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SkillsMP は stanfish06/skillquarium から 1,211 件の skill を収集しています。skill を開くとソースと詳細を確認できます。
stanfish06/skillquarium収集済み skill 1,211 件中 40 件を表示しています。
Machine learning in Python with scikit-learn. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), model evaluation, hyperparameter tuning, preprocessing, or building ML…
原文の言語: 英語
Single-cell immune receptor analysis with Scirpy for scanpy, anndata, and scvi-tools projects. Use for TCR/BCR V(D)J import, clonotype definition, clonal expansion, repertoire overlap, immune receptor QC, MuData/AnnData integration, and Scanpy-linked immune…
原文の言語: 英語
Use when the user's host screen must be captured — the full desktop, one monitor, or a pixel region — or when a screen capture needs cropping, resizing, rotation, flipping, format conversion (png/jpeg/webp), quality control, or filters/enhancement; also when…
原文の言語: 英語
Standard scRNA-seq preprocessing and clustering with Scanpy. Use for QC, normalization, HVG selection, PCA, neighbor graph construction, UMAP, Leiden clustering, and export of an analysis-ready AnnData object.
原文の言語: 英語
RNA velocity analysis with scVelo. Estimate cell state transitions from unspliced/spliced mRNA dynamics, infer trajectory directions, compute latent time, and identify driver genes in single-cell RNA-seq data. Complements Scanpy/scVI-tools for trajectory…
原文の言語: 英語
Deep generative models for single-cell omics. Use when you need probabilistic batch correction (scVI), transfer learning, differential expression with uncertainty, or multi-modal integration (TOTALVI, MultiVI). Best for advanced modeling, batch effects,…
原文の言語: 英語
SEC (size-exclusion chromatography) analysis with peak detection, oligomer classification, and publication-quality PDF report generation via Typst templates. Triggers on "SEC", "size exclusion", "chromatography", "oligomer analysis", "protein assembly", "SEC…
原文の言語: 英語
Use when the user asks for a security review of a pull request, commit, branch diff, working-tree patch, or other Git-backed change set.
原文の言語: 英語
Use for a standard, single-pass security audit of an entire repository or a scoped path, package folder, or submodule with no diff to review. This is the default repository scan. Do not use for PR/commit/branch/working-tree diffs, or for deep, multi-pass, or…
原文の言語: 英語
Install a .NET SDK locally for safe preview testing, specific-version pinning, or reproducible team setups — without modifying the system-wide installation. USE FOR: trying .NET previews safely, testing specific SDK versions, installing MAUI or other…
原文の言語: 英語
Single-cell RNA-seq analysis in R with Seurat v5 — QC, normalization (LogNormalize or SCTransform), dimensionality reduction, clustering, marker detection, integration of multiple samples, and interconversion with AnnData/scanpy. Use when single-cell work…
原文の言語: 英語
Model 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),…
原文の言語: 英語
Prepares production launches. Use when preparing to deploy to production. Use when you need a pre-launch checklist, when setting up monitoring, when planning a staged rollout, or when you need a rollback strategy.
原文の言語: 英語
Scaffold a new ClawBio skill from a spec file (JSON/YAML) or interactively — generates SKILL.md, Python skeleton, tests, and updates catalog.json
原文の言語: 英語
Python-based workflow manager for reproducible, scalable pipelines. Define rules with file-based dependencies; Snakemake resolves execution order and parallelism. Runs local, SLURM, LSF, AWS, GCP via profiles; per-rule conda/Singularity envs. For NGS…
原文の言語: 英語
MinHash/FracMinHash sketching for alignment-free comparison of genomes and metagenomes. Use for fast all-vs-all genome similarity and ANI estimation across thousands of genomes without alignment, taxonomic classification of metagenomes against GTDB/NCBI…
原文の言語: 英語
Creates specs before coding. Use when starting a new project, feature, or significant change and no specification exists yet. Use when requirements are unclear, ambiguous, or only exist as a vague idea.
原文の言語: 英語
Runs the Spec-Kit (GitHub SDD) artifact pipeline — constitution, spec, clarify, plan, tasks, analyze, implement — using its templates. Use when a feature needs a versioned spec/plan/tasks set under specs/NNN-feature/, when requirements must be pinned before…
原文の言語: 英語
Generate and normalize 2D sprite animations. Use when the user asks for full-strip generation from approved source frames, consistent anchor and scale normalization, or preview assets for browser-game animation.
原文の言語: 英語
Production-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…
原文の言語: 英語
Guided statistical analysis for research data - test selection, assumption checking, effect sizes, power analysis, Bayesian alternatives, and APA-formatted reporting. Use whenever a user wants to compare groups, test a hypothesis, analyze experimental or…
原文の言語: 英語
Semantic 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.
原文の言語: 英語
Structure retrieval, confidence-aware AlphaFold DB usage, coordinate download, PAE and pLDDT interpretation, and structure-guided biological annotation.
原文の言語: 英語
Postgres performance optimization and best practices from Supabase. Use this skill when writing, reviewing, or optimizing Postgres queries, schema designs, or database configurations.
原文の言語: 英語
Canonical rules and HTML/CSS contract for the page chrome (head boilerplate, cover, table of contents, section block, sources-section wrapper, footer, outlook-badge, design tokens) shared across Moody's Agentic Solutions HTML report skills…
原文の言語: 英語
Terraform and OpenTofu infrastructure-as-code (IaC) — declare cloud/SaaS resources in HCL, manage state with remote backends and locking, author and consume modules, and run the init/plan/apply/destroy lifecycle. Use whenever the user mentions Terraform,…
原文の言語: 英語
Performs pseudo-mutation analysis on production code in any language to find gaps in existing tests. Use when the user asks to find weak or shallow tests, discover untested edge cases, or check whether tests would catch a bug — e.g. "would my tests catch it…
原文の言語: 英語
Analyzes test suites in any language and tags each test with standardized traits (positive, negative, critical-path, boundary, smoke, regression, integration, performance, security). Use when the user wants to categorize, audit, or label tests with traits.…
原文の言語: 英語
Use when Codex is already in the threat-modeling phase of a security scan, the user explicitly invokes $threat-model, or the user explicitly asks to create, update, or persist a repository threat model. Do not use as the primary trigger for full PR, commit,…
原文の言語: 英語
Implement browser-game runtimes with plain Three.js. Use when the user wants imperative scene control in TypeScript or Vite with GLB assets, loaders, physics, and low-level WebGL debugging.
原文の言語: 英語
Efficient 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.
原文の言語: 英語
PyTorch Geometric (PyG) for graph neural networks — node/link/graph classification, message passing (GCN, GAT, GraphSAGE, GIN), heterogeneous graphs, neighbor sampling, and custom datasets. Use when working with torch_geometric, not for general NetworkX…
原文の言語: 英語
PyTorch-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…
原文の言語: 英語
Hugging Face Transformers for loading Hub models, running pipeline inference, text generation, and Trainer fine-tuning on NLP, vision, audio, and multimodal tasks. Use when working with AutoModel, pipelines, tokenizers, or TrainingArguments—not for general ML…
原文の言語: 英語
Generate 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.…
原文の言語: 英語
Use when the user supplies or imports existing security findings, vulnerability reports, or security/vulnerability Jira/Linear tickets from scanners, advisories, GitHub, Atlassian Rovo, Linear, or similar backlog sources and wants static repo-impact triage.…
原文の言語: 英語
Build, query, and analyse biomedical knowledge graphs in TuringDB, a columnar graph database with git-like versioning.
原文の言語: 英語
Use when building Twilio Enterprise Knowledge workflows for AI or human agents, including provisioning a knowledge base, adding website, PDF, or text sources, semantic search, or grounding responses in approved organization content. Use this for enterprise…
原文の言語: 英語
Specifies CSS-level implementation primitives for UI work — OKLCH palette construction, motion duration and easing tokens, interactive and input state coverage, text-on-fill contrast pairing, and framework-agnostic responsive-correctness bugs. Use when…
原文の言語: 英語
Builds and modifies dbt models, writes SQL transformations using ref() and source(), creates tests, and validates results with dbt show. Use when doing any dbt work - building or modifying models, debugging errors, exploring unfamiliar data sources, writing…
原文の言語: 英語