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CoreWeave GPU Cost Optimization Guide

coreweave-cost-tuning

jeremylongshore/claude-code-plugins-plus-skills

A comprehensive guide for optimizing cloud GPU expenditures on CoreWeave. Learn strategies like right-sizing instances, implementing scale-to-zero for development environments, and using quantization techniques (e.g., AWQ, GPTQ) to fit large models onto smaller, cost-effective GPUs, ensuring maximum efficiency and budget adherence for AI/ML workloads.

CoreWeave Resource Quota Management

coreweave-rate-limits

jeremylongshore/claude-code-plugins-plus-skills

This skill provides methods for managing GPU quota limits and rate restrictions for CoreWeave cloud services. It includes using `kubectl` to check resource quotas and demonstrates implementing robust request queuing mechanisms using Python's `asyncio` library, ensuring stable and efficient resource allocation for high-concurrency inference endpoints.

Securing CoreWeave GPU Workloads

coreweave-security-basics

jeremylongshore/claude-code-plugins-plus-skills

Provides comprehensive guidelines for securing CoreWeave cloud deployments on Kubernetes. Covers critical security areas including credential management, implementing Role-Based Access Control (RBAC), enforcing network isolation policies, and handling sensitive secrets for ML model access. Essential for hardening GPU workloads and protecting data in cloud environments.

ElevenLabs Cost Optimization and Monitoring

elevenlabs-cost-tuning

jeremylongshore/claude-code-plugins-plus-skills

This skill provides methods to optimize ElevenLabs usage costs for Text-to-Speech (TTS) workloads. It covers model selection (e.g., using Flash/Turbo for savings), implementing character-efficient text pre-processing to reduce character count, and setting up real-time quota monitoring with budget alerts. Ideal for developers managing high-volume, cost-sensitive voice applications.

Deploy ElevenLabs TTS to Cloud Platforms

elevenlabs-deploy-integration

jeremylongshore/claude-code-plugins-plus-skills

This guide provides comprehensive instructions and code examples for deploying ElevenLabs Text-to-Speech (TTS) applications to various cloud environments, including Vercel (serverless), Fly.io (containers), and Google Cloud Run. It covers best practices for managing platform-specific secrets, configuring timeouts, and implementing real-time streaming audio capabilities for production-grade voice applications.

ElevenLabs TTS API Integration Guide

elevenlabs-hello-world

jeremylongshore/claude-code-plugins-plus-skills

This comprehensive guide teaches you how to integrate and use the ElevenLabs Text-to-Speech (TTS) API. It provides multiple code examples (TypeScript, Python, cURL) for generating high-quality speech audio from text. Learn advanced features such as detailed voice parameter control, choosing optimal models (e.g., streaming vs. standard), and implementing low-latency streaming for real-time applications.

ElevenLabs Production Deployment Checklist

elevenlabs-prod-checklist

jeremylongshore/claude-code-plugins-plus-skills

A comprehensive checklist guiding the safe and robust deployment of Text-to-Speech (TTS) integrations powered by ElevenLabs into a live production environment. It covers critical steps including API configuration, implementing health checks, setting up circuit breakers for resilience, and establishing thorough monitoring and rollback procedures, ensuring reliable voice feature go-live.

ElevenLabs API Security Best Practices

elevenlabs-security-basics

jeremylongshore/claude-code-plugins-plus-skills

A comprehensive guide detailing security best practices for integrating with ElevenLabs. It covers secure API key management using environment variables, implementing Git pre-commit hooks, and demonstrating robust webhook signature verification using HMAC-SHA256. This ensures secure data handling, replay protection, and proper voice data governance.

Fathom API Cost Optimization Guide

fathom-cost-tuning

jeremylongshore/claude-code-plugins-plus-skills

This guide provides best practices for optimizing Fathom API usage and managing associated cloud costs. It covers strategies like implementing caching for transcripts, switching from API polling to webhooks, batching CRM writes, and establishing data retention policies (e.g., archiving after 90 days) to minimize unnecessary spending on storage and API calls.

Optimizing Fathom API Performance

fathom-performance-tuning

jeremylongshore/claude-code-plugins-plus-skills

This guide provides advanced strategies for optimizing bulk data synchronization and reducing latency when interacting with the Fathom meeting intelligence API. Techniques covered include implementing granular caching strategies (different TTLs for transcripts vs. action items), efficient batch processing with rate limit management, connection pooling, and robust error handling for reliable, high-throughput data operations.

Figma Multi-Environment API Setup

figma-multi-env-setup

jeremylongshore/claude-code-plugins-plus-skills

This skill guides the secure configuration of Figma API access across development, staging, and production environments. It details best practices for managing separate API tokens (PATs), file keys, and cache settings. The focus is on implementing robust environment guards and utilizing secret management solutions to prevent cross-environment data leakage and accidental operations.

Figma API Integration Architecture Guide

figma-reference-architecture

jeremylongshore/claude-code-plugins-plus-skills

A comprehensive reference architecture for building production-grade integrations with the Figma REST API. This guide covers the full design-to-code pipeline, including design token extraction, scalable asset export (icons/images), and robust webhook event handling. Ideal for architects planning new Figma services, establishing project structure, or implementing complex design system workflows.

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