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概要と使いどころ
Bulk RNA-seq DE with PyDESeq2: load counts, normalize, fit negative binomial models, Wald test (BH-FDR), LFC shrinkage, volcano/MA plots. Use for two-group comparisons, multi-factor designs with batch correction, multiple contrasts.
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。
Monarch Initiative knowledge graph REST API for disease-gene-phenotype associations and cross-species orthology. MONDO disease-to-gene/phenotype, HP phenotype profiles, cross-species comparisons. Use for rare disease gene prioritization and phenotype-based candidate ranking. For GWAS use gwas-database; for clinical pathogenicity use clinvar-database.
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。
Python library for genomic interval ML. Train/apply region2vec embeddings turning BED regions into vectors, index interval datasets for ML, search embedding space with BEDSpace, and evaluate embedding quality. Use for chromatin accessibility clustering, regulatory element classification, and cross-sample region comparison.
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。
Retrieve mouse phenotype data from the Jackson Laboratory Mouse Phenome Database (MPD) via its REST API. Browse 520+ projects, look up per-project measure metadata, pull strain-level means (raw or LS-mean adjusted) and per-animal values, find measures by MP/VT ontology terms, and resolve strain nomenclature or gene coordinates. Use for QTL support, cross-strain comparison, mouse model selection, and ontology-driven phenotype discovery. Use monarch-database for disease-gene-phenotype knowledge graphs; ensembl-database for mouse genome annotations.
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。
Guide to KEGG pathway enrichment for DEG results. Covers ORA vs GSEA, mandatory directionality splitting, KEGG organism codes, API failure handling with offline fallbacks, cross-condition comparisons, and answer-first reporting. Consult when running enrichment with clusterProfiler or gseapy.
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。
Guide for annotating statistical significance (p-value asterisks) on comparison plots. Covers standard notation (ns, *, **, ***, ****), matplotlib bracket+asterisk implementation, and use with seaborn box/violin/bar plots. Use when preparing publication-ready figures with significance markers.
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。
3Dmol.js WebGL molecular visualization emitted as self-contained HTML. Render structures (PDB/SDF/XYZ/MOL2/cube) with stick, sphere, cartoon, line, and surface styles; animate trajectories with a frame-delay (interval, ms) control; and animate vibrational normal modes via vibrate() from per-atom dx/dy/dz displacements or from precomputed frames. Output standalone HTML that loads 3Dmol from a CDN, with optional play/pause and speed controls. Use for transition-state imaginary-mode animations, MD or reaction-path playback, docking poses, and orbital/density isosurfaces. For static 2D chemical structure drawings use rdkit-chemdraw-cdxml; for 2D statistical plots use matplotlib or plotly.
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。
Bayesian modeling with PyMC 5: priors, likelihood, NUTS/ADVI sampling, diagnostics (R-hat, ESS), LOO/WAIC comparison, prediction. Hierarchical, logistic, GP variants; predictive checks.
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。
Security hardening and best practices for robotic systems, covering SROS2 DDS security, network segmentation, secrets management, secure boot, and the physical-cyber safety intersection. Use this skill when securing ROS2 communications, configuring DDS encryption and access control, hardening robot onboard computers, managing certificates and credentials, setting up network segmentation for robot fleets, or addressing the unique security challenges where cyber vulnerabilities become physical safety risks. Trigger whenever the user mentions SROS2, DDS security, robot security, robot hardening, ROS2 encryption, ROS2 access control, robot network security, secure robot deployment, robot certificates, keystore generation, robot firewall, e-stop security, safety controller isolation, or IEC 62443 for robotics.
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 tax-related questions, wants advice on deductions or tax savings, or needs expert guidance equivalent to a tax accountant (税理士) or life planner. Trigger phrases include: "税金について教えて", "控除は使える？", "確定申告の相談", "節税", "ふるさと納税の上限", "iDeCoの効果", "住宅ローン控除", "青色申告のメリット", "消費税はかかる？", "扶養に入れる？", "配偶者控除", "医療費控除", "法人成り", "経費になる？", "税率を教えて", "所得税の計算", "住民税", "社会保険料", "103万の壁", "130万の壁", "インボイス", "簡易課税", "税制改正", "開業届", "副業バレ", "白色申告", "税務調査", "特定支出控除", "予定納税", "中間納付".
Use swift-snapshot-testing to visually verify SwiftUI views during implementation. Renders views to PNG for comparison against design references. Fast feedback loop (~25s/cycle).
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。
Diagnose and fix Swift strict-concurrency warnings in WooCommerce iOS. Use for Swift 6 migration, actor-isolation changes, and Sendable diagnostics in this repository.
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。
Provides patterns for unit testing mappers, converters, and bean mappings. Validates entity-to-DTO and model transformation logic in isolation. Generates executable mapping tests with MapStruct and custom converter test coverage. Use when writing mapping tests, converter tests, entity mapping tests, or ensuring correct data transformation between DTOs and domain objects.
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。
Provides patterns for unit testing service layer with Mockito. Creates isolated tests that mock repository calls, verify method invocations, test exception scenarios, and stub external API responses. Use when testing service behaviors and business logic without database or external services.
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。
Provides patterns for unit testing REST controllers using MockMvc and @WebMvcTest. Generates controller tests that validates request/response mapping, validation, exception handling, and HTTP status codes. Use when testing web layer endpoints in isolation for API endpoint testing, Spring MVC tests, mock HTTP requests, or controller layer unit tests.
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。
When the user needs to prepare for SOC 2, build a compliance roadmap, assess security posture, quantify security risk, or says "we need SOC 2", "security audit", "compliance", "enterprise customer wants SOC 2", "CISO advice".
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。
When a founder needs demo scripts, discovery call frameworks, objection handling, RFP/RFI responses, competitive feature matrices, POC planning, or closing playbooks. Activate for sales calls, demo prep, talk tracks, bid responses, competitor comparisons, or pre-sales engineering.
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。
Check data compliance with construction standards. Validate data against ISO 19650, IFC, COBie, UniFormat standards.
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。
Process drone survey data for construction sites. Generate orthomosaics, DEMs, point clouds, calculate volumes, track progress, and integrate with BIM models for comparison.
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。
Orchestrate multiple AI agents for construction workflows: estimator, scheduler, document, QA and safety agents coordinated by a supervisor agent, with human checkpoints. Use when automating end-to-end project processes with agentic AI.
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。
Databricks Model Serving endpoint lifecycle and ops. Use when asked to: CRUD serving endpoints (CLI or MLflow Deployments client); configure traffic routing for A/B / canary deploys and zero-downtime version swaps; retrieve OpenAPI schemas; inspect logs, metrics, or permissions; manage legacy AI Gateway rate limits (not Unity Gateway); discover Foundation Model API endpoints at runtime; integrate endpoints into Databricks Apps; or stream from off-platform clients (Vercel AI SDK v6, standalone Node.js). NOT for: Unity Gateway CRUD and management (databricks-unity-gateway), training, MLflow autologging, UC registration, custom PyFunc/ResponsesAgent authoring (databricks-ml-training); Knowledge Assistants/Supervisor Agents (databricks-agent-bricks); MLflow evaluation (databricks-mlflow-evaluation).
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 Agent Bricks: Knowledge Assistants (KA) for document Q&A and Supervisor Agents for multi-agent orchestration (MAS).
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 structured podcast episodes. Segment timing, debate points, hot takes, listener questions, ad break placement.
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。
Reviews pitch decks and investor presentations. Reads slide content, evaluates narrative flow, problem/solution clarity, market sizing, competitive positioning, financial projections, team credibility, and ask clarity. Generates a scored pitch-review.md with slide-by-slide feedback, overall score, top improvements, investor objection predictions, and comparisons to successful decks. Use when reviewing fundraising materials, investor decks, or pitch presentations.
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。