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Ab Test Analyzer

ab-test-analyzer

jeremylongshore/claude-code-plugins-plus-skills

Provides automated guidance for ab test analyzer workflows, covering SQL queries, visualization, statistical analysis, and BI validation so teams can run reliable experiments within data analytics contexts.

AB Test Setup Guide

coreyhaines31/marketingskills

Guides teams through planning, designing, and running statistically sound A/B tests with hypothesis framing, sample sizing, metric selection, implementation strategies, and analysis checkpoints for systematic growth experimentation.

Chaos Engineering Playbook

Jeffallan/claude-skills

Designs and executes chaos experiments, failure-injection frameworks, and game days for distributed systems, providing runbooks, manifests, rollback plans, and continuous resilience automation in CI/CD.

Chaos Engineering Experimentation

conducting-chaos-engineering

jeremylongshore/claude-code-plugins-plus-skills

Guides chaos engineering experiments by defining objectives, choosing tools such as Chaos Mesh, Gremlin, Toxiproxy, or AWS FIS, injecting failures, monitoring metrics, and recommending fixes to harden services and APIs.

Cross Validation Setup

cross-validation-setup

jeremylongshore/claude-code-plugins-plus-skills

Automates cross validation setup for ML training requests, offering best-practice guidance, production-ready code samples, and validation steps across data preparation, model tuning, and experiment tracking.

Data Augmentation Pipeline

data-augmentation-pipeline

jeremylongshore/claude-code-plugins-plus-skills

Guides ML training teams through data augmentation pipelines, offering best practices, code/config generation, validation, and experiment-tracking support so pipelines stay production-ready.

Data-Driven Feature Development

data-engineering-data-driven-feature

sickn33/antigravity-awesome-skills

Build features guided by data insights, A/B testing, and continuous measurement using specialized agents for analysis, implementation, and experimentation.

Databricks MLflow Workflow

databricks-core-workflow-b

jeremylongshore/claude-code-plugins-plus-skills

Guides ML engineers through the Databricks secondary workflow that links Feature Store engineering, MLflow experiment tracking, model registry versioning, and serving so production-grade models can be trained and deployed.

Systematic Debugging Strategies

debugging-strategies

sickn33/antigravity-awesome-skills

This skill provides a structured methodology for tackling complex bugs, performance bottlenecks, and production incidents. It guides users through reproducing issues, forming hypotheses, performing controlled experiments, and narrowing down the scope using proven strategies and tools. Ideal for deep dive troubleshooting and root cause analysis in complex software systems.

Early Stopping Callback

early-stopping-callback

jeremylongshore/claude-code-plugins-plus-skills

Automated guidance for configuring and applying early stopping callbacks across ML training workflows, covering best practices, code generation, and validation for PyTorch, TensorFlow, and scikit-learn experiments.

Evernote Hello World

evernote-hello-world

jeremylongshore/claude-code-plugins-plus-skills

Create and experiment with a minimal Evernote integration by scripting your first note, demonstrating ENML usage, note creation, listing notebooks, and retrieval flows for API learning or setup validation.

Feature Engineering Helper

feature-engineering-helper

jeremylongshore/claude-code-plugins-plus-skills

Automatically activates when you mention feature engineering helper, offering guidance on data preparation, model training, hyperparameter tuning, and experiment tracking for ML projects.

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