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概要と使いどころ
Find similar design-registration candidates from a product image using Nexscope. Use for image-based design patent candidate screening with region, jurisdiction, Locarno and legal-status filters. Returns evidence for review, never an infringement or freedom-to-operate 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。
Analyze Amazon traffic gaps between an owned product and competitors using Nexscope keyword, traffic, listing and review evidence. Use for missing keyword coverage, organic-versus-paid traffic structure, variant-aware rank comparisons and evidence-based listing priorities. Produces a local HTML report; does not execute advertising changes.
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。
Check product images against a database of policy-violating items using visual similarity matching. Triggered when users mention policy compliance check, product image compliance review, violation detection, prohibited product screening, image-based compliance audit, pre-listing risk screening, or product image risk check. Even if the user does not explicitly say "compliance," this skill should be triggered whenever the need involves comparing product images against a violation database.
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。
Detect and search for similar utility/invention patents based on product information. Trigger when users mention utility patent detection, patent infringement risk, patent similarity search, patent screening, invention patent search, patent risk assessment, TRO (Temporary Restraining Order) risk analysis, utility patent, invention patent detection, patent infringement risk, patent search, TRO risk, Ruiguan. Even if the user does not explicitly say "utility patent", trigger this skill whenever their need involves checking whether a product may infringe existing utility/invention patents before selling in a target market.
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。
Detect graphic trademarks in product images by comparing against registered trademark databases across 15 major trademark offices using YOLO-based object detection and visual similarity. Triggered when users mention graphic trademark detection, logo infringement check, trademark similarity analysis, image trademark risk assessment, product image trademark screening, or logo detection. Even if the user does not explicitly say "trademark detection," this skill should be triggered whenever the need involves comparing a product image against registered graphic trademarks or assessing trademark infringement 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。
Detect image copyright infringement risks by comparing against a database of registered copyrighted works with similarity scoring, TRO litigation history, and radar-based infringement assessment. Triggered when users mention copyright detection, image infringement check, copyright risk analysis, TRO risk, copyright similarity search, rights owner lookup, or copyright compliance verification. Even if the user does not explicitly say "copyright," this skill should be triggered whenever the need involves checking whether an image may infringe registered copyright works.
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。
Search and filter TikTok global e-commerce products based on FastMoss data, supporting keyword search, multi-dimensional filtering (category, shop type, commission rate, sales, creator count, etc.) and sorting. Trigger when users mention TikTok product selection, TikTok product search, TikTok product data, TikTok creator sales, TikTok commission rate, TikTok bestseller tracking, TikTok GMV analysis, TikTok product search, TikTok product research, TikTok creator sales, TikTok commission rate, TikTok GMV analysis, FastMoss. Even if the user does not explicitly mention "FastMoss", trigger this skill whenever their need involves searching product data or analyzing product performance on TikTok.
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。
Perform image-based product search on the 1688 platform. Use an image URL to find visually similar supplier products, returning title, price, minimum order quantity, monthly sales, repurchase rate, trade score, and seller identity. Triggered when users mention 1688 image search, 1688 visual search, find supplier by image, reverse image search 1688, 1688 product sourcing by image, or Alibaba 1688 image search. Even if the user does not explicitly mention "image search," this skill should be triggered whenever a user provides an image URL and wants to find matching or similar products on the 1688 wholesale platform.
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。
Nexscope Product Database multi-condition filtering. Filter Amazon products by category, price, sales volume, revenue, reviews, rating, weight, BSR rank, LQS, seller type, and more across 10 marketplaces. Trigger when users mention Amazon product selection, product database filtering, BSR rank filtering, category-based product discovery, high-rating low-competition products, FBA product search, Amazon product discovery, or similar terms. Even if the user does not explicitly mention "Nexscope" or "product database," trigger this skill whenever the request involves filtering Amazon products by multiple criteria or discovering potential products.
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。
Find Amazon same-niche competitors by ASIN, with multi-dimensional filtering by click conversion rate, composite conversion rate, click volume, sales volume, reviews, ratings, price, and gross margin to identify potential competitors. Triggered when users mention same-niche competitors, ASIN competitor mining, niche competitor analysis, similar product benchmarking, ASIN benchmarking, niche market competitor list, high-conversion competitor screening, Nexscope product mining, niche competitor by ASIN, ASIN competitor analysis, same niche products, similar products discovery, conversion rate comparison, potential competitor screening, Nexscope ASIN mining. Even if users do not explicitly mention "niche" or "same niche", this skill should be triggered whenever the task involves discovering competitor lists or screening potential competitors based on a specific ASIN within the same market segment.
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-dimensional Amazon product search and filtering based on Nexscope data, covering 14 marketplaces, with support for historical monthly snapshot lookback. Trigger when the user mentions Nexscope product search, Amazon product filtering, competitor research, category analysis, brand bestsellers, seller analysis, seasonal products, historical snapshot review, product search, monthly sales/revenue, ABA keyword product discovery, price range filtering, new product discovery, multi-condition combined filtering, product search, competitor research, category analysis, brand bestsellers, seller analysis, seasonal products, historical snapshot. Even if the user does not explicitly mention "Nexscope", if their need involves Amazon product search, filtering, comparison, or product exploration by category/brand/seller dimensions, this skill should also be triggered.
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 reverse product selection: filter Amazon niches and keywords by 30+ business dimensions (market size & growth, price tiers & share, competition density & top concentration, demographics such as age/gender/income, review highlights & pain points) from a metrics pool aggregated from historical business insight reports. Trigger when users mention reverse product selection, metrics filtering, niche reverse lookup, blue ocean niche discovery, low-competition niche, newcomer-friendly niche, brand-fragmented market, pain-point entry, feature reverse lookup, pricing tier opportunity, demographic-based selection, or similar terms. Even if the user does not explicitly say "reverse product selection," trigger this skill whenever the request involves filtering Amazon niches that match specific business criteria.
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。
Perform image-based visual product search on Amazon across 8 marketplaces. Use an image URL to find visually similar products, with optional Nexscope enrichment for sales data. Triggered when users mention Amazon image search, Amazon visual search, find similar products on Amazon, reverse image lookup Amazon, Amazon search by photo, or competitor image search. Even if the user does not explicitly mention "image search," this skill should be triggered whenever a user provides an image URL and wants to find visually matching or similar products on Amazon.
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。
Cloud-based AI swarm deployment and event-driven workflow automation with Flow Nexus platform
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。
Converting technical knowledge into durable learning documents and publishable articles. Use for diff-based teaching, decision records, onboarding, note/Zenn/Qiita/dev.to posts, article series, retrospectives, and cross-platform repurposing.
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。
Analyzing session replays, extracting persona-based behavioral patterns, and storytelling UX issues. Reads the 'why' from real user operation logs. Works with Field/Echo for persona validation.
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。
Optimizing FinOps and cloud cost: IaC-based estimation, right-sizing, RI/SP recommendations, anomaly detection, budget alerts, AI/GPU workload economics. Use to forecast or cut cloud spend.
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。
Casting personas: rapid generation from diverse inputs, registry-based persistence and lifecycle, data-driven evolution, inter-agent sync. Not for UI walkthroughs (Echo) or user research (Field).
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 tests for a completed phase based on UAT criteria and implementation
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。
Gather phase context through adaptive questioning before planning. Use --all to skip area selection and discuss all gray areas interactively. Use --auto to skip interactive questions (Claude picks recommended defaults). Use --chain for interactive discuss followed by automatic plan+execute. Use --power for bulk question generation into a file-based UI (answer at your own pace).
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 all plans in a phase with wave-based parallelization
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。
Map evidence-based connections between a wellbeing initiative and specific academic learning outcomes. Use when justifying wellbeing programmes, integrating SEL, or linking pastoral and academic 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。
Select evidence-based study strategies matched to material type, learning goal, and student habits. Use when advising students on revision techniques, homework, or independent study approaches.
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 an uninterrupted work cycle with choice-based activities structured within a realistic time block. Use when planning Montessori-style independent work periods or extended choice time.
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。