All authors
Claude Skills by FOURTEEN1416
github.com/FOURTEEN1416951 skills0 installs77 views
- Transformer LensProvides guidance for mechanistic interpretability research using TransformerLens to inspect and manipulate transformer internals via HookPoints and activation caching. Use when reverse-engineering model algorithms, studying attention patterns, or performing activation patching experiments.Votes: 0GitHub stars: 10
- Trl Fine TuningFine-tune LLMs using reinforcement learning with TRL - SFT for instruction tuning, DPO for preference alignment, PPO/GRPO for reward optimization, and reward model training. Use when need RLHF, align model with preferences, or train from human feedback. Works with HuggingFace Transformers.Votes: 0GitHub stars: 10
- UnslothFast LLM fine-tuning with Unsloth - 2-5x faster training, 50-80% less VRAM. Use for single-GPU LoRA/QLoRA SFT, GRPO/RL reasoning training, vision/TTS fine-tuning, and GGUF export to Ollama/vLLM/llama.cpp. Supports 300+ models including Llama, Qwen, Gemma, DeepSeek, Mistral, Phi, and gpt-oss.Votes: 0GitHub stars: 10
- VerlProvides guidance for training LLMs with reinforcement learning using verl (Volcano Engine RL). Use when implementing RLHF, GRPO, PPO, or other RL algorithms for LLM post-training at scale with flexible infrastructure backends.Votes: 0GitHub stars: 10
- Weights And BiasesTrack ML experiments with automatic logging, visualize training in real-time, optimize hyperparameters with sweeps, and manage model registry with W&B - collaborative MLOps platformVotes: 0GitHub stars: 10
- CheckpointSave a local recovery packet from durable session state. Use when the user invokes /checkpoint, asks to preserve progress, or wants a safe restore point before risky or lengthy work.Votes: 0GitHub stars: 10
- CompactCompact the current chat context into a concise summary. Use when the user invokes /compact, context capacity is running low, or a long session needs a smaller continuation state.Votes: 0GitHub stars: 10
- ContextShow the current conversation context composition, estimated capacity, and compaction state. Use when the user invokes /context or asks how much context remains.Votes: 0GitHub stars: 10
- Get Available ResourcesThis skill should be used at the start of any computationally intensive scientific task to detect and report available system resources (CPU cores, GPUs, memory, disk space). It creates a JSON file with resource information and strategic recommendations that inform computational approach decisions such as whether to use parallel processing (joblib, multiprocessing), out-of-core computing (Dask, Zarr), GPU acceleration (PyTorch, JAX), or memory-efficient strategies. Use this skill before runni...Votes: 0GitHub stars: 10
- GoalSet an explicit objective, success criteria, and stopping conditions for the current OpenScience session.Votes: 0GitHub stars: 10
- HandoffCreate a self-contained continuation packet for another agent. Use when the user invokes /handoff, asks to transfer work, or needs the current context saved before another agent continues.Votes: 0GitHub stars: 10
- Hugging Face JobsThis skill should be used when users want to run any workload on Hugging Face Jobs infrastructure. Covers UV scripts, Docker-based jobs, hardware selection, cost estimation, authentication with tokens, secrets management, timeout configuration, and result persistence. Designed for general-purpose compute workloads including data processing, inference, experiments, batch jobs, and any Python-based tasks. Should be invoked for tasks involving cloud compute, GPU workloads, or when users mention ...Votes: 0GitHub stars: 10
- Hugging Face TrackioTrack and visualize ML training experiments with Trackio. Use when logging metrics during training (Python API) or retrieving/analyzing logged metrics (CLI). Supports real-time dashboard visualization, HF Space syncing, and JSON output for automation.Votes: 0GitHub stars: 10
- InitCreate or refresh an AGENTS.md project instruction file. Use when starting work in a repository, onboarding an agent to an unfamiliar codebase, or when the user explicitly invokes /init or asks to initialize project guidance.Votes: 0GitHub stars: 10
- Iso 13485 CertificationComprehensive toolkit for preparing ISO 13485 certification documentation for medical device Quality Management Systems. Use when users need help with ISO 13485 QMS documentation, including (1) conducting gap analysis of existing documentation, (2) creating Quality Manuals, (3) developing required procedures and work instructions, (4) preparing Medical Device Files, (5) understanding ISO 13485 requirements, or (6) identifying missing documentation for medical device certification. Also use wh...Votes: 0GitHub stars: 10
- Labarchive IntegrationElectronic lab notebook API integration. Access notebooks, manage entries/attachments, backup notebooks, integrate with Protocols.io/Jupyter/REDCap, for programmatic ELN workflows.Votes: 0GitHub stars: 10
- PlanEnter read-only plan mode and produce a decision-ready plan. Use when the user invokes /plan, asks to plan before implementation, or needs choices and tradeoffs resolved before execution.Votes: 0GitHub stars: 10
- ResumeResume an exhausted bounded research run from its existing contract and checkpoints. Use when the user invokes /resume or explicitly asks to continue after a runtime-budget boundary.Votes: 0GitHub stars: 10
- Skill InstallerInstall or remove third-party openscience skills from a public git repository. Use when the user says "add this skill <url>", "install skill <url>", or "remove skill <namespace>". The skill runs locally via `openscience skill add|list|remove`, fetches the repo, runs a 6-layer safety gate (regex + server-side Haiku classifier), prompts the user to confirm, then writes the skills to ~/.openscience/installed-skills/ and uploads to the dashboard for cross-machine sync.Votes: 0GitHub stars: 10
- StatusShow live session, plan, artifact, model, and workspace state. Use when the user invokes /status or asks for a concise progress and workspace summary.Votes: 0GitHub stars: 10
- StopStop active work in the current session. Use when the user invokes /stop or asks to cancel the current turn, active compute jobs, session kernels, or all running session work.Votes: 0GitHub stars: 10
- AstropyComprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.Votes: 0GitHub stars: 10
- Autoregressive Neural Pde SolverTraining patterns for autoregressive neural PDE solvers (FNO, DeepONet, CNO). Covers rollout training, noise injection for stability, multi-component loss functions (H1, frequency-sensitive, boundary-aware), per-channel normalization for coupled multi-variable systems, and the PDEBench nRMSE metric. Use when training any neural operator that predicts time-dependent PDE solutions.Votes: 0GitHub stars: 10
- Bayesian InferenceBayesian parameter estimation with MCMC (emcee) and probabilistic programming (PyMC). Posterior distributions, corner plots, model evidence, convergence diagnostics. Use when you need full posterior distributions, not just point estimates.Votes: 0GitHub stars: 10
- Conservation Law DiscoveryDiscover conserved quantities and symmetries from trajectory data. Identifies energy, momentum, angular momentum, and custom invariants using neural networks and symbolic methods. Inspired by Noether's theorem.Votes: 0GitHub stars: 10
- Dimensional AnalysisAutomated dimensional analysis — Buckingham Pi theorem, non-dimensionalization, unit validation with pint, and characteristic scale estimation. Use before any physics computation to verify consistency and reduce parameter space.Votes: 0GitHub stars: 10
- Dynamical SystemsAnalyze nonlinear dynamical systems — phase portraits, fixed points, stability analysis, bifurcation diagrams, Poincare sections, Lyapunov exponents, and chaos detection. Use for any autonomous or non-autonomous ODE system where qualitative behavior matters.Votes: 0GitHub stars: 10
- Fluid DynamicsComputational fluid dynamics — Navier-Stokes solvers, lid-driven cavity, channel flow, vortex methods, turbulence statistics, drag/lift computation. Spectral and finite-difference methods for incompressible and compressible flows.Votes: 0GitHub stars: 10
- 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: 10
- Hamiltonian MechanicsHamiltonian mechanics — symplectic integrators (leapfrog, Yoshida), Hamilton's equations, Poisson brackets, canonical transformations, action-angle variables, and KAM theory analysis. Use for energy-conserving long-time integration of conservative systems.Votes: 0GitHub stars: 10
- Neural OperatorTrain neural operators (FNO, DeepONet) to learn solution maps for parametric PDE families. Once trained, solve new PDE instances in milliseconds. Use when you need to solve many instances of the same PDE with different parameters/ICs/BCs.Votes: 0GitHub stars: 10
- Ode SolverSolve ordinary differential equations (initial and boundary value problems). Supports stiff/non-stiff systems, event detection, Hamiltonian/symplectic integration, parameter sweeps, and phase space analysis. Use for any ODE system in physics, engineering, or applied math.Votes: 0GitHub stars: 10
- Pde SolverSolve partial differential equations — finite differences, spectral methods, and physics-informed neural networks (PINNs via DeepXDE). Supports 1D/2D/3D, steady/transient, linear/nonlinear PDEs with Dirichlet, Neumann, and periodic boundary conditions.Votes: 0GitHub stars: 10
- Physics DatabasesQuery physics databases — NIST CODATA constants, NIST Chemistry WebBook, Materials Project, Particle Data Group (PDG), OEIS sequences. Always use these instead of hardcoding physical constants.Votes: 0GitHub stars: 10
- Physics FittingNonlinear curve fitting for physics data with proper error propagation, chi-squared analysis, residual diagnostics, confidence intervals, and model comparison (AIC/BIC). Use for any parameter extraction from experimental or simulation data.Votes: 0GitHub stars: 10
- Physics VisualizationPublication-quality physics plots — vector fields, streamlines, contour maps, 3D surfaces, phase space, spectrograms, and animations. Optimized for journal submission with LaTeX labels, proper colormaps, and multi-panel layouts.Votes: 0GitHub stars: 10
- Pinn TrainingTrain Physics-Informed Neural Networks (PINNs) using DeepXDE. Solve forward and inverse PDE problems by embedding physics equations into the neural network loss function. Supports 1D/2D/3D, time-dependent, and parametric PDEs.Votes: 0GitHub stars: 10
- PymatgenMaterials science toolkit. Crystal structures (CIF, POSCAR), phase diagrams, band structure, DOS, Materials Project integration, format conversion, for computational materials science.Votes: 0GitHub stars: 10
- Shock Capturing Neural OperatorsArchitectures and techniques for neural operators on discontinuous PDE solutions (shocks, contact discontinuities, steep gradients). Covers local-global spectral design (ShockFNO), reflection padding for non-periodic BCs, resolution scaling for shock width, and frequency-band error diagnostics. Use for low-viscosity Burgers, compressible Euler, Riemann problems, or any PDE where standard FNO produces Gibbs oscillations.Votes: 0GitHub stars: 10
- Sindy IdentificationSparse Identification of Nonlinear Dynamics (SINDy) — discover governing equations from time-series data. Builds sparse dynamical system models dx/dt = f(x) from measurements using PySINDy. Use when you have trajectory data and want to find the underlying ODE.Votes: 0GitHub stars: 10
- Spectral AnalysisFrequency-domain analysis — FFT, power spectral density (Welch/periodogram), spectrograms, wavelet transforms, and coherence. Use for any signal with periodic, quasi-periodic, or transient frequency content in physics data.Votes: 0GitHub stars: 10
- Statistical MechanicsMonte Carlo simulation for statistical mechanics — Ising model, Metropolis-Hastings, Wolff cluster algorithm, observables (magnetization, susceptibility, specific heat), finite-size scaling, and critical phenomena analysis.Votes: 0GitHub stars: 10
- Symbolic RegressionDiscover governing equations from data using PySR (evolutionary symbolic regression). Physics-constrained search with dimensional analysis, custom operators, and complexity-accuracy tradeoffs. Use when you need an interpretable equation, not a black-box model.Votes: 0GitHub stars: 10
- Wave PropagationSimulate wave propagation — acoustic, electromagnetic, elastic, and quantum waves. FDTD, spectral methods, and absorbing boundary conditions for 1D/2D/3D wave equations with sources, scattering, and dispersion.Votes: 0GitHub stars: 10
- CirqGoogle quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip.Votes: 0GitHub stars: 10
- PennylaneHardware-agnostic quantum ML framework with automatic differentiation. Use when training quantum circuits via gradients, building hybrid quantum-classical models, or needing device portability across IBM/Google/Rigetti/IonQ. Best for variational algorithms (VQE, QAOA), quantum neural networks, and integration with PyTorch/JAX/TensorFlow. For hardware-specific optimizations use qiskit (IBM) or cirq (Google); for open quantum systems use qutip.Votes: 0GitHub stars: 10
- QiskitIBM quantum computing framework. Use when targeting IBM Quantum hardware, working with Qiskit Runtime for production workloads, or needing IBM optimization tools. Best for IBM hardware execution, quantum error mitigation, and enterprise quantum computing. For Google hardware use cirq; for gradient-based quantum ML use pennylane; for open quantum system simulations use qutip.Votes: 0GitHub stars: 10
- 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: 10
- CompareCompare runs, artifacts, methods, models, or claims on a fair and explicit decision basis.Votes: 0GitHub stars: 10
- Conducting Scientific ResearchConduct rigorous, reproducible multi-step scientific work with literature, databases, local files, Python, R, shell, artifacts, reviewers, and approved compute. Use for evidence synthesis, data or statistical analysis, machine learning, simulation, study design, scientific figures or manuscripts, reproduction audits, and database curation. Do not invoke for a simple timeless science fact that needs no tools or project workflow. Kaggle competitions use the separate kaggle-competition skill.Votes: 0GitHub stars: 10