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概要と使いどころ
React composition patterns that scale. Use when refactoring components with boolean prop proliferation, building flexible component libraries, or designing reusable APIs. Triggers on tasks involving compound components, render props, context providers, or component architecture. Includes React 19 API changes.
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。
群众路线：从持有真实情况的多方（用户、使用者、代码库、日志、运行结果）收集分散意见，系统化为方案，再带回去对齐与检验，循环改进。当多方意见分歧、需要汇总零散反馈、方案要拿回给真实使用者确认、或你发觉自己在闭门造车时触发；信息源单一且完整、处于执行阶段时不触发。 English: Mass line. Collect scattered input from everyone who holds ground truth (users, operators, codebase, logs, runtime results), synthesize it into a coherent plan, take it back for alignment and validation, and iterate. Trigger when inputs conflict, feedback must be consolidated, a plan needs sign-off from real users, or you sense you are designing in isolation; skip when there is a single complete source and the work is pure execution.
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。
World-class prompt engineering skill for LLM optimization, prompt patterns, structured outputs, and AI product development. Expertise in Claude, GPT-4, prompt design patterns, few-shot learning, chain-of-thought, and AI evaluation. Includes RAG optimization, agent design, and LLM system architecture. Use when building AI products, optimizing LLM performance, designing agentic systems, or implementing advanced prompting techniques.
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。
World-class data science skill for statistical modeling, experimentation, causal inference, and advanced analytics. Expertise in Python (NumPy, Pandas, Scikit-learn), R, SQL, statistical methods, A/B testing, time series, and business intelligence. Includes experiment design, feature engineering, model evaluation, and stakeholder communication. Use when designing experiments, building predictive models, performing causal analysis, or driving data-driven decisions.
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Estimate causal effects from existing data. Use when fitting or interpreting DiD, ITS, synthetic control, regression discontinuity, or other treatment-effect analyses, including robustness checks and counterfactual plots. For choosing a study design before analysis, use designing-experiments instead.
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。
Design experiments and quasi-experiments before analysis. Use when choosing study design, treatment/control structure, outcomes, assumptions, validation plans after scientific experiment failure, or which of DiD, ITS, synthetic control, or regression discontinuity fits the research question. For fitting models or estimating effects on existing data, use performing-causal-analysis instead.
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。
Comprehensive data visualization toolkit for creating beautiful, mathematically elegant visualizations with D3.js, Chart.js, and custom SVG. Use when (1) building interactive data visualizations, (2) designing color palettes for charts, (3) choosing scales and visual encodings, (4) creating data pipelines from Census/SEC/Wikipedia APIs, (5) crafting narrative-driven data stories, (6) making perceptually accurate charts, or (7) implementing force-directed networks, timelines, or geographic maps.
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。
Use this skill when the user is doing hands-on DOCA GPUNetIO programming — wiring a CUDA kernel on an NVIDIA GPU to a doca-eth queue via doca_gpu_eth_rxq / doca_gpu_eth_txq, standing up the per-CUDA-device doca_gpu context, designing the persistent CUDA kernel that drains the GPU-visible queue, running the dual capability check (DOCA cap-query plus cudaGetDeviceProperties), registering cudaMalloc pools via doca_buf_arr_create_*, or debugging DOCA_ERROR_* returns from the GPUNetIO API. Trigger even when the user does not explicitly mention "DOCA GPUNetIO" or "persistent kernel" — typical implicit phrasings include "CUDA kernel reading packets directly from the NIC", "GPU-initiated networking on BlueField", "DOCA_ERROR_DRIVER on doca_gpu_create", "nvidia_peermem not loaded", "kernel-per-packet is too slow", or "which GPU supports GPU-side packet I/O". Refuse and route elsewhere for general CUDA programming, DOCA Ethernet queue bring-up, DOCA DPA, or DOCA install — those belong to other skills.
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。
Apply and maintain the wiki's controlled tag vocabulary. Use for choosing, normalizing, auditing, or extending tags when creating or updating wiki pages; consult the taxonomy before assigning tags.
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。
Idiomatic context.Context usage in Golang — propagation through API boundaries, cancellation, timeouts and deadlines, request-scoped values, context.WithoutCancel for background work outliving requests. Apply when designing context propagation across layers, debugging leaked or unexpired contexts, choosing between context.Background/TODO/WithoutCancel, or storing values in context. Not for code that merely accepts ctx as first parameter.
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。
Idiomatic Golang design patterns — functional options, constructor APIs, `init()` and global-state avoidance, enums, panic vs error decisions, resource management and lifecycle, graceful shutdown, timeouts and retries, streaming and iterators, and architecture styles (clean, hexagonal, DDD, flat). Apply when choosing between architectural patterns, implementing functional options, designing constructor APIs, setting up graceful shutdown, applying resilience patterns, or asking which idiomatic Go pattern fits a specific problem. Not for wiring a DI container or comparing DI libraries (→ See `samber/cc-skills-golang@golang-dependency-injection` skill), nor for error wrapping, `errors.Is`/`As`, or logging mechanics (→ See `samber/cc-skills-golang@golang-error-handling` skill).
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。
Implements GraphQL APIs in Golang using gqlgen or graphql-go. Apply when building GraphQL servers, designing schemas, writing resolvers, handling subscriptions, or integrating GraphQL with existing Go HTTP services. Also apply when the codebase imports `github.com/99designs/gqlgen` or `github.com/graph-gophers/graphql-go`.
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。
Golang struct and interface design patterns — composition, embedding, type assertions, type switches, interface segregation, dependency injection via interfaces, struct field tags, and pointer vs value receivers. Use this skill when designing Go types, defining or implementing interfaces, embedding structs or interfaces, writing type assertions or type switches, adding struct field tags for JSON/YAML/DB serialization, or choosing between pointer and value receivers. Also use when the user asks about "accept interfaces, return structs", compile-time interface checks, or composing small interfaces into larger ones.
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。
Troubleshoot Golang programs systematically - find and fix the root cause. Use when encountering bugs, crashes, deadlocks, races, or unexpected behavior in Go code. Covers debugging methodology, common Go pitfalls, test-driven debugging, pprof setup and capture, Delve, race detection, GODEBUG tracing, and production debugging. Start here for any 'something is wrong' situation. Not for interpreting profiles or benchmarking (→ See `samber/cc-skills-golang@golang-benchmark` skill), applying optimization patterns (→ See `samber/cc-skills-golang@golang-performance` skill), or designing new code (→ See `samber/cc-skills-golang@golang-safety` skill for defensive coding, `samber/cc-skills-golang@golang-concurrency` skill for concurrency design).
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。
Comprehensive guide for dependency injection (DI) in Golang. Covers why DI matters (testability, loose coupling, separation of concerns, lifecycle management), manual constructor injection, and DI library comparison (google/wire, uber-go/dig, uber-go/fx, samber/do). Use this skill when designing service architecture, setting up dependency injection, refactoring tightly coupled code, managing singletons or service factories, or when the user asks about inversion of control, service containers, or wiring dependencies in Go. For a specific DI library, → See `samber/cc-skills-golang@golang-google-wire`, `samber/cc-skills-golang@golang-uber-dig`, `samber/cc-skills-golang@golang-uber-fx`, or `samber/cc-skills-golang@golang-samber-do` skills.
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。
[omh] Releasing an iOS or Android app through the stores -- signing, the privacy manifest, a TestFlight or Play beta, a staged rollout, a hotfix: prepare each gate the store enforces, and plan the halt and the next build before the rollout starts, because a store release cannot be rolled back. Use when the user says: mobile-release, mobile release, mobile app release, ios release, android release, app store release, app store submission, submit to the app store.
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。
[omh] Designing an API, server, or data-layer change: prepare server, API, and data-layer contracts — auth boundary, error paths, response shape, and schema/migration discipline — before implementation. Use when the user says: backend, back-end, back end, backend skill, server side, server-side, api design, api contract.
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。
[omh] Designing or reviewing an iOS, macOS, or Apple-style UI: prepare native Apple UI or Apple marketing product-visual direction, review, and improvement briefs with evidence-backed remediation handoffs. Use when the user says: apple-design, apple design, apple ui design, apple hig, human interface guidelines, ios design guidelines, macos app design, apple-inspired web.
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。
How the reference commerce agents of either role are structured, covering the loop, where each rule lives, skills, the backend interface, delegates, and model fields. Load when designing or reviewing the structure of a shopping or merchant agent.
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。
Comprehensive QA and testing skill for quality assurance, test automation, and testing strategies for ReactJS, NextJS, NodeJS applications. Includes test suite generation, coverage analysis, E2E testing setup, and quality metrics. Use when designing test strategies, writing test cases, implementing test automation, performing manual testing, or analyzing test coverage.
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。
Manage cryptographic keys using Azure Key Vault Keys SDK for JavaScript (@azure/keyvault-keys). Use when creating, encrypting/decrypting, signing, or rotating keys.
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。
Azure Key Vault Keys SDK for .NET. Client library for managing cryptographic keys in Azure Key Vault and Managed HSM. Use for key creation, rotation, encryption, decryption, signing, and verification. Triggers: "Key Vault keys", "KeyClient", "CryptographyClient", "RSA key", "EC key", "encrypt decrypt .NET", "key rotation", "HSM".
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。
Transform the agent into a Cloud Solution Architect following Azure Architecture Center best practices. Use when designing cloud architectures, reviewing system designs, selecting architecture styles, applying cloud design patterns, making technology choices, or conducting Well-Architected Framework reviews.
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。