「product」の検索結果

Export Administration Regulations (EAR, 15 CFR Parts 730-774) compliance advisor — ECCN classification across all 10 CCL categories and 5 product groups (A-E), EAR99 determination, jurisdiction analysis (EAR vs ITAR order of review), license requirement analysis via Country Chart, all license exceptions (LVS, GBS, CIV, TMP, RPL, GOV, TSU, ENC, TSR, APP, BAG, AVS, ACE), end-user/end-use controls (Entity List, Denied Persons List, Unverified List, MEU List), deemed export rules, Foreign Direct Product Rule (FDPR), de minimis thresholds, 10 General Prohibitions, SNAP-R license applications, voluntary self-disclosure, civil/criminal penalties, Export Compliance Program (ECP) design, and EAR vs ITAR jurisdiction determination. Use for any dual-use export control, CCL classification, or BIS compliance question.

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。

Assess obligations under Regulation (EU) 2023/2854 for connected products, related services, statutory B2B data sharing, unfair data-contract terms, exceptional-need B2G requests, data-processing-service switching, international governmental access, interoperability, smart contracts, enforcement, and non-EU representatives. Use for Data Act scope analysis, gap assessments, product and service design, request handling, contract review, cloud exit planning, or cross-regulation mapping.

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。

EU Data Act (Regulation (EU) 2023/2854) skill for lawyers. Use when the user asks about Data Act classification, drafting, lookup, analysis, or audit. Triggers include "Data Act", "Regulation 2023/2854", "connected product", "related service", "data processing service", "DPS switching", "Article 3(2) pre-contract", "Article 25 contract", "trade-secret handbrake", "international government access", "Chapter VI cloud switching", "Article 50 timeline", "FAQ Q22a", "data holder", "exportable data", "functional equivalence", "Art. 4(10) competing product", and similar EU Data Act phrases. The skill produces lawyer-style Word output and cites verbatim from bundled regulation and FAQ source texts.

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。

Analyzes how multiple regulations interact for a specific product, service, or business model. Identifies where obligations overlap, reinforce, complement, duplicate, or conflict; builds a priority matrix; produces an integrated compliance timeline; and estimates the total compliance burden. Use when (1) scoping a new product or service against the full regulatory landscape before launch, (2) conducting M&A due diligence on a target's multi-regulation exposure, (3) building a strategic compliance roadmap where single-regulation analyses miss the interactions, (4) advising on complex situations where regulations touch the same conduct from different angles, or (5) estimating budget and resourcing for multi-regulation compliance. Primary coverage of EU digital regulation (GDPR, Data Act, AI Act, CRA, NIS2, DORA, DMA, DSA, ePrivacy) and national implementations; the framework extends to any jurisdiction where overlapping regulatory regimes apply to the same activity.

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。

U.S. customs and trade-law research assistant for HTS classification, CROSS ruling research, CIT/CAFC decision briefing, duty compilation (General + Special + Chapter 99 + AD/CVD + MPF/HMF), country of origin determination, FTA qualification, and end-to-end import compliance review. Triggers on product classification, tariff questions, customs rulings, trade remedy screening (Section 301/232/201), Partner Government Agency admissibility, and UFLPA forced-labor analysis. Produces attorney-reviewable draft work product with an enforced HTSUS authority hierarchy and explicit evidence ledger.

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。

Stage exploration before instruction on complex problems. The learner produces two attempted approaches before consolidation — which builds on those attempts, not from scratch. Use for genuinely hard problems where struggle produces deeper learning.

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 you want to pressure-test a potential new business, product, or side project against the serial-founder filter. Not "marketing ideas for a product" (that's marketing-skills:marketing-ideas) — this is "should this business exist + can you win it." Runs the idea through a structured framework (problem, audience, wedge, monetization, moat, portfolio fit, distribution, energy fit, opportunity cost), checks domain availability via /domain, optionally triggers /deep-research for market validation, and outputs a viability brief: build / sleep on it / pass. Archives every idea to ~/.config/makerskills/business-brainstorm/archive/ so past work is searchable. Triggers on "/business-brainstorm," "/brainstorm," "new business idea," "should I build X," "pressure test this idea," "validate this idea," "is X a good business," "what about a [type] for [audience]."

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 risk-matched whitebox or the approved production game for its target runtime. Turn GAME_DESIGN, and ART_DIRECTION when production begins, into a minimal BUILD_BRIEF and a runnable candidate that can be iterated with replayable evidence. Use for prototype the riskiest design question, implement the approved game design, or turn this design into a running game. 游戏构建执行。先按最大风险做白盒，或在正式生产时把批准后的 GAME_DESIGN 与 ART_DIRECTION 压缩成最小 BUILD_BRIEF，在目标运行环境中实现可运行候选并用可回放证据迭代。用于验证高风险设计问题、构建游戏原型或实现批准方案。

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 game concepts from a novel. From SOURCE_BIBLE and PRODUCT_BRIEF, compare meaningful alternatives on the dimensions still unlocked, then select a playable direction using hard vetoes and explicit trade-offs. Use for what game should this novel become, compare game concepts, choose a game direction for this book, decide whether this novel should become an interactive story. 小说游戏概念设计。根据 SOURCE_BIBLE 与 PRODUCT_BRIEF 比较未锁定维度上的有效替代方案，用硬否决和关键取舍选择可玩方向。用于判断小说适合做成什么游戏、该不该做成互动叙事、比较游戏方案等需求。

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。

Draft investment proposals for Chinese wealth management clients. Creates structured proposals with investment rationale, product recommendations, and risk disclosures. Adapted from the original investment-proposal skill for A-share products and Chinese regulatory requirements. Triggers on "A股投资建议书", "投资方案", "investment proposal China", "proposal for [client]", "investment recommendation A-share", or "build investment proposal".

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。

AI image generation for SEO assets: OG/social preview images, blog hero images, schema images, product photography, infographics. Powered by Gemini via nanobanana-mcp. Requires banana extension installed. Use when user says "generate image", "OG image", "social preview", "hero image", "blog image", "product photo", "infographic", "seo image", "create visual", "image-gen", "favicon", "schema image", "pinterest pin", "generate visual", "banner", or "thumbnail".

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。

Generates Custom Product Page metadata templates with screenshot strategies, keyword targeting, and audience-specific messaging for up to 35 page variants. Use when creating targeted App Store pages for different audiences, ad campaigns, or traffic sources.

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。

Business-development radar across your product family - find who's building, forking, integrating, and mentioning your products, ranked into a who-to-talk-to-this-week lead list.

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。

Amazon competitor monitoring and competitive intelligence for sellers. Track pricing changes, inventory levels, new product launches, review velocity, and advertising patterns for competitor ASINs. Set up monitoring alerts for price drops, stock-outs, and market changes. Works on 12 Amazon marketplaces. No API key required. Use when: (1) monitoring competitor pricing strategies, (2) tracking competitor inventory and stock patterns, (3) detecting new product launches in your category, (4) analyzing competitor review velocity and ratings, (5) identifying market opportunities from competitor gaps, (6) setting up competitive alerts and benchmarks.

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。

Amazon product listing image strategy and optimization. Comprehensive shot planning, infographic design, lifestyle photography, mobile optimization, and conversion-focused visual content. Use when the user asks about Amazon images, product photography, visual optimization, or listing conversion.

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 bundling strategy — virtual bundles, multi-pack pricing, cross-sell bundles, bundle listing optimization

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 compliance and safety — certifications, labeling requirements, restricted substances, 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。

Amazon Brand Analytics interpretation and strategic insights for Brand Registry owners. Decode Search Frequency Rank (SFR) data, analyze Market Basket patterns, interpret Item Comparison reports, and extract demographic insights to optimize product strategy and advertising spend. Works with Brand Analytics data from all Amazon marketplaces. Requires Brand Registry access. Use when: (1) analyzing Search Frequency Rank data for keyword opportunities, (2) interpreting Market Basket data for cross-sell and bundling, (3) understanding Item Comparison competitive positioning, (4) extracting customer demographic insights, (5) optimizing product portfolio based on customer behavior, (6) building data-driven advertising 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。

Amazon sales volume estimator for sellers and product researchers. Estimate monthly sales and revenue from BSR (Best Seller Rank), ASIN, or keyword. Three modes: (A) BSR Calculator — input BSR + marketplace + price + category to get instant sales estimate, (B) ASIN Lookup — input ASIN to auto-fetch data and estimate sales, (C) Keyword Market Analysis — input keyword to analyze total market size and competition. Works on 12 Amazon marketplaces. No API key required. Use when: (1) estimating how many units a product sells per month, (2) sizing a market or niche opportunity, (3) analyzing competitor sales performance, (4) comparing sales across price points, (5) identifying top sellers vs long-tail distribution.

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。

Applies the Bullseye Framework from Traction by Gabriel Weinberg and Justin Mares. Use when choosing growth channels, testing customer acquisition strategies, or deciding where to spend marketing effort. Covers all 19 traction channels with selection methodology, testing protocol, and phase-matched channel advice. Triggers include 'how do we get customers', 'which marketing channel should we use', 'we have a product but no users', 'our growth has stalled', 'should we do content marketing or paid ads', 'how do we test traction channels', 'what channels work at our stage'. NOT for product development (use Lean Startup), not for positioning/messaging (use Obviously Awesome), not for pricing (use Monetizing Innovation), not for enterprise sales methodology (use SPIN Selling).

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。

Applies the StoryBrand SB7 Framework from Building a StoryBrand by Donald Miller. Use when writing website copy, crafting brand messaging, creating marketing materials, building sales funnels, or designing email campaigns. The SB7 Framework positions the customer as the hero and the brand as the guide across 7 story elements. Triggers include 'how should we write our website', 'our messaging is confusing', 'customers don't understand what we do', 'how do I write a tagline', 'what should our homepage say', 'nobody reads our emails', 'how do I create a lead generator', 'our marketing isn't working but our product is good'. NOT for growth channel selection (use Traction), not for product positioning against competitors (use Obviously Awesome), not for pricing (use Monetizing Innovation).

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。

Full brand naming workflow for founders, agencies, and businesses. Use this skill whenever the user says "help me name this brand", "brand naming", "I need a name for", "name ideas for", "what should I call my brand/company/product", "naming a startup", "brand name suggestions", "help with naming", or shares a brand brief and asks for name options. Also triggers when the user shares existing name options and asks for feedback, evaluation, ranking, or scoring of those names. Auto-detects whether to run the full generation workflow or the evaluation workflow based on what the user provides. Always use this skill for any brand or product naming task — even if the user just casually mentions needing a name.

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 a packaging design brief — structure, visual direction, hierarchy, materials, and unboxing experience. Use when the user says "packaging design", "packaging brief", "product packaging", "packaging direction", "label design", "packaging identity", "unboxing experience", "packaging look and feel", "brief my packaging designer", "packaging for my product", "packaging strategy", "retail packaging", "e-commerce packaging", "what should my packaging look like", or is briefing a designer, agency, or manufacturer on packaging requirements.

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。

Pre-production story-and-character development for Higgsfield projects — the upstream layer that decides WHAT to prompt before any model runs. Use when the user wants to build a character, design a world, develop a story or premise, create a character sheet / character bible / story bible, lock a visual style or 'visual DNA', plan a multi-shot narrative with consistent characters, or says things like 'help me design a character', 'build the world', 'I need a backstory', 'make this character consistent across shots', 'develop my film/series concept', or 'I keep getting generic AI characters'. Routes the locked outputs into higgsfield-prompt + the right model. Adapted from Higgsfield's official character-design framework by @vavavinca.

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。