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Codebase Indexing for Semantic Search

cursor-codebase-indexing

jeremylongshore/claude-code-plugins-plus-skills

This tool optimizes the codebase indexing within Cursor. It processes your entire codebase, converting code chunks into vector embeddings stored in a vector database. This enables advanced @Codebase semantic search, allowing users to ask natural language questions (e.g., "Where is authentication handled?") and retrieve the most relevant code snippets, significantly improving AI context awareness across chat and coding tasks.

Avoiding Common AI Coding Pitfalls

cursor-known-pitfalls

jeremylongshore/claude-code-plugins-plus-skills

A comprehensive guide to avoiding common pitfalls when using AI-powered IDEs like Cursor. It covers best practices for AI interaction, secure coding habits (handling secrets, credentials), project configuration (rules, ignore files), and performance optimization. Essential for maintaining high code quality and security in AI-assisted workflows.

Databricks ML Workflow: Training and Serving

databricks-core-workflow-b

jeremylongshore/claude-code-plugins-plus-skills

This guide outlines the complete MLOps workflow on Databricks. It covers feature engineering using Feature Store, tracking experiments with MLflow, managing model versions in the Model Registry, and deploying real-time inference endpoints via Mosaic AI Model Serving. Ideal for building robust, production-grade ML pipelines.

Datarobot Automation Workflow

datarobot-automation

ComposioHQ/awesome-claude-skills

Automate Datarobot operations via Composio's Rube MCP by discovering tool schemas, managing connections, and executing workflows with RUBE_MULTI_EXECUTE_TOOL while observing schema compliance and session reuse best practices.

Dataset Loader Creator

dataset-loader-creator

jeremylongshore/claude-code-plugins-plus-skills

Automates dataset loader creation within ML Training workflows, offering best-practice guidance, validation checks, and production-ready code to accelerate data prep and model tuning.

Gemini Deep Research

sickn33/antigravity-awesome-skills

Uses the Gemini API to autonomously plan, search, read, and synthesize detailed research reports with streaming status updates, structured outputs, and the ability to continue previous investigations for market analysis, technical reviews, or due diligence.

Deepgram Automation Workflow

deepgram-automation

ComposioHQ/awesome-claude-skills

Provides a workflow for automating Deepgram operations through Composio's toolkit using the Rube MCP bridge, covering prerequisites, tool discovery, connection checks, executions, and handling schema and pagination details.

Real-Time Streaming Transcription with Deepgram

deepgram-core-workflow-b

jeremylongshore/claude-code-plugins-plus-skills

This guide demonstrates how to implement robust, real-time, low-latency streaming transcription using Deepgram's WebSocket API. It covers advanced audio handling, including microphone input capture (via Sox), speaker diarization, utterance boundary detection, and implementing automatic reconnection logic. Essential for building professional voice AI applications, live captioning services, or voice interfaces.

Deepgram SDK Installation and Auth

deepgram-install-auth

jeremylongshore/claude-code-plugins-plus-skills

A comprehensive guide for installing and configuring the Deepgram SDK for both Node.js and Python environments. This skill covers best practices for secure API key management using environment variables, client initialization (including version differences), and connection verification. Use this when integrating Deepgram's advanced speech-to-text and text-to-speech capabilities into a new application.

Automated Model Deployment

deploying-machine-learning-models

jeremylongshore/claude-code-plugins-plus-skills

Deploying Machine Learning Models automates serving trained models to production by analyzing requirements, generating API and infrastructure code, and orchestrating deployment workflows with validation, error handling, and monitoring baked in.

TorchTitan Distributed Pretraining

distributed-llm-pretraining-torchtitan

Orchestra-Research/AI-Research-SKILLs

Orchestrates PyTorch-native TorchTitan 4D parallelism (FSDP2, TP, PP, CP) for large-scale LLM pretraining, scaling from 8 to 512+ GPUs with Float8, torch.compile, and distributed checkpointing to boot Llama 3.1, DeepSeek V3, or custom models.

Distributed Training Setup

distributed-training-setup

jeremylongshore/claude-code-plugins-plus-skills

Guides automated distributed training setups with step-by-step practices, production-ready configs, and validation checks for ML training workflows.

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