Scan to join WeChat groupBrowse curated skills with source links, package snapshots, README assets and install signals in one calm, searchable catalog.
Expert guidance for building AI agents with Pydantic AI framework. Use when creating multi-agent systems, AI orchestration workflows, or structured LLM applications with type safety and validation.
Python interface to OpenMS for mass spectrometry data analysis. Use for LC-MS/MS proteomics and metabolomics workflows including file handling (mzML, mzXML, mzTab, FASTA, pepXML, protXML, mzIdentML), …
Provides guidance for performing causal interventions on PyTorch models using pyvene's declarative intervention framework. Use when conducting causal tracing, activation patching, interchange interven…
Use when working with Qdrant vector database for semantic search and RAG. Covers collection setup, embedding generation, vector upsert/search, HNSW indexing, filtering, and integration with OpenAI emb…
Extract Question-Reasoning-Answer pairs from text. Use --context for domain-focused extraction. Validates answers are grounded in source text.
Quantum computer music composition and performance using quantum circuits, ZX-calculus notation, and quantum instruments
Qwen Training Data Miner (Prototype)
Integration of RAG (Retrieval Augmented Generation) with xAI Grok Collections and Google Gemini. Use this skill when you need to add an AI chat with a knowledge base, set up a RAG system, integrate Gr…
Python library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel …
Expert guidance for Python AI development fundamentals, essential libraries, data structures, async programming, and best practices for AI/ML projects
Conducts structured Q&A discussions with users, handling multiple choice, single choice, and open-ended questions one at a time - tracks progress, validates answers, and provides summary reports for c…
Transfer learning, metrics optimization, and continuous improvement for AI-powered QE agents.
Mechanic wobbling duckoid robot that quacks and generates nonstandard musical scale compositions. Maximally cost-efficient design (~$68 BOM).
GraphDB Exploration Agent - Explore the RyuGraph database in natural language or Cypher and return related code or specifications. Invoke with /query-graph [query].
Generates race-day pacing and fueling strategies with contingency plans. Use when user has an upcoming race, asks for race preparation advice, or wants a printable race-day plan with segment pacing an…
Modélise le raisonnement juridique d'un magistrat français pour l'analyse de dossiers civils. Utiliser ce skill pour analyser un litige et identifier les questions juridiques, construire un raisonneme…
Comprehensive healthcare AI toolkit for developing, testing, and deploying machine learning models with clinical data. This skill should be used when working with electronic health records (EHR), clin…
High-level training framework for PyTorch that abstracts boilerplate while maintaining flexibility. Includes the Trainer, LightningModule, and support for multi-GPU scaling and reproducibility. (light…
Manage Qdrant Cloud collections, including vectorization of textbook chapters and metadata tagging for RAG retrieval. Agent: AIEngineer
This skill provides guidance for implementing robust Qdrant vector database integration with RAG (Retrieval Augmented Generation) systems, including proper async client handling, error management, and…
Comprehensive research combining web search, quantum analysis, and persistent memory. Use when researching topics that need current information plus deep cognitive analysis.
Fast ticker analysis for /analysis page. Provides quick BUY/SELL/HOLD recommendations based on technical indicators, recent news, and basic fundamentals within seconds. Optimized for speed over depth.
Improves the RAG (Retrieval-Augmented Generation) chatbot for the Physical AI & Humanoid Robotics textbook with strict grounding, citation requirements, and performance optimization.
Set up automated agent-driven development with Ralph. Run AI agents in a loop to implement features from user stories, verify acceptance criteria, and log progress for the next agent.