Data & Analytics
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Browse skills in this category.
performing-causal-analysis
Data & Analyticsby pymc-labs
Fits causal models, estimates impacts, and plots results using CausalPy. Use when performing analysis with DiD, ITS, SC, or RD.
running-placebo-analysis
Data & Analyticsby pymc-labs
Performs placebo-in-time sensitivity analysis to validate causal claims. Use when checking model robustness, verifying lack of pre-intervention effects, or ensuring observed effects are not spurious.
working-with-marimo
Data & Analyticsby pymc-labs
Interactive development in marimo notebooks with validation loops. Use for creating/editing marimo notebooks and verifying execution.
insforge-schema-patterns
Data & Analyticsby InsForge
Database schema patterns for InsForge including social graphs, e-commerce, content publishing, and multi-tenancy with RLS policies. Use when designing data models with relationships, foreign keys, or Row Level Security.
github-archive
Data & Analyticsby gadievron
Investigate GitHub security incidents using tamper-proof GitHub Archive data via BigQuery. Use when verifying repository activity claims, recovering deleted PRs/branches/tags/repos, attributing actions to actors, or reconstructing attack timelines. Provides immutable forensic evidence of all public GitHub events since 2011.
aggregating-performance-metrics
Data & AnalyticsAggregate and centralize performance metrics from applications, systems, databases, caches, and services. Use when consolidating monitoring data from multiple sources. Trigger with phrases like "aggregate metrics", "centralize monitoring", or "collect performance data".
analyzing-logs
Data & AnalyticsAnalyze application logs for performance insights and issue detection including slow requests, error patterns, and resource usage. Use when troubleshooting performance issues or debugging errors. Trigger with phrases like "analyze logs", "find slow requests", or "detect error patterns".
analyzing-system-throughput
Data & AnalyticsAnalyze and optimize system throughput including request handling, data processing, and resource utilization. Use when identifying capacity limits or evaluating scaling strategies. Trigger with phrases like "analyze throughput", "optimize capacity", or "identify bottlenecks".