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Cursor Model Selection

cursor-model-selection

jeremylongshore/claude-code-plugins-plus-skills

Configure and select AI models inside Cursor by reviewing available providers, matching models to task needs, setting defaults, and managing per-conversation choices while keeping costs efficient.

Feature Engineering Toolkit

engineering-features-for-machine-learning

jeremylongshore/claude-code-plugins-plus-skills

Feature Engineering Toolkit automates creating, selecting, and transforming dataset features to improve machine learning models; use it whenever you need new interactions, automatic selection, scaling, or encoding to boost accuracy and interpretability.

Exa Cost Optimization Guide

exa-cost-tuning

jeremylongshore/claude-code-plugins-plus-skills

Guides teams through reducing Exa AI search API bills by adding query caching, picking cost-effective search types, limiting result counts, deduplicating batch queries, and monitoring budget and usage alerts.

Firebase Vertex AI Hub

firebase-vertex-ai

jeremylongshore/claude-code-plugins-plus-skills

Guide to architect and deploy Firebase projects that securely call Vertex AI/Gemini from Cloud Functions, covering Auth, Firestore, Hosting, observability, and ops guardrails for production readiness.

GPTQ LLM Quantization

Orchestra-Research/AI-Research-SKILLs

Post-training 4-bit quantization for LLMs that trims memory by 4× with minimal perplexity loss, enabling 70B+ models to run faster on consumer GPUs while integrating with transformers, PEFT, and QLoRA workflows.

Groq Cost Tuning

groq-cost-tuning

jeremylongshore/claude-code-plugins-plus-skills

Guide to reducing Groq inference spend by routing requests to cost-effective models, trimming token usage, caching repeated calls, batching requests, and setting spend limits for Groq Cloud billing scenarios.

Groq Multi-Environment Config

groq-multi-env-setup

jeremylongshore/claude-code-plugins-plus-skills

Sets up Groq LLM API clients for development, staging, and production tiers with tailored models, retries, and rate-limit handling so deployments stay aligned with each environment’s speed and cost profile.

Ideogram Cost Tuning

ideogram-cost-tuning

jeremylongshore/claude-code-plugins-plus-skills

Guides selection of Ideogram models, resolutions, caching, batching, and monitoring to lower per-image credits while maintaining quality; ideal for billing analysis or budget-aware teams using Ideogram image generation.

Kling AI Pitfall Guide

klingai-known-pitfalls

jeremylongshore/claude-code-plugins-plus-skills

A quick reference for developers to manage common mistakes when integrating Kling AI, covering troubleshooting steps, best practices, async patterns, secure credential usage, and cost controls for more reliable implementations.

Klingai Video Models

klingai-model-catalog

jeremylongshore/claude-code-plugins-plus-skills

Guides users through Kling AI’s video generation models, comparing capabilities, advising on tradeoffs (quality, speed, cost), and suggesting how to test and select the best model for specific use cases.

KlingAI Performance Tuning

klingai-performance-tuning

jeremylongshore/claude-code-plugins-plus-skills

Optimize Kling AI for faster generations, higher output quality, and lower costs by benchmarking current behavior, identifying bottlenecks, applying targeted improvements, and validating gains with after-action measurements.

LLM Knowledge Distillation

knowledge-distillation

Orchestra-Research/AI-Research-SKILLs

Compress large language models via teacher-student distillation, covering temperature scaling, soft targets, reverse KLD, and response distillation so you can deploy smaller LLMs with GPT-4-level behavior and lower inference cost.

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