Analyze labor productivity from site data. Compare planned vs actual, identify trends, benchmark against industry standards.
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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概要と使いどころ
Analyze labor productivity from site data. Compare planned vs actual, identify trends, benchmark against industry standards.
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 construction labor productivity using data analytics. Track worker performance, identify inefficiencies, predict resource needs, and optimize crew allocation for maximum efficiency.
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。
Designs pricing strategies for products and services. Takes product/service, costs, target market, competitors. Analyzes cost-plus, value-based, competitor-based, penetration, premium models. Researches competitor pricing. Generates pricing-strategy.md with recommended model, price points, tier structure, discount policies, annual vs monthly analysis, sensitivity to churn, expansion revenue modeling.
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。
Run a go-to-market war room for a launch, repositioning, price change, or new product. Convenes opposing expert and customer-persona viewpoints to debate the plan, surfaces the risks that kill launches, and returns a go/no-go call plus a phased rollout plan with owners, sequencing, and kill criteria. Use before any launch you can't easily walk back.
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。
Wire a System One model (Jev, or an open reproduction like Von) into a product feature — routing, guardrails, scoring, classification. Use when replacing an LLM call that returns a label rather than prose, when adding a typed decision to an agent loop, or when deciding between the hosted Jev API and a local open model. Covers question design, the eval-set-first workflow, threshold calibration, confidence gates, and the traps measured on real 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。
Define a product's motion design language -- duration and easing scales, choreography rules, and signature moves -- and export it as tokens plus ready-to-use Framer Motion variants and CSS. The difference between animations and a motion system: everything moves like it belongs to the same 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。
Writes conversion-focused landing page copy - headlines, subheads, value propositions, feature and benefit blocks, social proof, FAQs, and CTA button text - using PAS, AIDA, or StoryBrand. Use when the user wants words for a landing page, sales page, product or pricing page, waitlist page, homepage hero, or ad-to-page flow, including rewriting weak copy, generating headline or CTA variants for A/B tests, or turning a product description into page sections. Use landing-page-optimizer instead for auditing an existing page's performance, and a frontend skill for building the page itself.
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。
Turn a marketing brief or product offer into a finished short-form video ad built in HyperFrames — hook, script, shot-by-shot storyboard, scene-by-scene HTML composition, captions, and voiceover. Outputs platform cuts (vertical 9:16, square, 16:9). Use when you need a launch ad, product promo, social video, or paid-creative concept ready to render.
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。
Turn a website URL, product docs, or a founder's rambling description into a tight 60-90 second explainer video built in HyperFrames -- problem/solution narrative, animated product walkthrough scenes, captions, and voiceover, ready for the homepage hero, sales emails, and onboarding.
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 an AI coding agent is writing or refactoring production code and its known failure modes need to be held in check — over-engineering, silent scope creep, invented APIs, claiming work is done without checking, deleting tests to make them pass. Trigger when the user asks for careful, production-grade, or reviewed code, or when a previous agent run produced confident output that turned out wrong.
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, modify, debug, and cloud-validate VeADK Agents from an accepted product intent. Use for VeADK architecture, tools, workflows, memory, knowledge, executable AgentKit projects, local tests, and AgentKit build/deploy/invoke/log repair loops. Do not use for unrelated user requests, other Agent frameworks, standalone cloud administration, or production Runtime 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。
マーケティングコンテンツ制作スキル。X/Instagram投稿、Note/Medium記事、 バナー画像、動画スクリプト等を作成する。 「投稿作って」「バナー作成」「記事書いて」「コピー作成」等で発動。 product-context.mdを参照してブランド一貫性を保つ。
プロダクトローンチ、機能リリース、Go-to-Market 戦略を立案するスキル。 「ローンチ戦略を立てて」「リリース計画」「Product Hunt準備」等のリクエストで発動。 フェーズドローンチ、チャネル戦略、モメンタム構築をカバー。
マーケティング計画策定・プロダクトマーケティングコンテキスト作成スキル。 「マーケ計画」「ポジショニング」「ペルソナ作成」「競合分析」「コンテンツ戦略」等で発動。 product-marketing-context.mdを生成し、他のマーケティングスキルの土台を作る。
Use when evaluating, designing, or pressure-testing the business model of an AI agent product. Triggers on "agent business model", "agent economics", "agent canvas", "evaluate agent product", "agent pricing", "agent unit economics", "agentic business", "AI agent company", "agent cost structure".
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。
Get the first 50 real users through channels the user's ICP already uses. Use when the product shipped and nobody came, the user is "posting more" with no result, or is reaching for paid ads before 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。
Analytics de produto — PostHog, Mixpanel, eventos, funnels, cohorts, retencao, north star metric, OKRs e dashboards 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。
6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.
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。
Preparation guide for ISO 31700 privacy by design for consumer goods certification. Covers the 30 requirements across design, production, and disposal phases. Includes gap assessment methodology, remediation planning, and mapping to GDPR Article 25 data protection by design obligations for consumer-facing products and services.
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 a Seedance 2.0 brand, product, website, app, shop, or personal-project promo from verified assets and claims. Use when the user needs a truthful 4–15 second reel with a clear hook, product proof, controlled typography, camera, sound, CTA, and provenance-aware asset roles; not for inventing claims or imitating unavailable brand marks.
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。
Product analytics and growth expert. Use when designing event tracking, defining metrics, running A/B tests, or analyzing retention. Covers AARRR framework, funnel analysis, cohort analysis, and experimentation.
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。
Product interaction and UX expert. Use when reviewing UI/UX, conducting heuristic evaluations, designing user journeys, applying cognitive psychology principles, or ensuring WCAG 2.2 accessibility compliance.
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 needs product management workflows such as RICE prioritization, customer interview analysis, PRD templates, discovery frameworks, go-to-market strategy, feature prioritization, research synthesis, or requirements 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。
Route full software-development architecture work from product intent through design, implementation, testing, release, and operations. Use when the user asks for a complete development architecture, wants to know which Spellbook skills to combine, needs an execution path across PRD/spec/API/data/security/performance/release/SRE, or asks to turn an idea or repo into a production-ready engineering plan.
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。