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Found 288 Skills
Azure AI Projects SDK for .NET. High-level client for Azure AI Foundry projects including agents, connections, datasets, deployments, evaluations, and indexes. Use for AI Foundry project management, versioned agents, and orchestration. Triggers: "AI Projects", "AIProjectClient", "Foundry project", "versioned agents", "evaluations", "datasets", "connections", "deployments .NET".
Use when fine-tuning LLMs, training custom models, or optimizing model performance for specific tasks. Invoke for parameter-efficient methods, dataset preparation, or model adaptation.
Profile and explore a dataset to understand its shape, quality, and patterns. Use when encountering a new table or file, checking null rates and column distributions, spotting data quality issues like duplicates or suspicious values, or deciding which dimensions and metrics to analyze.
BioBlend and Planemo expertise for Galaxy workflow automation. Galaxy API usage, workflow invocation, status checking, error handling, batch processing, and dataset management. Essential for any Galaxy automation project.
Dify dataset retrieve API for knowledge base chunk search/testing. Use when integrating or debugging Dify knowledge base retrieval requests, retrieval_model options, or response shaping.
INVOKE THIS SKILL when creating evaluation datasets, uploading datasets to LangSmith, or managing existing datasets. Covers dataset types (final_response, single_step, trajectory, RAG), CLI management commands, SDK-based creation, and example management. Uses the langsmith CLI tool.
Create and manage datasets on Hugging Face Hub. Supports initializing repos, defining configs/system prompts, streaming row updates, and SQL-based dataset querying/transformation. Designed to work alongside HF MCP server for comprehensive dataset workflows.
Annotate Airflow tasks with data lineage using inlets and outlets. Use when the user wants to add lineage metadata to tasks, specify input/output datasets, or enable lineage tracking for operators without built-in OpenLineage extraction.
Golden dataset lifecycle patterns for curation, versioning, quality validation, and CI integration. Use when building evaluation datasets, managing dataset versions, validating quality scores, or integrating golden tests into pipelines.
Interact with the Langfuse API. Use when user wants to query traces, fetch prompts, create datasets, manage scores, or do anything else via the Langfuse REST API.
Build AI applications using Azure AI Projects SDK for JavaScript (@azure/ai-projects). Use when working with Foundry project clients, agents, connections, deployments, datasets, indexes, evaluations, or getting OpenAI clients.
INVOKE THIS SKILL when creating, managing, or querying Arize datasets and examples. Covers dataset CRUD, appending examples, exporting data, and file-based dataset creation using the ax CLI.