Claude Skills by VectorSpaceLab

"Guide NeuroMANCER 1.5.6 differentiable scientific machine-learning

"Assemble safe NeuroMANCER open- and closed-loop rollouts with

"Route NeuroMANCER data preparation and CPU-first training

"Construct and route NeuroMANCER neural blocks, continuous and

"Route pure-Python NeuroMANCER SLiM maps, structured recurrent

"Formulate and diagnose NeuroMANCER symbolic variables, objectives,

"Use Newton physics engine APIs for robotics simulation, solvers,

"Use Newton URDF, MJCF, USD, schema resolver, mesh, remesh,

"Build, step, and debug core Newton simulation models, states,

"Use Newton robotics APIs for actuators, controllers, inverse

"Use Newton sensors, viewer backends, example CLI, recording,

Choose and configure Newton solvers and contact/collision workflows.

"Route Nexent SDK, backend, frontend, knowledge/memory, and

"Operate Nexent backend FastAPI app/service/database changes,

"Operate Nexent Docker, Kubernetes, offline deployment, SQL

"Routes Nexent frontend App Router work, service clients, typed API

"Operate Nexent document processing, knowledge-base vector search,

"Operate Nexent SDK agent runtime, streaming execution, models,

"Use and maintain Nilearn, the Python neuroimaging package for

"Handle Nilearn Niimg image I/O, volume image operations,

"Use Nilearn dataset/template/atlas fetchers and public interfaces

"Make safe Nilearn checkout code, test, documentation, changelog,

"Build Nilearn first-level and second-level GLM workflows,

"Choose and use Nilearn maskers, atlas region extraction, inverse

"Use Nilearn supervised decoding, searchlight, SpaceNet/FREM,

"Create Nilearn plots, interactive views, surface visualizations,

"Work with Nilearn surface meshes, surface images,

"Routes Nitrain medical-imaging dataset, preprocessing, training,

"Build Nitrain datasets from files, CSV/TSV columns, folder labels,

"Fetch Nitrain architectures and train or evaluate Keras/TensorFlow

"Run Nitrain prediction workflows and inspect the current

"Apply Nitrain transforms, random augmentation, samplers, and

"Routes tasks for using NLP-progress as a multilingual NLP

"Helps agents find, interpret, and cite NLP-progress benchmark,

"Helps maintain NLP-progress Markdown task pages by adding or

"Guides NLP-progress structured JSON export, Markdown parser

"Use NLTK for classical natural-language processing in Python:

"Configure NLTK data search paths, download only needed NLTK data

"Use NLTK grammars, parsers, chunkers, trees, dependency graphs,

"Use NLTK classical ML, probability, language modeling, metrics,

"Use NLTK tokenization, detokenization, POS tagging, tagger

"Use NNI for AutoML experiments, hyperparameter tuning, neural

"Use NNI feature selectors and standalone utilities for tabular

"Use NNI HPO experiments, nnictl, ExperimentConfig, trial metric

"Use NNI model compression for pruning, quantization, distillation,

"Use NNI neural architecture search with model spaces, mutables,

"Use nnU-Net v2 for medical image segmentation workflows: dataset

"Extend nnU-Net v2 with custom trainers, planners, preprocessors,

"Prepare nnU-Net v2-compatible datasets, path variables,

"Run nnU-Net v2 prediction from dataset/results or explicit model