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概要と使いどころ
[Design] Create or describe a UI design — quick (fast), immersive (good), or recreated/described from a screenshot or video, in a product-UI or marketing/creative lane. Dispatch via --mode={fast|good|describe|screenshot|video} (default fast) and --lane={product|marketing} (default product).
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 or refresh screenshot-led product hero images, localized interface captures, and image-led README sections for GitHub repositories. Use whenever a user asks to make a GitHub README show a GUI product visually, add software screenshots, design a README hero image, reproduce a screenshot-collage reference, or prepare repository-bound visual documentation. For GUI applications, default to the deterministic product-proof split hero with real software screenshots unless the user explicitly requests another visual direction.
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 a crouton app to Cloudflare Workers STAGING (auto-provisioning) — the DEFAULT deploy, staging only, never production. Handles the staging bootstrap (auto-creates D1+KV, syncs ids, migrates), wiring CI, routine staging deploys, and Pages→Workers migration. For production use the separate /deploy-production skill. Use when deploying any app in apps/.
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 a crouton app to Cloudflare Workers PRODUCTION (<app>.friendlyinter.net). A deliberate, human-initiated action — separate from the default staging /deploy skill. Use ONLY when explicitly asked to ship/release to production. Never run as part of routine work or an automated flow.
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 says /deployprod, deploy prod, deploy production, upload production static hosting, or asks to deploy the current app to its production Convex static-hosting target.
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。
Marc Andreessen-mode decision and productivity skill. A blunt, market-first operator that pressure-tests ideas, ventures, features, and career bets through Andreessen's actual frameworks — market dominates team and product; the only milestone that matters is product/market fit.
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 AI marketing videos for ads, promos, product launches, and brand content. Models: Veo, Seedance, Wan, FLUX for visuals, Kokoro for voiceover. Types: product demos, testimonials, explainers, social ads, brand videos. Use for: Facebook ads, YouTube ads, product launches, brand awarene...
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 professional AI product photography and commercial images. Models: FLUX, Imagen 3, Grok, Seedream for product shots, lifestyle images, mockups. Capabilities: studio lighting, lifestyle scenes, packaging, e-commerce photos. Use for: e-commerce, Amazon listings, Shopify, marketing, ...
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。
You are an AI product engineer who has shipped LLM features to millions of users. You've debugged hallucinations at 3am, optimized prompts to reduce costs by 80%, and built safety systems that caught thousands of harmful outputs. You know that demos are easy and production is hard.
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。
本番と同じ失敗を本番前に検出するためのテスト階層設計スキル。 DB方言差、実依存関係、永続化確認、timezone差、packaging整合性、 adversarial regressionをunit/integration/e2e/smoke/packagingに 適切に割り振り、PR CIで最低限の本番同等性を保証する。 Use when designing production-parity tests, closing test blind spots, building smoke suites for real dependencies, verifying persistence beyond UI success, or creating adversarial regression backlogs.
Domain knowledge for using PrintKK print-on-demand API tools effectively. PrintKK is a print-on-demand platform that lets sellers create custom products, manage designs, upload images, and fulfill orders via API. Use this skill whenever the user wants to interact with PrintKK — browsing products, creating designs, placing orders, managing images, or building integrations with the PrintKK API. Also trigger when the user mentions "PrintKK", "print on demand", "POD fulfillment", custom product design workflows, or wants to automate their PrintKK store operations.
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。
Knowledge base from the NASA Systems Modeling Handbook for Systems Engineering (NASA-HDBK-1009A Rev A, 2025). Use for model-based systems engineering (MBSE) wired into NASA's NPR 7123.1 SE processes: the three aspects of MBSE (language / methodology / framework), the NASA SE Engine and its two OOSEM-derived steps (Model Planning, Setting Up the Model), the Modeling Plan as a SEMP subset, the tool-agnostic NASA SE metamodel of elements and relationships across the four SysML pillars (structure / behavior / requirements / parametrics), worked SysML diagrams and tables for stakeholders, requirements, structure and V&V, generating SE work products (ConOps, MOE, MOP, TPM, V&V), the MBSE Grid framework, alternative modeling approaches (PBR, Scenario, System Specification, Verification), and the ConOps model-content template. Scope is bounded to four common technical processes (Stakeholder Expectation Definition, Technical Requirements Definition, Product Verification, Product Validation). Does NOT teach SysML itself, mandate a tool, define NPR 7123.1 processes, cover technical-management processes 10-17, or reproduce the OMG SysML specification.
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。
Knowledge base from the DoD Manufacturing Readiness Level (MRL) Deskbook (Version 2022, OSD ManTech / Joint Service–Industry MRL Working Group). Use for assessing and managing manufacturing maturity and producibility risk in defense acquisition: the 10-level MRL scale and its non-linear, target-not-grade nature; the five demonstration environments (laboratory → production-relevant → production-representative → pilot line → production line); the nine manufacturing-risk threads and sub-threads; how MRL targets map onto Adaptive Acquisition Framework milestones (MRL 4/6/7/8/9); conducting an MRL Assessment; building a Manufacturing Maturation Plan; putting MRL maturity into contract language (Section L/M, SOW, AS6500A, DIDs); tailoring criteria for S&T, single-system, ship, sustainment, and industry contexts; and screening operational-technology cybersecurity. Manufacturing-readiness focused — it measures producibility risk and frames mitigation; it is NOT a technology-readiness (TRL) guide, a full systems-engineering process model, a cost-estimating or schedule guide, or a deep cybersecurity audit method (see sibling packs for those).
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。
新しいソフトウェア/デジタルプロダクトのコンセプトを対話で固め、競合・類似プロダクトを並列調査し、軽量な仕様ドラフトを作るオーケストレーションスキル。/product-spec <一言のプロダクトアイデア> で明示的に呼び出されたときのみ使用する。
Optimize WooCommerce product pages, category pages, and site content for search engines. Covers keyword research, meta tags, product descriptions, schema markup, internal linking, and local SEO. Use when writing product titles/descriptions, conducting keyword research, auditing pages for SEO gaps, setting up internal linking, adding schema markup, or optimizing for local search visibility.
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。
Given the product offering and existing page inventory, create new core landing and resource pages (homepage refresh, features, solutions, pricing, comparison, resource hubs, about) that capture core product intent using the query-fanout pattern. Use this skill whenever the user asks to "spawn pages", "generate landing pages", "create marketing pages", "build a pricing page", "add a solutions page", "build out the site", "fill in missing pages", or wants new top-level marketing/product pages. Output is one new page per route in the project's native file format (component or markdown), matching the existing page style and framework idiom.
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。
Every product will be AI-powered. The question is whether you'll build it right or ship a demo that falls apart in production.
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 products that wrap AI APIs (OpenAI, Anthropic, etc. ) into focused tools people will pay for. Not just "ChatGPT but different" - products that solve specific problems with AI.
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 the user wants to create, generate, or produce video content using AI tools or programmatic frameworks. Also use when the user mentions 'video production,' 'AI video,' 'Remotion,' 'Hyperframes,' 'HeyGen,' 'Synthesia,' 'Veo,' 'Sora,' 'Runway,' 'Kling,' 'Seedance,' 'Hailuo,' 'MiniMax,' 'Pika,' 'Hunyuan,' 'Wan,' 'video generation,' 'AI avatar,' 'talking head video,' 'programmatic video,' 'video template,' 'explainer video,' 'product demo video,' 'video pipeline,' 'copy this edit,' 'match this video style,' 'reverse-engineer this video,' 'edit like this reference,' or 'make me a video.' Use this for video creation, generation, and production workflows. For video content strategy and what to post, see social. For paid video ad creative, see ad-creative.
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 or update the shared product-marketing context: product, audience, positioning, competitors, jobs-to-be-done, objections, customer language, proof and goals. Use before downstream execution when context is missing.
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。
Compatibility skill for product marketing context. Use when a user or upstream workflow invokes this name; route the task to `product-marketing` while preserving the requested scope and source-specific intent.
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 the user wants to create, generate, edit, or optimize images for marketing — blog heroes, social graphics, product mockups, profile banners, listing visuals, or brand assets. Also use when the user mentions 'AI image generation,' 'generate an image,' 'create a graphic,' 'product mockup,' 'hero image,' 'social media graphic,' 'banner image,' 'cover photo,' 'profile banner,' 'listing screenshot,' 'Flux,' 'Flux Kontext,' 'Midjourney,' 'DALL-E,' 'GPT Image,' 'ChatGPT Images,' 'Ideogram,' 'Gemini image,' 'Nano Banana,' 'Recraft,' 'Stable Diffusion,' 'Canva,' 'Figma,' 'image optimization,' 'compress images,' 'WebP,' or 'OG image.' Use this for general-purpose marketing image creation and optimization. For paid ad image creative and platform-specific ad specs, see ad-creative. For video production, see video.
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。
Produce product-led video ad concepts and variants while preserving approved product details, claims, and platform constraints.
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。
Every product will be AI-powered. The question is whether you'll build it right or ship a demo that falls apart in production. This skill covers LLM integration patterns, RAG architecture, 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。