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Found 5,550 Skills
Design cross-border logistics strategies including direct mail, overseas warehousing, and bonded warehouse models for international e-commerce. Use this skill when the user needs to ship products internationally, choose a logistics model for cross-border sales, optimize shipping costs, or set up fulfillment in a foreign market — even if they say 'ship to Southeast Asia', 'overseas warehouse vs direct shipping', 'customs clearance', or 'reduce international shipping time'.
Analyze e-commerce performance using GA4 metrics, conversion funnel analysis, and key e-commerce KPIs. Use this skill when the user needs to evaluate online store performance, diagnose conversion drop-offs, set up e-commerce tracking, or create performance dashboards — even if they say 'why are sales down', 'optimize our online store', 'set up GA4 for e-commerce', or 'what metrics should we track'.
Optimize e-commerce search relevance across the full pipeline from query understanding to result presentation. Use this skill when the user needs to improve search quality, implement query processing features, or diagnose search relevance issues — even if they say 'search results are bad', 'improve product search', or 'search relevance optimization'.
昇腾（Ascend）推理生态开源代码仓库智能问答专家旨在为 vLLM、vLLM-Ascend、MindIE-LLM、MindIE-SD、MindIE-Motor、MindIE-Turbo 以及 msModelSlim (MindStudio-ModelSlim) 等仓库提供专家级且易于理解的解释。在处理昇腾（Ascend）推理生态相关项目的用户询问时，务必触发此技能（Skill），可解答使用方法、部署流程、支持模型、支持特性、系统架构、配置管理、调试、测试、故障排查、性能优化、定制开发、源码解析以及其他技术问题。支持中英文双语回复，并可借助 deepwiki MCP 工具检索仓库知识库，生成具备上下文感知且基于证据的回答。Ascend inference ecosystem open-source code repository intelligent question-and-answer (Q&A) expert. Provide expert-level yet comprehensible explanations for repositories such as vLLM, vLLM-Ascend, MindIE-LLM, MindIE-SD, MindIE-Motor, MindIE-Turbo, and msModelSlim (MindStudio-ModelSlim). Use this skill when addressing user inquiries related to these Ascend inference ecosystem projects, including topics such as usage, deployment process, supported models, supported features, system architecture, configuration management, debugging, testing, troubleshooting, performance optimization, custom development, source code analysis, and any other technical issues about these projects. Support responses in both Chinese and English. Use deepwiki MCP tools to query repository knowledge bases and generate context-aware, evidence-based responses.
Interact with AstroBox through the command-line interface. Use this skill whenever the user wants to control AstroBox, manage devices, browse providers, download resources, install files, or check connection status. If the task involves AstroBox operations, ALWAYS use abcli via npx instead of trying to manipulate AstroBox internals directly. Trigger on mentions of AstroBox, device connection, authkey, provider browsing, resource download, watchface/app installation, or anything related to managing the AstroBox desktop app.
Genesys Cloud CX platform help — enterprise CCaaS with AI-powered experience orchestration, omnichannel ACD routing (voice + digital), Architect IVR/flow builder, workforce management (WFM forecasting/scheduling/adherence), quality management (evaluations/scoring), predictive routing, agent assist, virtual agents, outbound dialer, Interaction Analytics, AppFoundry marketplace (450+ apps), REST Platform API with OAuth 2.0 and 15 regional endpoints, deep Salesforce integration (CX Cloud joint product + Service Cloud Voice BYOT), 4 tiers CX1 $75/CX2 $115/CX3 $155/CX4 $240 per user/mo + telephony minutes. Use when setting up Genesys Cloud routing or Architect flows, WFM forecasting not matching actual volume, quality management evaluations not triggering coaching, dropped calls or audio quality issues, comparing Genesys pricing tiers, integrating Genesys with Salesforce or ServiceNow, Genesys reporting hard to navigate, MFA management confusing, Genesys API integration, or evaluating enterprise CCaaS platforms. Do NOT use for building a general coaching program (use /sales-coaching) or comparing CCaaS platforms (use /sales-ccaas-selection).
Manages Medusa Cloud resources through the Cloud CLI (mcloud). Use when deploying, debugging deployments, managing environments, environment variables, or any Medusa Cloud operation. CRITICAL for mcloud commands, deployment failures, build logs, Cloud setup, and CI/CD workflows.
Design and operate data quality programs for financial data — golden source architecture, validation rules, data lineage, exception management, profiling, and governance. Use when building validation rules for pricing or client data pipelines, designing a data quality monitoring framework, establishing golden source designations across systems, implementing data lineage for BCBS 239 or MiFID II, investigating reconciliation breaks or billing errors traced to bad data, preparing for regulatory exams on data accuracy, building data quality scorecards, or defining data stewardship roles. Trigger on: data quality, golden source, data lineage, data validation, data profiling, exception management, data governance, BCBS 239, data completeness, data accuracy, validation rules, data anomaly, data stewardship, data quality scorecard.
Ingest sources into the Obsidian wiki vault. Reads a source, extracts entities and concepts, creates or updates wiki pages, cross-references, and logs the operation. Supports files, URLs, and batch mode. Triggers on: ingest, process this source, add this to the wiki, read and file this, batch ingest, ingest all of these, ingest this url.
Use whenever researching a technical question — a library, tool, API, error, version, or "what's the best way to X" — or whenever you're about to answer from memory. Forces multiple real searches over primary sources (official docs, source code, high-vote Stack Overflow, maintainer blogs) instead of one search plus training-data filler, and rejects SEO content-farm slop. Trigger on "research X", "look into", "what's the best library for", "how does X work", "is this still true", "find out".
Plan Amazon coupons that lift conversion without leaking margin. Decides between percentage and dollar-off coupons, sets the right discount depth, picks the goal (launch, conversion lift, review velocity, stock clearance), and checks the math against fees and margin. Use when a user asks about coupons, the green coupon badge, percentage vs dollar off, coupon discount depth, or whether a coupon is worth running. Trigger phrases: "coupon", "coupon strategy", "coupon badge", "percentage off coupon", "dollar off coupon". Works with zero tools. the user provides price, cost, and fees.
Optimizes GKE costs, rightsizes workloads, and configures Spot VMs, CUDs, cost allocation, and resource quotas. Use when optimizing GKE cluster or workload costs, configuring GKE cost allocation or quotas, rightsizing CPU/memory requests, or selecting Spot VMs and machine types. Don't use for general compute class provisioning or GPU Selection (use gke-compute-classes instead).