Results for “aad-graph”

Graph-based drug discovery toolkit. Molecular property prediction (ADMET), protein modeling, knowledge graph reasoning, molecular generation, retrosynthesis, GNNs (GIN, GAT, SchNet), 40+ datasets, for PyTorch-based ML on molecules, proteins, and biomedical graphs.

Autonomous discovery of concepts, methods, and vocabulary we have NOT heard of yet — sweeps broadly, diffs against a known-concepts ledger, and reports only what is genuinely new plus whether it names a gap in this stack. Built because 'graph engineering' had to arrive by word of mouth: a fixed topic list can only refresh what you already named, so it can never surface the thing you did not know to look for. Use for periodic/scheduled discovery, 'what's new in agent engineering', 'what are we missing', 'anything we haven't heard of'. Triggers: radar, discover, what's new, unknown unknowns, 新概念, 我们没听过的, 有什么没跟上的 — NOT for researching a topic you can already name (use /research), NOT for model releases (use /model-research), NOT for internal priorities (use /next).

Guides the agent through structured protocols for writing technical specifications, implementation plans, and summaries, with file naming and task directory conventions.