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- AndersonCompute the anderson metric — provided by scipy.stats. Use when the user has predictions and ground-truth and needs to compute anderson, or asks how to score with anderson.Votes: 0GitHub stars: 3
- Anderson KsampCompute the anderson_ksamp metric — provided by scipy.stats. Use when the user has predictions and ground-truth and needs to compute anderson_ksamp, or asks how to score with anderson_ksamp.Votes: 0GitHub stars: 3
- AdjustedrandscoreCompute the AdjustedRandScore metric — provided by torchmetrics. Use when the user has predictions and ground-truth and needs to compute AdjustedRandScore, or asks how to score with AdjustedRandScore.Votes: 0GitHub stars: 3
- AdjustedmutualinfoscoreCompute the AdjustedMutualInfoScore metric — provided by torchmetrics. Use when the user has predictions and ground-truth and needs to compute AdjustedMutualInfoScore, or asks how to score with AdjustedMutualInfoScore.Votes: 0GitHub stars: 3
- Adjusted Rand ScoreCompute the adjusted_rand_score metric — provided by scikit-learn. Use when the user has predictions and ground-truth and needs to compute adjusted_rand_score, or asks how to score with adjusted_rand_score.Votes: 0GitHub stars: 3
- Adjusted Mutual Info ScoreCompute the adjusted_mutual_info_score metric — provided by scikit-learn. Use when the user has predictions and ground-truth and needs to compute adjusted_mutual_info_score, or asks how to score with adjusted_mutual_info_score.Votes: 0GitHub stars: 3
- Accuracy ScoreCompute the accuracy_score metric — provided by scikit-learn. Use when the user has predictions and ground-truth and needs to compute accuracy_score, or asks how to score with accuracy_score.Votes: 0GitHub stars: 3
- CIDErEvaluates how well automatic image description metrics correlate with human consensus on sentence similarity. It probes the ability of generated or candidate sentences to accurately describe an image by measuring alignment with multiple human-generated reference descriptions. Use when the user has predictions and gold and needs to compute CIDEr.Votes: 0GitHub stars: 3
- Dna VisualizationPublication-quality DNA/RNA visualizations. Plasmid maps (circular/linear), sequence logos, restriction enzyme maps, GC content plots, and gene feature annotation tracks from GenBank/FASTA.Votes: 0GitHub stars: 4
- QutipQuantum physics simulation library for open quantum systems. Use when studying master equations, Lindblad dynamics, decoherence, quantum optics, or cavity QED. Best for physics research, open system dynamics, and educational simulations. NOT for circuit-based quantum computing—use qiskit, cirq, or pennylane for quantum algorithms and hardware execution.Votes: 0GitHub stars: 4
- FluidsimFramework for computational fluid dynamics simulations using Python. Use when running fluid dynamics simulations including Navier-Stokes equations (2D/3D), shallow water equations, stratified flows, or when analyzing turbulence, vortex dynamics, or geophysical flows. Provides pseudospectral methods with FFT, HPC support, and comprehensive output analysis.Votes: 0GitHub stars: 4
- SaelensProvides guidance for training and analyzing Sparse Autoencoders (SAEs) using SAELens to decompose neural network activations into interpretable features. Use when discovering interpretable features, analyzing superposition, or studying monosemantic representations in language models.Votes: 0GitHub stars: 4
- PyveneProvides guidance for performing causal interventions on PyTorch models using pyvene's declarative intervention framework. Use when conducting causal tracing, activation patching, interchange intervention training, or testing causal hypotheses about model behavior.Votes: 0GitHub stars: 4
- NnsightProvides guidance for interpreting and manipulating neural network internals using nnsight with optional NDIF remote execution. Use when needing to run interpretability experiments on massive models (70B+) without local GPU resources, or when working with any PyTorch architecture.Votes: 0GitHub stars: 4
- Llama FactoryExpert guidance for fine-tuning LLMs with LLaMA-Factory - WebUI no-code, 100+ models, 2/3/4/5/6/8-bit QLoRA, multimodal supportVotes: 0GitHub stars: 4
- AxolotlExpert guidance for fine-tuning LLMs with Axolotl - YAML configs, 100+ models, LoRA/QLoRA, DPO/KTO/ORPO/GRPO, multimodal supportVotes: 0GitHub stars: 4
- AccelerateSimplest distributed training API. 4 lines to add distributed support to any PyTorch script. Unified API for DeepSpeed/FSDP/Megatron/DDP. Automatic device placement, mixed precision (FP16/BF16/FP8). Interactive config, single launch command. HuggingFace ecosystem standard.Votes: 0GitHub stars: 4
- Stable DiffusionState-of-the-art text-to-image generation with Stable Diffusion models via HuggingFace Diffusers. Use when generating images from text prompts, performing image-to-image translation, inpainting, or building custom diffusion pipelines.Votes: 0GitHub stars: 4
- OutlinesGuarantee valid JSON/XML/code structure during generation, use Pydantic models for type-safe outputs, support local models (Transformers, vLLM), and maximize inference speed with Outlines - dottxt.ai's structured generation libraryVotes: 0GitHub stars: 4
- Bio Workflows Grn PipelineEnd-to-end gene regulatory network inference pipeline from processed single-cell data to regulon discovery and perturbation simulation. Supports RNA-only (pySCENIC) and multiome (SCENIC+) paths. Use when building gene regulatory networks from single-cell transcriptomic or multiome data.Votes: 0GitHub stars: 4
- SympyUse this skill when working with symbolic mathematics in Python. This skill should be used for symbolic computation tasks including solving equations algebraically, performing calculus operations (derivatives, integrals, limits), manipulating algebraic expressions, working with matrices symbolically, physics calculations, number theory problems, geometry computations, and generating executable code from mathematical expressions. Apply this skill when the user needs exact symbolic results rath...Votes: 0GitHub stars: 4
- RdkitCheminformatics toolkit for fine-grained molecular control. SMILES/SDF parsing, descriptors (MW, LogP, TPSA), fingerprints, substructure search, 2D/3D generation, similarity, reactions. For standard workflows with simpler interface, use datamol (wrapper around RDKit). Use rdkit for advanced control, custom sanitization, specialized algorithms.Votes: 0GitHub stars: 4
- Molecule VisualizationPublication-quality molecular visualization. 2D structure drawings (PNG/SVG), molecule grids with property annotations, scaffold highlighting, protein-ligand interaction diagrams, and interactive 3D views.Votes: 0GitHub stars: 4
- Tooluniverse Gene EnrichmentGene-set enrichment analysis — GO (Biological Process, Molecular Function, Cellular Component), KEGG, Reactome pathway enrichment via clusterProfiler, gseapy, ORA, GSEA. Use for interpreting DEG lists, screen hit lists, or any gene-list-to-pathways query. Includes simplify-cutoff handling and union-vs-total denominator conventions for percent-DE questions.Votes: 0GitHub stars: 4