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Claude Skills by luokai0
github.com/luokai05,222 skills168 installs10,845 views
- Segment AnythingFoundation model for image segmentation with zero-shot transfer. Use when you need to segment any object in images using points, boxes, or masks as prompts, or automatically generate all object masks in an image.Votes: 0GitHub stars: 11
- Sentence TransformersFramework for state-of-the-art sentence, text, and image embeddings. Provides 5000+ pre-trained models for semantic similarity, clustering, and retrieval. Supports multilingual, domain-specific, and multimodal models. Use for generating embeddings for RAG, semantic search, or similarity tasks. Best for production embedding generation.Votes: 0GitHub stars: 11
- SentencepieceLanguage-independent tokenizer treating text as raw Unicode. Supports BPE and Unigram algorithms. Fast (50k sentences/sec), lightweight (6MB memory), deterministic vocabulary. Used by T5, ALBERT, XLNet, mBART. Train on raw text without pre-tokenization. Use when you need multilingual support, CJK languages, or reproducible tokenization.Votes: 0GitHub stars: 11
- Session ManagementContext preservation, tiered summarization, resumabilityVotes: 0GitHub stars: 11
- SglangFast structured generation and serving for LLMs with RadixAttention prefix caching. Use for JSON/regex outputs, constrained decoding, agentic workflows with tool calls, or when you need 5× faster inference than vLLM with prefix sharing. Powers 300,000+ GPUs at xAI, AMD, NVIDIA, and LinkedIn.Votes: 0GitHub stars: 11
- ShapModel interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (waterfall, beeswarm, bar, scatter, force, heatmap), debugging models, analyzing model bias or fairness, comparing models, or implementing explainable AI. Works with tree-based models (XGBoost, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), linear models, and any black-box mo...Votes: 0GitHub stars: 11
- Shopify AppsShopify app development - Remix, Admin API, checkout extensionsVotes: 0GitHub stars: 11
- SimpoSimple Preference Optimization for LLM alignment. Reference-free alternative to DPO with better performance (+6.4 points on AlpacaEval 2.0). No reference model needed, more efficient than DPO. Use for preference alignment when want simpler, faster training than DPO/PPO.Votes: 0GitHub stars: 11
- SimpyProcess-based discrete-event simulation framework in Python. Use this skill when building simulations of systems with processes, queues, resources, and time-based events such as manufacturing systems, service operations, network traffic, logistics, or any system where entities interact with shared resources over time.Votes: 0GitHub stars: 11
- Simulation OrchestratorOrchestrate multi-simulation campaigns including parameter sweeps, batch jobs, and result aggregation. Use for running parameter studies, managing simulation batches, tracking job status, combining results from multiple runs, or automating simulation workflows.Votes: 0GitHub stars: 11
- Simulation ValidatorValidate simulations before, during, and after execution. Use for pre-flight checks, runtime monitoring, post-run validation, diagnosing failed simulations, checking convergence, detecting NaN/Inf, or verifying mass/energy conservation.Votes: 0GitHub stars: 11
- Site ArchitectureTechnical SEO - robots.txt, sitemap, meta tags, Core Web VitalsVotes: 0GitHub stars: 11
- SkypilotMulti-cloud orchestration for ML workloads with automatic cost optimization. Use when you need to run training or batch jobs across multiple clouds, leverage spot instances with auto-recovery, or optimize GPU costs across providers.Votes: 0GitHub stars: 11
- SlimeProvides guidance for LLM post-training with RL using slime, a Megatron+SGLang framework. Use when training GLM models, implementing custom data generation workflows, or needing tight Megatron-LM integration for RL scaling.Votes: 0GitHub stars: 11
- Slurm Job Script GeneratorGenerate SLURM `sbatch` job scripts and sanity-check HPC resource requests (nodes, tasks, CPUs, memory, GPUs) for simulation runs. Use when preparing submission scripts, deciding MPI vs MPI+OpenMP layouts, standardizing `#SBATCH` directives, or debugging job launch configuration (`sbatch`/`srun`).Votes: 0GitHub stars: 11
- Soft SkillTeaches the AI to design like a high-end agency. Defines the exact fonts, spacing, shadows, card structures, and animations that make a website feel expensive. Blocks all the common defaults that make AI designs look cheap or generic.Votes: 0GitHub stars: 11
- Soul ArchitectDesign the complete identity stack for any AI agent. Creates SOUL.md, IDENTITY.md, AGENTS.md, USER.md, and HEARTBEAT.md files tailored to the agent purpose. Covers personality design, behavioral rules, workflow procedures, memory initialization, and cross-model testing.Votes: 0GitHub stars: 11
- Speckit UpdaterThis skill provides safe update capabilities for GitHub SpecKit installations, preserving customizations while applying template updates. **Installation**: Available via plugin (`/plugin marketplace add NotMyself/claude-plugins` then `/plugin install speckit-updater`) or manual Git clone. See [README.md](../../README.md#installation) for details.Votes: 0GitHub stars: 11
- Speculative DecodingAccelerate LLM inference using speculative decoding, Medusa multiple heads, and lookahead decoding techniques. Use when optimizing inference speed (1.5-3.6× speedup), reducing latency for real-time applications, or deploying models with limited compute. Covers draft models, tree-based attention, Jacobi iteration, parallel token generation, and production deployment strategies.Votes: 0GitHub stars: 11
- SpeedLaunch RSVP speed reader for textVotes: 0GitHub stars: 11
- Stable Baselines3Production-ready reinforcement learning algorithms (PPO, SAC, DQN, TD3, DDPG, A2C) with scikit-learn-like API. Use for standard RL experiments, quick prototyping, and well-documented algorithm implementations. Best for single-agent RL with Gymnasium environments. For high-performance parallel training, multi-agent systems, or custom vectorized environments, use pufferlib instead.Votes: 0GitHub stars: 11
- 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: 11
- Statistical AnalysisGuided statistical analysis with test selection and reporting. Use when you need help choosing appropriate tests for your data, assumption checking, power analysis, and APA-formatted results. Best for academic research reporting, test selection guidance. For implementing specific models programmatically use statsmodels.Votes: 0GitHub stars: 11
- StatsmodelsStatistical models library for Python. Use when you need specific model classes (OLS, GLM, mixed models, ARIMA) with detailed diagnostics, residuals, and inference. Best for econometrics, time series, rigorous inference with coefficient tables. For guided statistical test selection with APA reporting use statistical-analysis.Votes: 0GitHub stars: 11
- Stitch SkillSemantic Design System Skill for Google Stitch. Generates agent-friendly DESIGN.md files that enforce premium, anti-generic UI standards — strict typography, calibrated color, asymmetric layouts, perpetual micro-motion, and hardware-accelerated performance.Votes: 0GitHub stars: 11
- String DatabaseQuery STRING API for protein-protein interactions (59M proteins, 20B interactions). Network analysis, GO/KEGG enrichment, interaction discovery, 5000+ species, for systems biology.Votes: 0GitHub stars: 11
- SwanlabProvides guidance for experiment tracking with SwanLab. Use when you need open-source run tracking, local or self-hosted dashboards, and lightweight media logging for ML workflows.Votes: 0GitHub stars: 11
- 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: 11
- Task DistributorUse when distributing tasks across multiple agents or workers, managing queues, and balancing workloads to maximize throughput while respecting priorities and deadlines.Votes: 0GitHub stars: 11
- Team CoordinationMulti-person projects - shared state, todo claiming, handoffsVotes: 0GitHub stars: 11
- TensorboardVisualize training metrics, debug models with histograms, compare experiments, visualize model graphs, and profile performance with TensorBoard - Google's ML visualization toolkitVotes: 0GitHub stars: 11
- Ticket CraftCreate Jira/Asana/Linear tickets optimized for Claude Code execution - AI-native ticket writingVotes: 0GitHub stars: 11
- TiledbvcfEfficient storage and retrieval of genomic variant data using TileDB. Scalable VCF/BCF ingestion, incremental sample addition, compressed storage, parallel queries, and export capabilities for population genomics.Votes: 0GitHub stars: 11
- Time SteppingPlan and control time-step policies for simulations. Use when coupling CFL/physics limits with adaptive stepping, ramping initial transients, scheduling outputs/checkpoints, or planning restart strategies for long runs.Votes: 0GitHub stars: 11
- Timesfm ForecastingZero-shot time series forecasting with Google's TimesFM foundation model. Use for any univariate time series (sales, sensors, energy, vitals, weather) without training a custom model. Supports CSV/DataFrame/array inputs with point forecasts and prediction intervals. Includes a preflight system checker script to verify RAM/GPU before first use.Votes: 0GitHub stars: 11
- Token MinterGenerate, build, and deploy custom ERC20 tokens on EVM networks. Use when users want to create and deploy their own ERC20 tokens with custom parameters like name, symbol, decimals, and initial supply. Supports deployment to various networks including Sepolia testnet and requires Foundry (forge/cast) for blockchain interactions.Votes: 0GitHub stars: 11
- Torch GeometricGraph Neural Networks (PyG). Node/graph classification, link prediction, GCN, GAT, GraphSAGE, heterogeneous graphs, molecular property prediction, for geometric deep learning.Votes: 0GitHub stars: 11
- TorchdrugPyTorch-native graph neural networks for molecules and proteins. Use when building custom GNN architectures for drug discovery, protein modeling, or knowledge graph reasoning. Best for custom model development, protein property prediction, retrosynthesis. For pre-trained models and diverse featurizers use deepchem; for benchmark datasets use pytdc.Votes: 0GitHub stars: 11
- TorchforgeProvides guidance for PyTorch-native agentic RL using torchforge, Meta's library separating infra from algorithms. Use when you want clean RL abstractions, easy algorithm experimentation, or scalable training with Monarch and TorchTitan.Votes: 0GitHub stars: 11
- TorchtitanProvides PyTorch-native distributed LLM pretraining using torchtitan with 4D parallelism (FSDP2, TP, PP, CP). Use when pretraining Llama 3.1, DeepSeek V3, or custom models at scale from 8 to 512+ GPUs with Float8, torch.compile, and distributed checkpointing.Votes: 0GitHub stars: 11
- Trading StrategistProvides trading strategies for cryptocurrencies based on Binance market data, calculated technical analysis indicators, and aggregated market sentiment from crypto RSS news feeds. Use when users ask for trading advice, strategy recommendations, or analysis combining price data, TA, and sentiment for crypto assets like ETH, BTC, or altcoins.Votes: 0GitHub stars: 11
- 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: 11
- TransformersThis skill should be used when working with pre-trained transformer models for natural language processing, computer vision, audio, or multimodal tasks. Use for text generation, classification, question answering, translation, summarization, image classification, object detection, speech recognition, and fine-tuning models on custom datasets.Votes: 0GitHub stars: 11
- Treatment PlansGenerate concise (3-4 page), focused medical treatment plans in LaTeX/PDF format for all clinical specialties. Supports general medical treatment, rehabilitation therapy, mental health care, chronic disease management, perioperative care, and pain management. Includes SMART goal frameworks, evidence-based interventions with minimal text citations, regulatory compliance (HIPAA), and professional formatting. Prioritizes brevity and clinical actionability.Votes: 0GitHub stars: 11
- 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: 11
- TypescriptTypeScript strict mode with eslint and jestVotes: 0GitHub stars: 11
- Ui MobileMobile UI patterns - React Native, iOS/Android, touch targetsVotes: 0GitHub stars: 11
- Ui TestingVisual testing - catch invisible buttons, broken layouts, contrastVotes: 0GitHub stars: 11
- Ui WebWeb UI - glassmorphism, Tailwind, dark mode, accessibilityVotes: 0GitHub stars: 11
- Umap LearnUMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualization, clustering preprocessing (HDBSCAN), supervised/parametric UMAP, for high-dimensional data.Votes: 0GitHub stars: 11