GitHub
sqlmesh-expert
Use when working with SQLMesh projects - creating models, reviewing plans, validating changes, debugging failures, or deploying to production environments.
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tools data analysis AI Skills
Discover tools data analysis skills, compare source repositories and read the instructions for each workflow.
Categories: tools data analysis
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GitHub
data-analysis
Data analysis and visualization expert using Python pandas and visualization libraries
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GitHub
kc-docs
Generate intelligent Python project documentation with UML class diagrams, architecture diagrams, and code analysis. Analyzes codebase structure to recommend and create appropriate visualizations for project ov...
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GitHub
mermaid-diagram
Generate well-structured Mermaid diagrams for visual documentation. Use when designing systems, documenting workflows, creating architecture diagrams, or any task requiring visual representation of processes, r...
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GitHub
clio-clustering
Build a complete data clustering and visualization pipeline from any data source. Use when the user wants to analyze patterns in text data (GitHub issues, Slack messages, support tickets, code reviews, forum po...
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GitHub
ad-assessment-documents
Professional document generator for Active Directory health assessments. Creates executive-quality DOCX reports with consistent branding, proper data visualization, severity-based formatting, and actionable rem...
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GitHub
test-report
テスト結果報告書を作成する。テスト完了後の結果報告、品質レビュー時に使う。
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GitHub
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.
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GitHub
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.
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GitHub
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 drive...
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GitHub
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.
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GitHub
funnel-analysis
Conversion funnel analysis with drop-off investigation. Use when analyzing multi-step processes, identifying conversion bottlenecks, A/B testing funnel performance, or optimizing user journeys.
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GitHub
visualization-builder
Create effective, publication-ready data visualizations. Use when choosing chart types, designing dashboards, creating presentation visuals, or building interactive visualizations with best practices.
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GitHub
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.
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GitHub
schema-mapper
Database schema understanding and relationship mapping. Use when exploring unfamiliar databases, documenting table relationships, identifying join paths, or generating ERD documentation for existing schemas.
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GitHub
metric-reconciliation
Cross-source metric validation and discrepancy investigation. Use when metrics from different sources don't match, investigating data quality issues between systems, or validating data migration accuracy.
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GitHub
analysis-documentation
Structured, reproducible analysis documentation. Use when documenting analysis findings, creating analysis notebooks, ensuring reproducibility, or building analysis archives for future reference.
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GitHub
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.
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GitHub
cohort-analysis
Time-based cohort analysis with retention and behavior tracking. Use when analyzing user retention over time, comparing cohort performance, identifying lifecycle patterns, or measuring feature adoption by cohor...
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GitHub
data-narrative-builder
Build compelling data-driven narratives and stories. Use when presenting analysis results, creating reports, or communicating data insights through storytelling frameworks.
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GitHub
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.
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GitHub
programmatic-eda
Systematic exploratory data analysis following best practices. Use when analyzing any dataset to understand structure, identify data quality issues (duplicates, missing values, inconsistencies, outliers), exami...
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GitHub
data-quality-audit
Comprehensive data quality assessment against defined business rules and constraints. Use when validating data against expected schemas, checking referential integrity across tables, or auditing data pipeline o...
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GitHub
query-validation
SQL query review and validation for correctness, performance, and best practices. Use when reviewing queries for logical errors, optimizing query performance, checking for SQL anti-patterns, or validating busin...
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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.