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Rev AI Workflow Automation
rev-ai-automation
ComposioHQ/awesome-claude-skills
393
Guide to automating Rev AI tasks through Composio’s Rube MCP toolkit, covering setup, mandatory tool discovery, connection checks, and schema-driven execution best practices for reliable results.
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Rosette Text Analytics Automation
rosette-text-analytics-automation
ComposioHQ/awesome-claude-skills
235
Automates Rosette Text Analytics actions through Composio’s Rube MCP, guiding users to discover current tool schemas, verify connections, and execute workflows with schema-compliant inputs.
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RWKV Hybrid Architecture
rwkv-architecture
Orchestra-Research/AI-Research-SKILLs
253
RWKV is an RNN+Transformer hybrid architecture with linear-time inference, infinite context, and GPT-style training. It delivers constant-memory, streaming generation on CUDA and CPU, ideal for long-context, memory-constrained deployments.
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Sagemaker Endpoint Deployer
sagemaker-endpoint-deployer
jeremylongshore/claude-code-plugins-plus-skills
256
Auto-activating assistant that guides AWS Sagemaker endpoint deployment, from best practices to production-ready code, configurations, and validation for inference serving and monitoring workflows.
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Semanticscholar MCP Automation
semanticscholar-automation
ComposioHQ/awesome-claude-skills
423
Automates Semanticscholar workflows through Composio’s Semanticscholar toolkit via Rube MCP, covering tool discovery, connection verification, session reuse, and schema-compliant multi-tool execution for reliable research automation.
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Senior Prompt Engineering Toolkit
senior-prompt-engineer
alirezarezvani/claude-skills
468
Toolkit for prompt engineering experts to optimize prompts, evaluate LLM outputs, design agentic workflows, assess RAG quality, and curate few-shot examples across evaluation and orchestration tasks.
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Sentence Embedding Framework
sentence-transformers
Orchestra-Research/AI-Research-SKILLs
326
Sentence Transformers provides 5000+ pre-trained models that generate sentence, text, and image embeddings for RAG, semantic search, clustering, and multilingual production workloads without relying on external APIs.
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Serpapi Automation With Rube
serpapi-automation
ComposioHQ/awesome-claude-skills
364
Orchestrates Serpapi searches through Composio's Rube MCP by discovering current tool schemas, validating the connection, and executing schema-compliant calls with session reuse and explicit memory placeholders to keep automation workflows reliable.
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Experiment Tracking Setup
setting-up-experiment-tracking
jeremylongshore/claude-code-plugins-plus-skills
325
Automates the setup of ML experiment tracking with MLflow or W&B, configures the environment, initializes servers, and supplies snippets for logging parameters, metrics, and artifacts so runs stay reproducible and easy to compare.
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SGLang Structured Inference Service
sglang
Orchestra-Research/AI-Research-SKILLs
150
SGLang is a high-performance serving framework for LLMs and VLMs that uses RadixAttention prefix caching to deliver structured outputs (JSON/regex/grammar) and agentic workflows with function calls, providing up to 5× faster inference than vLLM across multi-GPU production deployments.
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Similarity Search Patterns Implementation
similarity-search-patterns
sickn33/antigravity-awesome-skills
302
This pattern provides established best practices for implementing efficient similarity search in production systems. It is crucial for building semantic search engines, implementing Retrieval-Augmented Generation (RAG), creating advanced recommendation systems, and optimizing retrieval performance when scaling to millions of vectors.
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Simple Preference Optimization for LLM Alignment
simpo-training
Orchestra-Research/AI-Research-SKILLs
112
SimPO (Simple Preference Optimization) is a state-of-the-art, reference-free method designed for aligning Large Language Models (LLMs) using human preference data. It is an efficient alternative to DPO and PPO, notably outperforming DPO without requiring a separate reference model. It is ideal for practitioners who need faster, simpler, and more resource-efficient fine-tuning for preference alignment.
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