DataMaster

Dataset discovery and download toolkit covering HuggingFace, GitHub, Google, and academic paper search. Use when you need to find, inspect, or download ML datasets.

Tree-structured memory management for node-based exploration. Manages global memory, data link records, and per-node manifest (TL;DR + recordings). Use when agents need to persist, share, or retrieve exploration knowledge.

Code execution and submission tools for DataNode (Black/Red) agents. Manages DataLoader code, runs assembled scripts, validates and grades submissions.

Data loading, cleaning, external-data merge, and validation-diagnosis guidance for black-node style ML agents. Use when a coding agent must improve data quality or integrate external datasets without changing the core model logic, especially for image tasks but also for tabular and text tasks.

Retrieval-Augmented Generation (RAG) skill for generic semantic search and knowledge retrieval. Use when you need to build or call vector-based search over your own documents using vector indexes (optional FAISS) and embedding models (local transformers or OpenAI embeddings), or when integrating LLMs with external knowledge bases in a project-agnostic way.