2,423 件 ・ 関連度順
概要と使いどころ
This skill should be used when the user asks to "create AGENTS.md", "update AGENTS.md", "maintain agent docs", "set up CLAUDE.md", or needs to keep agent instructions concise. Enforces research-backed best practices for minimal, high-signal agent documentation.
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。
Presents a risk framework for every configurable security control in NemoClaw. Use when evaluating security posture, reviewing sandbox security defaults, or assessing control trade-offs. Trigger keywords - nemoclaw security best practices, sandbox security controls risk framework, nemoclaw credential storage, credentials.json, api key security, openclaw security controls, nemoclaw security boundary, prompt injection, tool access control.
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。
Review UI code for Web Interface Guidelines compliance. Use when asked to "review my UI", "check accessibility", "audit design", "review UX", or "check my site against best practices".
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。
High-level PyTorch framework with Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks system, and minimal boilerplate. Scales from laptop to supercomputer with same code. Use when you want clean training loops with built-in best practices.
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。
Generate images using nano-banana-2 MCP tools with best-practice prompting. Use this skill when the user asks to create, generate, or edit images.
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。
React Native and Expo best practices for building performant mobile apps. Use when building React Native components, optimizing list performance, implementing animations, or working with native modules. Triggers on tasks involving React Native, Expo, mobile performance, or native platform APIs.
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。
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
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。
Review UI code for Web Interface Guidelines compliance. Use when asked to "review my UI", "check accessibility", "audit design", "review UX", or "check my site against best practices".
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 a PostgreSQL-specific schema. Covers best-practices, data types, indexing, constraints, performance patterns, and advanced 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。
Create employment contracts, offer letters, and HR policy documents following legal best practices. Use when drafting employment agreements, creating HR policies, or standardizing employment documentation.
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 effective code review practices to provide constructive feedback, catch bugs early, and foster knowledge sharing while maintaining team morale. Use when reviewing pull requests, establishing review standards, or mentoring developers.
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。
Write and maintain Architecture Decision Records (ADRs) following best practices for technical decision documentation. Use when documenting significant technical decisions, reviewing past architect...
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。
Software architecture patterns and best practices
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 API design patterns covering REST, GraphQL, gRPC, versioning, authentication, and modern API best practices
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。
AI基础设施实战——从GPU集群调度到模型推理部署的全栈实操指南。覆盖：昇腾/GPU统一调度、PyTorch分布式训练、vLLM推理部署、模型量化实战、LLMOps、GPU故障诊断、HuggingFace生态、MLOps流水线。触发词：AI基础设施、GPU、昇腾、训练、推理、vLLM、PyTorch分布式、模型部署、LLMOps、MLOps、集群调度、HuggingFace
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。
Google-grade software engineering culture encompassing Code Readability, Design Doc Review, Blameless Postmortem, Testing Philosophy, Code Review standards, and engineering excellence practices distilled from Google's internal engineering culture documented in "Software Engineering at Google" and real Google/Brain/DeepMind experience. USE WHEN: establishing engineering standards, reviewing code quality, designing development workflows, onboarding engineers, setting code review guidelines, adopting Google-level engineering excellence, or building an engineering culture that promotes maintainability, readability, and quality.
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。
Writes production-quality Pine Script v6 code following TradingView guidelines and best practices. Use when implementing indicators, strategies, or any Pine Script code. Triggers on requests to create, write, implement, or code Pine Script functionality.
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。
Audit GDPR compliance, generate privacy policies, and document data flows. Use when auditing practices, drafting policies, or checking consent flows.
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。
Compare cross-border e-commerce shipping options, packaging tactics, customs-risk signals, and speed-versus-cost tradeoffs for sellers, operations teams, and marketplace operators. Use when choosing routes, carriers, declaration practices, or packaging plans for parcel shipments without relying on live carrier APIs.
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。
Creates and refines Founder Story and brand narrative content for DTC/independent stores selling founder-driven products (e.g. handcrafted leather, artisan sauces, small-batch goods). Use whenever the user mentions founder story, brand story, about page, origin story, artisan brand, handcrafted brand, "who we are" copy, brand voice, mission/vision for a product brand, landing page hero narrative, PDP brand block, or wants to differentiate through authenticity and founder-led storytelling—even if they do not say "founder story" explicitly. Output structured narrative frameworks, placement guidance, and ready-to-use copy aligned with DTC best practices.
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。
Support accounting understanding from basic bookkeeping to professional practice and research.
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。
Power BI semantic modeling assistant for building optimized data models. Use when working with Power BI semantic models, creating measures, designing star schemas, configuring relationships, implementing RLS, or optimizing model performance. Triggers on queries about DAX calculations, table relationships, dimension/fact table design, naming conventions, model documentation, cardinality, cross-filter direction, calculation groups, and data model best practices. Always connects to the active model first using power-bi-modeling MCP tools to understand the data structure before providing guidance.
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 creating professional UI/UX designs in Penpot using MCP tools. Use this skill when: (1) Creating new UI/UX designs for web, mobile, or desktop applications, (2) Building design systems with components and tokens, (3) Designing dashboards, forms, navigation, or landing pages, (4) Applying accessibility standards and best practices, (5) Following platform guidelines (iOS, Android, Material Design), (6) Reviewing or improving existing Penpot designs for usability. Triggers: "design a UI", "create interface", "build layout", "design dashboard", "create form", "design landing page", "make it accessible", "design system", "component library".
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 JSON parsing best practices covering performance optimization (orjson/msgspec), handling large files (streaming/JSONL), security (injection prevention), and advanced querying (JSONPath/JMESPath).
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。