Comprehensive collection of 128+ ready-to-use scientific skills for Claude enabling research across biology, chemistry, medicine, genomics, and advanced analysis domains.
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A comprehensive collection of 128+ ready-to-use scientific skills that transforms Claude into an AI research assistant capable of executing complex multi-step scientific workflows.
Sequence analysis, single-cell RNA-seq, gene regulatory networks, variant annotation, phylogenetic analysis
Molecular property prediction, virtual screening, ADMET analysis, molecular docking, lead optimization
LC-MS/MS processing, peptide identification, spectral matching, protein quantification
Clinical trials, pharmacogenomics, variant interpretation, drug safety, precision therapeutics
EHR analysis, physiological signal processing, medical imaging, clinical prediction models
DICOM processing, whole slide image analysis, computational pathology, radiology workflows
Deep learning, reinforcement learning, time series analysis, model interpretability, Bayesian methods
Crystal structure analysis, phase diagrams, metabolic modeling, computational chemistry
Astronomical data analysis, cosmological calculations, symbolic mathematics, physics computations
Discrete-event simulation, optimization, metabolic engineering, systems modeling
Each skill within this collection includes:
Explore the scientific-skills/ subdirectory for individual skill implementations and detailed documentation.
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概要と使いどころ
Testing patterns for PHPUnit and Playwright E2E tests. Use when writing tests, debugging test failures, setting up test coverage, or implementing test patterns for ActivityPub features.
日本語の概要は準備中です。原文の説明を表示しています。
Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.
日本語の概要は準備中です。原文の説明を表示しています。
Add unsigned integer (uint) type support to PyTorch operators by updating AT_DISPATCH macros. Use when adding support for uint16, uint32, uint64 types to operators, kernels, or when user mentions enabling unsigned types, barebones unsigned types, or uint support.
日本語の概要は準備中です。原文の説明を表示しています。
This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.
日本語の概要は準備中です。原文の説明を表示しています。
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
日本語の概要は準備中です。原文の説明を表示しています。
Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
日本語の概要は準備中です。原文の説明を表示しています。