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概要と使いどころ
Expert patterns for Azure Functions development including isolated worker model, Durable Functions orchestration, cold start optimization, and production patterns. Covers .NET, Python, and Node.js ...
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 Azure Cosmos DB NoSQL services with Python/FastAPI following production-grade patterns. Use when implementing database client setup with dual auth (DefaultAzureCredential + emulator), service...
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。
Analyze market conditions, geographic opportunities, pricing, consumer behavior, and product validation across Google Maps, Facebook, Instagram, Booking.com, and TripAdvisor.
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。
Specialized skill for building production-ready serverless applications on AWS. Covers Lambda functions, API Gateway, DynamoDB, SQS/SNS event-driven patterns, SAM/CDK deployment, and cold start opt...
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 and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring—where even top agents achieve less than 50% on re...
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 production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.
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 production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations.
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 in building 3D experiences for the web - Three.js, React Three Fiber, Spline, WebGL, and interactive 3D scenes. Covers product configurators, 3D portfolios, immersive websites, and bringing ...
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 a diff-grounded, one-page technical changelog for a release — from the actual code changes between the last production tag and HEAD (the next, still-unreleased version). Asks for the next version number, since HEAD is not yet in package.json.
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。
Shape FriendlyBet Pundit content, bilingual product copy, community voice, share-card copy, social moments, video briefs, Hebrew/English wording, and group-chat friendly communication. Use when a task touches copy, Pundit tone, social videos, share text, community loops, or public-facing FriendlyBet voice.
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 FriendlyBet privacy, RLS security, auth, recovery codes, session storage, data minimization, public snapshots, share surfaces, legal/gambling wording, real-money risk, and compliance-sensitive product changes. Use when a task changes data access, user identity, public sharing, money-like language, security posture, or legal risk.
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 or design FriendlyBet user experience, visual direction, mobile-first flows, premium sports interface, Hebrew/English copy fit, RTL behavior, accessibility, interaction patterns, and product UI polish. Use when a task touches screens, flows, layout, visual hierarchy, onboarding, prediction UX, share UX, or design 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。
Act as FriendlyBet's CEO and primary front door for every FriendlyBet request through automatic company preflight. Own end-to-end routing, planning, execution coordination, department orchestration, decision-rights enforcement, quality gates, board-style reporting, and escalation only for strategic, legal, brand, cost, risk, or taste decisions. Use by default in FriendlyBet threads, with full department planning for broad, ambiguous, strategic, cross-functional, or outcome-driven requests such as SEO, new features, multi-sport expansion, product direction, release execution, company operations, or agent coordination.
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。
Execute production-readiness gates with applicability control, consolidate validation report, and issue final readiness verdict
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 backend spec production from completed IA shards through classify and write passes with mandatory ambiguity gates
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 phase validation across code-quality and production-readiness gates with mandatory reporting and verdicting
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。
Apply the confirmed design direction to all visual surfaces. This skill now bridges the pipeline's placeholder system with the `impeccable` skill's PRODUCT.md and DESIGN.md files. If `{{DESIGN_DIRECTION}}` still appears as a literal placeholder, run `/impeccable teach` to establish design context.
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 when the user wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI 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 direction interview methodology — SUPERSEDED. The `impeccable` skill's `/impeccable teach` command now handles design direction discovery with a more comprehensive, multi-round interview that writes PRODUCT.md and DESIGN.md. This file is kept for pipeline backward compatibility — all new design work should use `/impeccable teach` 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。
Decompose validated idea-brief.md into 4–8 per-feature PRDs with screens nested. Use after kta-idea-pipeline. Triggers — write PRD, decompose features, feature breakdown, screen list, MVP scope to PRD, post-idea-validation, per-feature PRD, product requirements document, generate PRDs.
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 distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, or applications. Generates creative, polished code that avoids generic AI aesthetics.
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 is for interface design — dashboards, admin panels, apps, tools, and interactive products. NOT for marketing design (landing pages, marketing sites, campaigns).
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。
Multi-phase dialectical stress-test for HIGH-STAKES decisions only (architecture choices, irreversible product calls, strategic bets). Heavy-cost skill — do NOT use for routine questions, brainstorming, or simple tradeoffs. User must explicitly invoke or describe a decision they call "high-stakes", "irreversible", or "needs stress-testing". Triggers: "stress test this decision", "dialectic on", "challenge this thesis", "should I really".
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。