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Azure Content Safety Analysis for TypeScript
azure-ai-contentsafety-ts
sickn33/antigravity-awesome-skills
373
A comprehensive REST SDK for TypeScript that enables developers to analyze both text and images for harmful content using Azure AI services. It supports detecting various categories of harmful material (e.g., hate speech, violence, sexual content) and allows for advanced customization through creating and enforcing custom blocklists. Ideal for building robust content moderation layers in applications.
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Azure Content Safety Analysis for TypeScript
azure-ai-contentsafety-ts
sickn33/antigravity-awesome-skills
373
A comprehensive REST SDK for TypeScript that enables developers to analyze both text and images for harmful content using Azure AI services. It supports detecting various categories of harmful material (e.g., hate speech, violence, sexual content) and allows for advanced customization through creating and enforcing custom blocklists. Ideal for building robust content moderation layers in applications.
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TLDR Prompt Summary Helper
tldr-prompt
github/awesome-copilot
333
Generates concise TLDR-format summaries for GitHub Copilot customization files, MCP server docs, or related URLs, ensuring actionable examples and context-aware verbosity for inline or chat view sessions.
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ElevenLabs TTS and Voice Cloning Workflow
elevenlabs-core-workflow-a
jeremylongshore/claude-code-plugins-plus-skills
190
Implement professional text-to-speech generation and advanced voice cloning using the ElevenLabs API. This comprehensive workflow supports standard text-to-speech conversion, advanced voice customization (stability, similarity boost), and instant voice cloning from audio samples. It also includes WebSocket streaming for real-time applications like chatbots or live narration, making it ideal for building sophisticated, high-quality audio features.
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Fine-Tuning and Deploying LLMs Workflow
together-core-workflow-b
jeremylongshore/claude-code-plugins-plus-skills
200
This workflow guides users through the complete lifecycle of customizing large language models (LLMs). It covers uploading training data, initiating fine-tuning jobs, monitoring training progress, managing model versions, and finally deploying the optimized model to a dedicated, autoscaling inference endpoint using the Together AI API. Ideal for production-level customization.
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