Design accessibility testing strategies. TRIGGERS - Use when user needs help with accessibility-testing related tasks.
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。
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Design accessibility testing strategies. TRIGGERS - Use when user needs help with accessibility-testing related tasks.
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 account-based marketing strategies with targeting. TRIGGERS - Use when user needs help with abm-strategy related tasks.
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 committing VCSDD pipeline artifacts to git. Provides conventional commit message format, phase tag patterns, and atomic staging strategies.
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 applying VCSDD to Rust projects. Provides Kani proof harness patterns, proptest strategies, cargo-fuzz integration, and cargo-mutants mutation testing 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。
PC and console game development principles. Engine selection, platform features, optimization strategies.
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。
Build modern full-stack web applications with Next.js (App Router, Server Components, RSC, PPR, SSR, SSG, ISR), Turborepo (monorepo management, task pipelines, remote caching, parallel execution), and RemixIcon (3100+ SVG icons in outlined/filled styles). Use when creating React applications, implementing server-side rendering, setting up monorepos with multiple packages, optimizing build performance and caching strategies, adding icon libraries, managing shared dependencies, or working with TypeScript full-stack projects.
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。
Production deployment principles and decision-making. Safe deployment workflows, rollback strategies, and verification. Teaches thinking, not scripts.
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。
Testing patterns and principles. Unit, integration, mocking strategies.
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。
Web application testing principles. E2E, Playwright, deep audit strategies.
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。
Deploy and manage cloud infrastructure on Cloudflare (Workers, R2, D1, KV, Pages, Durable Objects, Browser Rendering), Docker containers, and Google Cloud Platform (Compute Engine, GKE, Cloud Run, App Engine, Cloud Storage). Use when deploying serverless functions to the edge, configuring edge computing solutions, managing Docker containers and images, setting up CI/CD pipelines, optimizing cloud infrastructure costs, implementing global caching strategies, working with cloud databases, or building cloud-native 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。
Build robust backend systems with modern technologies (Node.js, Python, Go, Rust), frameworks (NestJS, FastAPI, Django), databases (PostgreSQL, MongoDB, Redis), APIs (REST, GraphQL, gRPC), authentication (OAuth 2.1, JWT), testing strategies, security best practices (OWASP Top 10), performance optimization, scalability patterns (microservices, caching, sharding), DevOps practices (Docker, Kubernetes, CI/CD), and monitoring. Use when designing APIs, implementing authentication, optimizing database queries, setting up CI/CD pipelines, handling security vulnerabilities, building microservices, or developing production-ready backend systems.
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。
Work with MongoDB (document database, BSON documents, aggregation pipelines, Atlas cloud) and PostgreSQL (relational database, SQL queries, psql CLI, pgAdmin). Use when designing database schemas, writing queries and aggregations, optimizing indexes for performance, performing database migrations, configuring replication and sharding, implementing backup and restore strategies, managing database users and permissions, analyzing query performance, or administering production databases.
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 context engineering for AI agent systems. Use when designing agent architectures, debugging context failures, optimizing token usage, implementing memory systems, building multi-agent coordination, evaluating agent performance, or developing LLM-powered pipelines. Covers context fundamentals, degradation patterns, optimization techniques (compaction, masking, caching), compression strategies, memory architectures, multi-agent patterns, LLM-as-Judge evaluation, tool design, and project development.
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 effective reasoning processes for AI agents and optimize decision-making strategies. Use when designing agent prompts, improving decision quality, implementing specialized reasoning modes, creating reasoning traces, or debugging agent mistakes. Covers prompting, chain-of-thought, reasoning depth, and decision 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。
Expert error coordinator specializing in distributed error handling, failure recovery, and system resilience. Masters error correlation, cascade prevention, and automated recovery strategies across multi-agent systems with focus on minimizing impact and learning from failures.
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。
Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them. Key insight: Memory isn't just storage - it's retrieval. A million stored facts mean nothing if you can't find the right one. Chunking, embedding, and retrieval strategies determine whether your agent remembers or forgets. The field is fragm
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 and evaluate programmatic SEO strategies for creating SEO-driven pages at scale using templates and structured data.
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 demand generation campaigns, optimizes paid ad spend across LinkedIn, Google, and Meta, develops SEO strategies, and structures partnership programs for Series A+ startups scaling internationally. Use when planning marketing strategy, growth marketing, advertising campaigns, PPC optimization, lead generation, pipeline generation, or startup marketing budgets. Covers multi-channel acquisition (Google Ads, LinkedIn Ads, Meta Ads), CAC analysis, MQL/SQL workflows, attribution modeling, technical SEO, and co-marketing partnerships for hybrid PLG/Sales-Led motions in EU/US/Canada markets.
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。
Provide proven marketing strategies and growth ideas for SaaS and software products, prioritized using a marketing feasibility scoring system.
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 the Co-opetition Value Net framework (Brandenburger and Nalebuff, 1996) to map cooperative and competitive dynamics in business relationships. Use this skill when the user needs to identify complementors, analyze the PARTS framework, or design strategies that simultaneously cooperate and compete with the same players.".
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 Smith and Lewis's paradox theory to identify and manage organizational tensions across performing, organizing, belonging, and learning dimensions. Use this skill when the user needs to diagnose persistent either/or tensions, design dynamic equilibrium strategies that embrace both poles, or when they ask 'why does solving this problem make it worse', 'how do we pursue exploration AND exploitation simultaneously', or 'why do our strategic tensions keep recurring despite resolution attempts'.".
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 platform economics to analyze network effects, solve chicken-and-egg problems, and design multi-sided platform pricing strategies. Use this skill when the user needs to evaluate a platform business model, diagnose why a platform is failing to scale, or choose a subsidy strategy for bootstrapping a two-sided market.".
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 the Elaboration Likelihood Model to design persuasion strategies by matching message type to audience elaboration level. Use this skill when the user needs to craft persuasive communications, choose between argument-based and cue-based messaging, predict attitude durability after a campaign, or when they ask 'why did the message fail to persuade', 'how to change resistant attitudes', or 'should we use data or endorsements'.".
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 and conduct mixed methods research using convergent, explanatory sequential, or exploratory sequential strategies with genuine integration of qualitative and quantitative strands. Use this skill when the user needs to choose a mixed methods design, integrate qualitative and quantitative data at design, methods, or interpretation levels, justify mixing on pragmatist grounds, or when they ask 'which mixed methods design should I use', 'how do I integrate qual and quant findings', or 'is running both qual and quant enough to be mixed methods'.".
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。