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Crypto Options Flow Analysis Tool

analyzing-options-flow

jeremylongshore/claude-code-plugins-plus-skills

This tool analyzes cryptocurrency options flow from major derivatives exchanges (e.g., Deribit). It tracks open interest, calculates put/call ratios, and analyzes implied volatility to identify institutional positioning, gauge market sentiment, and detect significant trading activity (block trades) in BTC and ETH options. It is essential for quantitative traders and market analysts seeking to predict market movements.

Crypto Options Flow Analysis Tool

analyzing-options-flow

jeremylongshore/claude-code-plugins-plus-skills

This tool analyzes cryptocurrency options flow from major derivatives exchanges (e.g., Deribit). It tracks open interest, calculates put/call ratios, and analyzes implied volatility to identify institutional positioning, gauge market sentiment, and detect significant trading activity (block trades) in BTC and ETH options. It is essential for quantitative traders and market analysts seeking to predict market movements.

AWQ Weight Quantization

awq-quantization

Orchestra-Research/AI-Research-SKILLs

Activation-aware weight quantization that compresses 7B-70B models to 4-bit with minimal accuracy loss, delivering ~3x inference speedups and memory reductions for constrained GPU deployments while integrating with vLLM and Marlin kernels.

Technical Debt Analysis and Remediation Plan

code-refactoring-tech-debt

sickn33/antigravity-awesome-skills

This expert skill analyzes codebases to identify, quantify, and prioritize all forms of technical debt—including code complexity, architectural flaws, outdated dependencies, and testing gaps. It calculates the measurable impact of this debt on development velocity, bug rates, and overall business risk. The output provides a comprehensive, actionable, and ROI-driven roadmap for systematic remediation.

Technical Debt Analysis And Remediation

codebase-cleanup-tech-debt

sickn33/antigravity-awesome-skills

A comprehensive expert system for analyzing software codebases to identify, quantify, and prioritize technical debt across various dimensions (code, architecture, testing, infrastructure). It provides detailed metrics, impact assessments (development velocity, quality loss), and actionable, prioritized remediation roadmaps with clear ROI projections.

Code Model Evaluation and Benchmarking

evaluating-code-models

Orchestra-Research/AI-Research-SKILLs

A comprehensive toolkit for evaluating the performance of code generation models. It supports benchmarking against industry standards like HumanEval, MBPP, and MultiPL-E across multiple languages. Use this tool to quantitatively compare different LLM coding abilities and measure code synthesis quality using pass@k metrics.

Detect Crypto Arbitrage Opportunities

finding-arbitrage-opportunities

jeremylongshore/claude-code-plugins-plus-skills

This tool detects profitable arbitrage opportunities across centralized exchanges (CEX), decentralized exchanges (DEX), and cross-chain markets in real-time. It aggregates price data, calculates net profit after fees, and identifies various arbitrage paths, including direct, triangular, and cross-chain opportunities. It is designed for quantitative traders needing to monitor market efficiency and exploit price discrepancies.

LLM Fine-Tuning Guide

fine-tuning-expert

Jeffallan/claude-skills

Guides ML engineers through dataset prep, PEFT strategy selection, LoRA/QLoRA adapter setup, training monitoring, and deployment checks for practical LLM fine-tuning, quantization, and adapter merge workflows.

GGUF Quantization for Efficient LLM Inference

gguf-quantization

Orchestra-Research/AI-Research-SKILLs

This guide details the use of the GGUF format and quantization techniques for running large language models (LLMs) efficiently. GGUF enables optimal inference on consumer hardware, Apple Silicon, and systems requiring CPU-only operation. By compressing models using various K-quant methods (like Q4_K_M), developers can significantly reduce memory footprint and hardware requirements while maintaining high performance.

GPTQ Quantization Guide

Orchestra-Research/AI-Research-SKILLs

GPTQ enables post-training 4-bit quantization for large LLMs, delivering up to 4× memory reduction and 3-4× faster inference with under 2% perplexity loss on consumer GPUs through AutoGPTQ, PEFT, and Transformer integrations.

Optimizing Granola Spending and ROI

granola-cost-tuning

jeremylongshore/claude-code-plugins-plus-skills

This comprehensive guide provides strategies to optimize your Granola spending. Learn how to calculate individual and team ROI by quantifying time saved, selecting the most appropriate plan (Basic, Business, or Enterprise) based on usage needs, auditing inactive seats, and implementing advanced billing strategies to maximize value and minimize costs.

Half-Quadratic Quantization

hqq-quantization

Orchestra-Research/AI-Research-SKILLs

Provides calibration-free weight quantization for LLMs down to 1-bit precision with multiple optimized backends, ideal for fast deployments with vLLM/HuggingFace and LoRA/PEFT fine-tuning without collecting calibration data.

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