「product」の検索結果

Systematic testing methodology for exhaustive branch coverage, edge case identification, and production bug prevention. Use when PR review reveals incomplete test coverage, when tests pass but users report bugs, when code changes break existing features, when verifying all branches and edge cases before merge, when analyzing "it works on my machine" issues, when planning test strategy for new features, or when debugging flaky tests and race conditions.

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 reviewing PRs/diffs/branches/documents for .NET quality, correctness, performance, security, data access, messaging, and observability. Includes adversarial critical-thinking mode for skeptical/cynical review requests. Keywords: code review, review PR, review diff, critical review, cynical review, adversarial review, production readiness, low GC, AOT, security review.

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 Chinese PPT pages through a prompt-to-image-to-editable-PPT workflow. Use when the user wants 中文PPT图片提示词, PPT image prompts, 16:9中文PPT页面图片, 直接生成PPT图片, 根据提示词生成图片, 把图片/PDF/截图复刻成可编辑PPT, 转成可编辑PPTX, 按图片完全复刻PPT, or full production from topic/source material to generated page images and editable PowerPoint slides with editable text, cards, tables, lines, callouts and high-quality icon/image assets.

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。

Research and compare how competing products implement a similar feature at the UX and interaction level. Provides structured comparison tables and strategic differentiation recommendations.

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。

Finalize documentation changes for production readiness by discovering existing conventions, verifying code-doc alignment, reviewing format/terminology/tone consistency, verifying branch/worktree intent, and structuring clean commits with a post-publish branch/worktree cleanup decision. Counterpart of finalize-and-commit for documentation 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。

Finalize code changes for production readiness by removing duplicate logic, auditing hardcoded values, verifying branch/worktree intent, verifying build integrity, structuring clean commits with Conventional Commits format, and forcing a post-publish branch/worktree cleanup decision.

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 shares a Sentry URL, says "check Sentry", or wants to investigate production errors. Uses Sentry MCP tools for deep analysis.

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 designing product-led retention — habit formation, trigger-action-reward, network vs single-user loops. Triggers on 'why don't users come back', 'design a habit loop'.

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 designing production-LLM prompts — few-shot, chain-of-thought, system prompts, templates, self-verification — distinct from prompt-optimizer and refine-prompt.

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 shaping employee onboarding — time-to-productivity, role-by-role program, mentor pairing, 30/60/90 milestones. Triggers on 'design our onboarding', 'why are new hires ramping slow'.

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 shaping a fuzzy product ask into a refined backlog item — problem framing, user-story rewrite, AC tightening — even if the user just says 'help me write this ticket'.

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。

Before stating any specific fact about an LLM provider's product — models, pricing, limits, context windows, SDK/API — for OpenAI, Gemini, Claude & others, verify against official docs, not memory.

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 diagnosing where a SaaS or product funnel leaks — visitor → signup → activation → paid → retained — channel-agnostic, conversion-rate-driven.

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 during or right after an incident — frames severity, sets comms cadence, drafts the post-mortem skeleton — even when the user just says 'production is down' or 'wir haben einen Vorfall'.

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 working with Laravel queues in production — Horizon dashboard, worker supervision, job metrics, balancing strategies — even when the user just says 'my jobs are piling up'.

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 DESIGN.md + PRODUCT.md — captures visual decisions and interaction patterns so design tasks stay consistent across sessions without re-scanning past work.

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。

Combine independent work from two or more selected agents into one decision-ready research report, design, or proposal. Preserve useful complementary findings, develop stronger combined options, and present material alternatives only when they exist. Use when multiple perspectives should improve the product without forcing consensus or staging disagreement.

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。

Quando o usuário quer adicionar, corrigir ou otimizar schema markup e dados estruturados no seu site. Use também quando o usuário menciona "schema markup", "dados estruturados", "JSON-LD", "rich snippets", "schema.org", "FAQ schema", "product schema", "review schema" ou "breadcrumb schema". Para problemas de SEO mais amplos, consulte seo-audit.

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。

Kit de ferramentas completo para gerentes de produto, incluindo priorização RICE, análise de entrevistas com clientes, templates de PRD, frameworks de descoberta e estratégias de go-to-market. Use para priorização de features, síntese de pesquisa com usuários, documentação de requisitos e desenvolvimento de estratégia de produto.

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 asks to generate or edit images via the OpenAI Image API (for example: generate image, edit/inpaint/mask, background removal or replacement, transparent background, product shots, concept art, covers, or batch variants); run the bundled CLI (`scripts/image_gen.py`) and require `OPENAI_API_KEY` for live calls.

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。

Quando o usuário quer criar ou otimizar paywalls in-app, telas de upgrade, modais de upsell ou feature gates. Use também quando o usuário mencionar "paywall", "tela de upgrade", "modal de upgrade", "upsell", "feature gate", "converter free para paid", "conversão freemium", "tela de expiração de trial", "tela de limite atingido", "prompt de upgrade de plano" ou "preço in-app". Distinto de páginas de preço públicas (veja page-cro) — esta skill foca em momentos de upgrade in-product onde o usuário já experimentou valor.

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。

Mecanismo de busca de similaridade vetorial de alto desempenho para RAG e busca semântica. Use ao construir sistemas RAG em produção que exigem busca de vizinhos mais próximos rápida, busca híbrida com filtragem ou armazenamento vetorial escalável com desempenho impulsionado por Rust.

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。

Banco de dados vetorial gerenciado para aplicações de IA em produção. Totalmente gerenciado, com auto-scaling, busca híbrida (vetores densos + esparsos), filtragem de metadados e namespaces. Latência baixa (<100ms p95). Use para RAG em produção, sistemas de recomendação ou busca semântica em escala. Ideal para infraestrutura serverless e gerenciada.

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。

Todo produto será potencializado por IA. A questão é se você vai construir corretamente ou entregar uma demo que desmorona em produção. Esta skill cobre padrões de integração de LLM, arquitetura RAG, engenharia de prompt que escala, UX de IA em que usuários confiam, e otimização de custos que não quebra o orçamento. Use quando: keywords, file_patterns, code_patterns.

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。