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Optimizing Juicebox API Performance

juicebox-performance-tuning

jeremylongshore/claude-code-plugins-plus-skills

This guide provides advanced strategies for optimizing interactions with the Juicebox AI API. It covers crucial best practices such as implementing caching mechanisms (with defined TTLs), executing batch operations for efficiency, managing rate limits, and optimizing data chunking for large datasets. Following these steps can significantly reduce end-to-end analysis time and ensure responsive, scalable data workflows.

AI Agent Observability and Metrics Monitoring

lindy-observability

jeremylongshore/claude-code-plugins-plus-skills

This guide details how to implement comprehensive observability for AI agents. It covers monitoring key metrics such as task success rates, step failures, execution duration, and credit consumption. Use this when setting up performance dashboards, configuring real-time alerts (via webhooks/Prometheus), or tracking agent reliability over time.

Regression Analysis Assistant

performing-regression-analysis

jeremylongshore/claude-code-plugins-plus-skills

Enables regression modeling via the regression-analysis-tool plugin by analyzing datasets, choosing linear or polynomial fits, validating models, and reporting metrics so users can predict outcomes or explore variable relationships.

Pipeline Monitoring Setup

pipeline-monitoring-setup

jeremylongshore/claude-code-plugins-plus-skills

Guides users through setting up monitoring for data pipelines, covering ETL, transformation, orchestration, streaming, and validation with best-practice code and configuration.

Capturing Events with PostHog SDKs

posthog-hello-world

jeremylongshore/claude-code-plugins-plus-skills

This guide provides minimal working examples demonstrating the three core PostHog functionalities: event capture, user identification, and feature flag evaluation. It covers both server-side (Node.js, Python) and client-side (JavaScript) SDK usage, as well as direct API calls, making it perfect for initial integration setup, testing, and learning basic product analytics patterns.

PostHog Webhook and Event Analysis

posthog-webhooks-events

jeremylongshore/claude-code-plugins-plus-skills

This skill guides you through integrating PostHog's Customer Data Platform (CDP) features. It covers setting up webhooks to trigger real-time actions (e.g., syncing to CRM, sending notifications) when specific user events occur. Furthermore, it demonstrates how to query event data using the Events API and perform complex funnel analysis using HogQL, allowing for deep, custom insights into user behavior.

Automated Data Preprocessing

preprocessing-data-with-automated-pipelines

jeremylongshore/claude-code-plugins-plus-skills

This skill builds and executes automated pipelines to clean, validate, and transform data for machine learning, covering ETL workflows, error handling, and quality reporting so Claude can deliver analysis-ready datasets.

Clustering Analysis Assistant

running-clustering-algorithms

jeremylongshore/claude-code-plugins-plus-skills

Automates clustering workflows on supplied datasets with K-means, DBSCAN, or hierarchical algorithms, handling preprocessing, validation, metrics, and visualizations to expose groupings and anomalies.

Crypto Market Movers Scanner

scanning-market-movers

jeremylongshore/claude-code-plugins-plus-skills

Detects real-time significant price movements and unusual volume spikes across cryptocurrency markets. It calculates a composite significance score by combining price change, volume ratio, and market cap. Use it to track top gainers, biggest losers, or identify sudden market pumps across thousands of assets, with filtering options for category and timeframe.

Schema Optimization Workflow Orchestrator

schema-optimization-orchestrator

jeremylongshore/claude-code-plugins-plus-skills

An advanced workflow orchestrator designed to perform multi-phase, deep-dive schema optimization on large datasets (e.g., BigQuery exports). It systematically analyzes schema structure, identifies unused or redundant fields, assesses potential impact, and generates a comprehensive, actionable report with recommended optimization strategies and estimated savings.

Dataset Splitter Tool

splitting-datasets

jeremylongshore/claude-code-plugins-plus-skills

Automates splitting datasets into training, validation, and test subsets by generating and running Python code so you can quickly prepare data for machine learning model training and evaluation.

TensorFlow Serving Setup

tensorflow-serving-setup

jeremylongshore/claude-code-plugins-plus-skills

Guides TensorFlow Serving setup with step-by-step ML deployment orchestration, enforcing best practices, ready-to-run configurations, and output validation for production inference services.

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