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Scrapegraph AI Workflow Automation

scrapegraph-ai-automation

ComposioHQ/awesome-claude-skills

Automates Scrapegraph AI operations through Composio’s Rube MCP, guiding you to discover tools, check active connections, execute schema-compliant workflows, and manage sessions and pagination safely.

Segment Anything Model

segment-anything-model

Orchestra-Research/AI-Research-SKILLs

Provides Meta AI’s Segment Anything Model for zero-shot image segmentation via interactive prompts or automatic mask generation, enabling rapid dataset creation and integration in vision pipelines.

Semanticscholar MCP Automation

semanticscholar-automation

ComposioHQ/awesome-claude-skills

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.

Production Computer Vision Engineering Pipeline

senior-computer-vision

alirezarezvani/claude-skills

Comprehensive skill set covering the full lifecycle of advanced visual AI systems. Expertise includes object detection (YOLO, Faster R-CNN), instance and semantic segmentation (Mask R-CNN, SAM), model training using PyTorch, and production deployment optimization using ONNX and TensorRT for edge or cloud targets.

Advanced Prompt Engineering and LLM Evaluation

senior-prompt-engineer

alirezarezvani/claude-skills

A comprehensive, model-agnostic toolkit for advanced LLM development. It enables iterative prompt optimization through static analysis (token usage, clarity), measures critical RAG metrics (relevance, faithfulness, coverage), and validates complex agent workflows and configurations. Essential for rigorous LLM quality assurance and cost management.

Sentence Embedding Framework

sentence-transformers

Orchestra-Research/AI-Research-SKILLs

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.

Serpapi Automation With Rube

serpapi-automation

ComposioHQ/awesome-claude-skills

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.

Experiment Tracking Setup

setting-up-experiment-tracking

jeremylongshore/claude-code-plugins-plus-skills

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.

SGLang Structured Inference Service

Orchestra-Research/AI-Research-SKILLs

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.

Similarity Search Patterns Implementation

similarity-search-patterns

sickn33/antigravity-awesome-skills

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.

Simple Preference Optimization for LLM Alignment

Orchestra-Research/AI-Research-SKILLs

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.

Automated Documentation to AI Skills

sickn33/antigravity-awesome-skills

This skill provides an automated solution for transforming diverse, unstructured technical data sources—including documentation websites, GitHub repositories, and PDFs—into structured, actionable 'Claude AI skills.' It significantly streamlines the process of knowledge base creation, data structuring, and preparing large volumes of technical information for advanced AI applications.

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