Claude Skills by VectorSpaceLab

"Guides braindecode model selection, signal-parameter

"Guides braindecode preprocessing pipelines for MNE and

"Use Brian2 for clock-driven spiking-neural-network modeling,

"Choose Brian2 runtime and C++ standalone code-generation targets,

"Install and validate Brian2 2.9.0 environments, configure

"Build and validate Brian2 2.9.0 neuron populations, equations,

"Record Brian2 2.9.0 spikes, state variables, custom events, rates,

"Assemble and run Brian2 simulations with explicit or magic

"Build Brian2 2.9.0 morphologies and multicompartment SpatialNeuron

"Define Brian2 2.9.0 synaptic connectivity, event pathways, delays,

"Use Brian2 physical units, equation declarations and flags,

"Use this self-contained Browser Use repo skill for Python agents

"Write and debug Browser Use Python agent workflows with legacy

"Configure and troubleshoot Browser Use Browser, BrowserSession,

"Use the persistent browser-use/bu CLI for browser automation,

"Select Browser Use LLM adapters and configure provider

"Deploy and integrate Browser Use with sandbox execution, Browser

"Build and debug Browser Use tools/actions: custom Tools/Controller

"Use CAMEL-AI to build, configure, tool, remember, evaluate, and

"Build CAMEL ChatAgent workflows, BaseMessage setup, role-playing

"Use CAMEL-AI synthetic data generation, data collectors, datasets,

"Build CAMEL memory, retrieval/RAG, embedding, storage, loader,

"Choose, configure, inspect, and troubleshoot CAMEL model backends,

"Attach Python functions, CAMEL toolkits, MCP/OpenAPI tools,

"Use CausalML for causal inference, uplift modeling, matching,

"Score, validate, interpret, and optimize causalml treatment-effect

"Classical CausalML causal estimators covering meta-learners, TMLE,

"Prepare causalml datasets, encodings, propensity scores, matching

"Operate CausalML optional deep neural estimators: DragonNet and

Tree-based causal and uplift model workflows.

"Use CausalNex to learn causal structures, fit Bayesian networks,

"Fit Bayesian networks, query marginals, intervene, evaluate

"Discretize continuous features with unsupervised, tree-based, or

"Learn causal graph structure with NOTEARS, DYNOTEARS, and the

"Generate synthetic DAGs, tabular samples, dynamic time-series

"Use CellTypist for single-cell RNA-seq cell type annotation, model

"Run CellTypist prediction and annotation workflows from Python or

"Manage CellTypist built-in model discovery, local cache behavior,

"Plan and preflight custom CellTypist model training, including

"Handle CellTypist AnnotationResult exports, AnnData insertion,

"Routes CenterNet object-detection training, evaluation,

"Use Chai Lab / Chai-1 for molecular structure prediction, input

"Run, script, and troubleshoot Chai-1 folding with the chai-lab

"Author, validate, and debug Chai FASTA input records for proteins,

"Prepare and validate Chai MSA and template inputs from aligned

"Author, validate, and troubleshoot Chai-1 restraint CSVs, covalent

"Routes Chainer workflows for training, export, distributed

Routes ChainerX build, backend, device, ndarray, and fallback workflows.

"Routes ChainerMN distributed training, MPI, communicator, and

Routes Chainer model export workflows for ONNX-Chainer and Caffe.