183 件 ・ 関連度順
概要と使いどころ
Use when reviewing game code in C#, GDScript or C++ (Unity, Godot, Unreal, custom engines) - client vs server authority, RPC and packet validation, in-app purchases and economy, save and replay files, mod and script loading, secrets in client builds
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。
Help complete beginners set up their development environment. Detect Mac or other. Guide VPS purchase and SSH setup step by step.
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 production payment and billing systems. Use when implementing Stripe, Paddle, Adyen, subscriptions, tax, marketplaces, or mobile purchase flows.
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。
Fetch and analyze Amazon product reviews by ASIN, supporting 15 marketplaces (including US) with star rating filtering. Triggered when users mention Amazon reviews, US reviews, product reviews, buyer complaints, negative reviews, positive reviews, star ratings, review analysis, review sentiment, product improvement suggestions, Vine reviews, verified purchase reviews, competitor review research, Amazon reviews, US reviews, Amazon.com reviews, product feedback, negative review analysis, positive review analysis, star rating filter, review sentiment analysis, product improvement insights, Vine reviews, competitor reviews, customer feedback. Even if users do not explicitly say "reviews", this skill should be triggered whenever the task involves reading, filtering, or analyzing Amazon product customer reviews.
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 Nexscope data to reverse-lookup traffic keywords for any Amazon ASIN, including organic ranking, ad ranking, search volume, traffic share, organic/paid scores, ABA TOP3 click concentration, click conversion rate, year-over-year search volume changes, and weekly/monthly time windows. Trigger when the user mentions ASIN keyword analysis, ASIN reverse lookup, traffic keyword research, organic ranking query, ad ranking query, keyword position tracking, Nexscope keyword data, competitor keyword peeking, viewing which keywords drive traffic to a product, analyzing keyword performance for a specific ASIN, time windows by week/month/recent N days, ASIN reverse keyword lookup, traffic keywords, organic ranking, ad ranking, search volume, Nexscope keywords, competitor keyword reverse lookup, click concentration, click-to-purchase conversion, week-over-week search volume. Even if the user does not explicitly mention "Nexscope", if their need involves finding keywords associated with a specific Amazon product (ASIN), 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。
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。
Query 1688 product bestseller billboard data for sourcing discovery and wholesale product research. Trigger when the user mentions 1688 product rankings, 1688 bestseller lists, wholesale hot products, domestic sourcing rankings, dropshipping product selection, 1688 trending products, bulk purchase popular items, supplier product rankings, 1688 billboard, 1688 bestsellers, sourcing rankings, wholesale hot products, trending product rankings, supplier rankings, 1688 trends. Even if the user does not explicitly mention "1688 billboard", if their need involves discovering hot-selling wholesale products or sourcing opportunities on the 1688 platform, 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。
Drafts due diligence checklists for U.S. corporate transactions (M&A, asset purchases, investments, JVs, restructurings). Covers corporate structure, financials, tax, contracts, IP, litigation, employment, benefits, insurance, and environmental compliance. Surfaces change-of-control triggers, consent requirements, and red flags. Use when preparing for deal closing, board presentations, or investor disclosure.
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。
Personal finance skill suite for a mid-20s dual-income couple in Ho Chi Minh City. Covers budgeting, emergency fund building, investments, insurance, tax optimization, goal planning, and couple dynamics — all calibrated to Vietnam's financial ecosystem. Use when the user asks about budgeting, saving, investing, insurance, taxes, or financial goal planning — trigger phrases include "review our budget", "how should we invest", "do we have enough insurance", and "plan for a home purchase". Use even if the user only mentions one financial topic without asking for a full 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。
The household as an economic unit with income, expenses, savings, and debt. Covers the envelope method, fixed vs variable expenses, the 50-30-20 baseline, emergency reserves, the true cost of ownership, opportunity cost in household decisions, and the distinction between a budget and a spending plan. Use when building a household budget, diagnosing why a household is always over, planning a major purchase, or teaching financial literacy at the household level.
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。
Buy and sell NFTs through OpenSea on EVM chains and Solana. Fulfill listings, accept or create offers, cancel orders, make cross-chain purchases, and sweep listings. Requires wallet signing; for read-only queries use opensea-api instead.
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。
Builds revolving securitization models with replenishment criteria, early amortization triggers, and portfolio composition limits. Use when modeling revolving structures, analyzing credit card ABS, or evaluating asset purchase 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。
Constructs accretion/dilution analysis with pro forma financials, synergy phasing, and purchase price allocation. Use when modeling merger outcomes, calculating EPS accretion, or analyzing deal structures.
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。
Evaluates stapled secondary structures combining primary commitment with secondary purchase in coordinated transactions. Use when analyzing stapled deals, structuring combined primary/secondary, or evaluating staple economics.
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。
Evaluates insider purchase patterns with cluster buying identification, historical signal analysis, and conviction scoring. Use when analyzing insider buying, assessing management confidence signals, or tracking insider activity 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。
Build automated email flows that nurture, convert, and retain. Creates complete sequences for welcome, nurture, launch, re-engagement, and onboarding with subject lines, body copy, timing, and A/B test plans. Use when someone needs email automation, a drip campaign, welcome series, launch emails, post-purchase emails, abandoned cart recovery, or says 'email sequence', 'drip campaign', 'welcome series', 'onboarding emails', 'nurture flow', 'automated emails', 'email marketing', 'retention emails', or 'lifecycle emails'. Even if they just say 'set up emails' or 'email strategy' without specifying 'sequence', this is likely the right skill. Includes deliverability rules and spam avoidance.
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 a conversion loop for a one-person company from reach to lead capture to purchase. Use when Codex needs to explain conversion concepts when needed, verify MVP prerequisites, ask one question at a time, present multiple conversion-path options, and write user-confirmed outputs into `opc-doc/`.
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 RFM (Recency, Frequency, Monetary) customer segmentation from transaction data. Use this skill when the user needs to segment customers by purchase behavior, identify high-value buyers, design retention campaigns, or prioritize marketing spend by customer value — even if they say 'who are our best customers', 'which customers are at risk of churning', or 'how do we target our 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。
"Solve the newsvendor problem for single-period ordering decisions under uncertain demand. Use this skill when the user needs to determine optimal order quantity for perishable goods, seasonal products, or one-time purchase decisions — even if they say 'how much to order for this season', 'perishable inventory', or 'single-period ordering'.".
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 the end-to-end customer journey across awareness, consideration, purchase, onboarding, adoption, retention, and advocacy stages. Identify touchpoints, pain points, emotions, and Moments of Truth per stage. Use when designing or improving customer experience. Do not use for internal employee process mapping — use process-mapper instead.
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 Ticketmaster events and seats with pricing. Returns Buy-now links to Ticketmaster checkout; it cannot complete a purchase 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。
Marketing analytics and data-driven optimization for B2B SaaS campaigns. Use this skill when analyzing marketing performance, optimizing conversion rates, running A/B tests, conducting customer research, creating marketing dashboards, building attribution models, analyzing funnel metrics, or storytelling with data. Also triggers on: marketing ops, performance analytics, CRO, A/B testing, data storytelling, customer insights, tracking plan, event taxonomy, UTM taxonomy, GA4 audit, consent mode, instrumentation contract, sample size calculation, minimum detectable effect, test duration, not enough traffic to A/B test, statistical significance, Bayesian vs frequentist, sample ratio mismatch, experiment feasibility, martech stack, marketing tech stack audit, tool consolidation, build vs buy, vendor evaluation, shadow IT tools, ESP/CRM/platform migration, switching cost, cutover plan, suppression list migration, data portability, customer interviews, survey design, sampling frame, non-response bias, how many people should I interview, thematic saturation, voice of customer, jobs-to-be-done, buyer persona research, is this finding real, data enrichment, which enrichment provider should we buy, waterfall enrichment, contact data quality, match rate, our list data is bad, email verification, catch-all domain, accept-all, bounce rate from bad data, B2B data decay, how often should we re-verify contacts, ZoomInfo vs Apollo vs Clearbit evaluation, cost per usable record, where did this list come from, GDPR Article 14 notice, purchased list compliance, suppression screening, TAM list building, demand planning, marketing plan, how many leads do we need, what pipeline target should marketing carry, funnel model, top-down vs bottom-up plan, plan of record, annual marketing planning, quarterly planning, pipeline coverage we have to create, sales cycle lag, our leads cannot close this quarter, carry-in pipeline, scenario planning, conservative moderate aggressive forecast, stretch target, reforecast, re-forecast triggers, assumption register, capacity ceiling, addressable audience ceiling, marginal cost per lead, blended CPL is wrong, we missed plan and nobody knows why, AI policy for the marketing team, AI governance, AI acceptable use policy, which AI tools are we allowed to use, can I paste customer data into ChatGPT, shadow AI, AI use register, human review of AI output, when can we stop reviewing every AI draft, can the agent send on its own, the AI made a mistake now what, pull back AI autonomy, AI evals, our AI vendor changed the model, AI output went out wrong, prompt injection, can our AI read prospect replies safely, lethal trifecta, the AI leaked internal notes, turn off auto-generated ad assets, auto-applied recommendations, AI literacy training, EU AI Act Article 4, duplicate records in the CRM, dedupe before import, which value wins in a merge, CRM cleanup.
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 a task needs the judgment of an Advertising Sales Agent — pricing an ad-inventory package against a client budget, building a media-kit pitch, protecting yield on scarce inventory while moving remnant, or forecasting close rate on a sales pipeline. Sell-side: this role sells a publisher's or station's own ad space/time to advertisers, the opposite side of the table from a buyer-side advertising-promotions-manager who purchases media on a client's behalf.
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。
Detects external payment processors and WebView payment flows used for digital goods and verifies StoreKit integration, enforcing Guideline 3.1.1's requirement to use Apple IAP for all digital content purchases.
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。