons with confidence intervals.

GitHub

survey-analyzer

dkyazzentwatwa

Analyze survey responses with Likert scale analysis, cross-tabulations, sentiment scoring, and frequency distributions with visualizations.

GitHub

clustering-analyzer

dkyazzentwatwa

Cluster data using K-Means, DBSCAN, hierarchical clustering. Use for customer segmentation, pattern discovery, or data grouping.

GitHub

expense-report-generator

dkyazzentwatwa

Generate formatted expense reports from receipt data or CSV. Create professional PDF reports with categorization, totals, and approval workflows.

GitHub

time-series-decomposer

dkyazzentwatwa

Decompose time series into trend, seasonal, and residual components. Use for forecasting, pattern analysis, and seasonality detection.

GitHub

table-extractor

dkyazzentwatwa

Extract tables from PDFs and images to CSV or Excel. Support for scanned documents with OCR, multi-page PDFs, and complex table structures.

The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.

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