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Backtesting Trading Strategies Framework

backtesting-trading-strategies

jeremylongshore/claude-code-plugins-plus-skills

This comprehensive framework allows users to validate and test both crypto and traditional trading strategies against extensive historical market data. It calculates essential performance metrics (Sharpe Ratio, Sortino Ratio, Max Drawdown), simulates trade execution, generates equity curves, and includes advanced parameter grid search optimization tools for robust strategy validation.

PostHog Cost Optimization and Sampling

posthog-cost-tuning

jeremylongshore/claude-code-plugins-plus-skills

This skill provides advanced techniques for optimizing PostHog Cloud usage and reducing associated costs. It covers auditing event volume, implementing intelligent event sampling (e.g., sampling pageviews or autocapture events), filtering bot traffic, and tuning session recording rates. The goal is to maintain critical analytical value while staying within budget limits.

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.

Hybrid Parsing: Regex vs LLM Decision Framework

regex-vs-llm-structured-text

affaan-m/everything-claude-code

A practical decision framework for determining whether to use regular expressions or Large Language Models (LLMs) when parsing structured text (e.g., forms, quizzes, invoices). It recommends starting with deterministic, low-cost regex for 95-98% of structured data, and only invoking expensive LLM calls for identifying and validating ambiguous edge cases, optimizing both cost and accuracy.

Automatic Visa Document Translation Tool

visa-doc-translate

affaan-m/everything-claude-code

This comprehensive tool automates the process of translating non-English official documents (images) for visa applications. It handles image preprocessing (conversion and rotation), performs robust OCR using multiple frameworks, translates the extracted text into professional English while maintaining document structure, and generates a certified bilingual PDF containing both the original image and the formatted translation.

Insider Threat Investigation Workflow

performing-insider-threat-investigation

mukul975/Anthropic-Cybersecurity-Skills

This comprehensive guide outlines a structured workflow for investigating insider threats—incidents where authorized employees or contractors misuse their access to steal data or sabotage systems. It integrates DLP alerts, User Behavior Analytics (UBA), and digital forensics, emphasizing mandatory collaboration between Legal, HR, and Security teams to build an admissible, evidence-based case.

Structured Knowledge Extraction From AI Models

bdistill-knowledge-extraction

sickn33/antigravity-awesome-skills

bdistill transforms AI interactions into a structured, queryable knowledge base. It extracts, structures, and quality-scores domain knowledge from both closed-source AI models (in-session) and local open-source models (via Ollama). Users can build comprehensive reference datasets, Q&A pairs, or generate structured training data for traditional machine learning, ensuring validated and exportable domain expertise.

Chemical And Numerical Matching For Biology

bio-chemical-numeric

EverMind-AI/EverOS

This technique guides users to use precise chemical compound names, specific concentration values (e.g., "1.5 mg/L"), and taxonomic synonym counts as exact-match search anchors when querying biological literature. By leveraging quotation marks and combining multiple specific terms, it uniquely identifies research papers or species details, greatly improving search precision in biochemistry and botany.

Bioinformatics Database Query Tool

K-Dense-AI/scientific-agent-skills

gget is a comprehensive command-line and Python package providing unified access to over 20 major bioinformatics databases. Users can perform deep analyses across genomics, proteomics, and disease associations. Key functions include gene information lookups, sequence alignment (BLAST), structural prediction (AlphaFold), single-cell analysis, and enrichment studies, supporting both interactive queries and automated pipelines.

Explaining Machine Learning Model Predictions

K-Dense-AI/scientific-agent-skills

SHAP (SHapley Additive exPlanations) is a powerful technique used to interpret and audit machine learning model predictions. It calculates feature attributions (SHAP values) to explain how input features map to model outputs. This skill guides users through selecting appropriate explainers, handling multi-output models, validating feature attributions, and generating visualizations for both local and global model understanding.

Scraping Dynamic Data With Bright Data

brightdata-core-workflow-a

jeremylongshore/claude-code-plugins-plus-skills

Utilize Bright Data's Scraping Browser with Playwright or Puppeteer to reliably scrape structured data from JavaScript-rendered pages, Single Page Applications (SPAs), and anti-bot-protected sites. This tool manages proxy routing, CAPTCHA solving, and fingerprint management, ensuring robust data collection from complex web environments.

Collect ClickHouse Diagnostic Bundle

clickhouse-debug-bundle

jeremylongshore/claude-code-plugins-plus-skills

This tool collects comprehensive diagnostic data from ClickHouse system tables. It gathers crucial metrics, query logs, merge statuses, and disk usage information. It is essential for troubleshooting performance bottlenecks, preparing detailed support tickets, or investigating complex database infrastructure issues.

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