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Found 1,732 Skills
Mobile and web push notification strategy — opt-in optimization, rich push, segmentation, timing, frequency capping, deep linking, A/B testing, and analytics. Covers strategy and implementation across Braze, OneSignal, Airship, Firebase/FCM, Customer.io, Klaviyo, Iterable, and MoEngage. Use when designing push notification strategy, improving push opt-in rates, building push campaigns, choosing a push provider, or optimizing push engagement. Do NOT use for in-app messages (use /sales-in-app-messaging), email marketing (use /sales-email-marketing), SMS/WhatsApp messaging (use /sales-braze or platform-specific skill), or cold outbound (use /sales-cadence). For Braze-specific help, use /sales-braze. For Customer.io-specific help, use /sales-customerio.
Used when applying the SCAMPER creative thinking framework to systematically generate innovative ideas for products, services, processes, or concepts. It is triggered by requests involving SCAMPER (奔驰法), creative ideation, innovative thinking, product improvement, service optimization, brainstorming, systematic innovation, or when users want to explore multiple creative perspectives for an existing object, service, or business model.
When the user wants help with Google Ads keyword research, keyword strategy, match types, search term analysis, keyword planning, keyword organization, or keyword audits. Triggers on 'keyword research', 'keyword strategy', 'match types', 'search terms', 'keyword planner', 'keyword audit', 'broad match', 'phrase match', 'exact match', 'keyword expansion', or 'keyword list'. For deep negative keyword optimization, wasted spend elimination, or cannibalization prevention see google-ads-negative-keywords. For building search campaigns see google-ads-search. For bid management on keywords see google-ads-bidding.
When the user wants to audit a Google Ads account for a lead generation business — reviewing CPL, lead volume, lead quality, form conversion rates, offline conversion imports, and pipeline-focused optimization. Triggers on 'lead gen audit', 'Google Ads audit lead generation', 'CPL audit', 'audit my lead gen account', 'B2B Google Ads audit', 'lead quality audit', 'cost per lead audit', 'lead gen account review', or 'review lead generation Google Ads'. For general account audits see google-ads-account-audit. For ecommerce audits see google-ads-audit-ecommerce.
Technical SEO expert specializing in website performance optimization, structured data, mobile optimization, and technical issue diagnosis. Applicable for scenarios such as website technical implementation, performance tuning, and search engine crawling optimization.
Use when the workflow feels over-engineered, has premature optimizations, unnecessary abstraction layers, or complexity beyond actual requirements.
Deep Performance Optimization Skill for Triton Operators on Ascend NPU, dedicated to achieving the Triton operator performance improvement required by users. Core technologies include but are not limited to Unified Buffer (UB) capacity planning, multi-Tokens parallel processing, MTE/Vector pipeline parallelism, mask optimization, etc. This Skill must be triggered when the user mentions the following: performance optimization of Vector-type Triton operators on Ascend NPU.
Generate Triton operator requirement documents suitable for Ascend NPU. Used when users need to design new Triton operators, write operator requirement documents, or perform operator performance optimization design.
Troubleshoot and optimize the performance of Ascend C operators. This skill is applicable when users develop, review or optimize Ascend C kernel operators, or triggered when users mention keywords such as Ascend C performance optimization, operator optimization, tiling, pipeline, data copy, memory optimization, NPU/Ascend.
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.
Use when app feels slow, memory grows, battery drains, or diagnosing ANY performance issue. Covers memory leaks, profiling, Instruments workflows, retain cycles, performance optimization.
Application performance profiling and bottleneck identification — Node.js profiling, Chrome DevTools, flame graphs, memory leak detection, CPU profiling, React rendering performance. Activate on "profiling", "performance bottleneck", "flame graph", "memory leak", "slow app", "CPU profiling", "heap snapshot", "React re-renders", "EXPLAIN ANALYZE", "event loop lag", "clinic.js", "Core Web Vitals". NOT for infrastructure monitoring or observability (use logging-observability), load testing (use a load-testing skill), or database schema optimization.