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Found 6,836 Skills
Orchestrator skill for enabling CMDB (Configuration Management Database) end-to-end in Service Cloud ITSM against a production or sandbox org. Use when the user asks to set up CMDB, enable Configuration Management Database, configure the ITSM CMDB, onboard CMDB from scratch, wants a guided walkthrough of CMDB enablement, or asks what CMDB setup steps are available. Triggers on: set up CMDB, enable CMDB, configure CMDB, CMDB onboarding, Configuration Management Database setup, ITSM CMDB walkthrough. DO NOT TRIGGER when: the user asks about a specific CMDB sub-step directly (e.g. only installing a bundle, only assigning permission sets), CMDB record CRUD (creating CIs, relationships), Discovery/Service Graph Connector configuration, or general ITSM queries without CMDB setup intent.
Deploy (install) the CMDB Foundation base content bundle in Service Cloud ITSM against a production or sandbox org, after the CMDB feature is enabled. Use when the user asks to install the CMDB bundle, deploy CMDB Foundation, set up the CMDB base content, install CMDB out-of-the-box content, or finish CMDB setup with the base bundle. Triggers on: install CMDB bundle, deploy CMDB Foundation, CMDB base content, CMDB content bundle, bundleInstallation, finish CMDB setup. DO NOT TRIGGER when: the user wants to enable the CMDB feature for the org (that is the CMDB feature-enable skill), assign CMDB permission sets to a user (that is the CMDB access-assign skill), install optional non-base add-on bundles, deploy general (non-CMDB) metadata or packages, or work with CMDB records directly.
Use when you need to create a brand new Lightning Web Component from a Figma design, a Product Requirements Document, or another design artifact — orchestrating the five-phase workflow (gather requirements → generate code → optimize → lint/format/compile → test) and stitching together the specialized skills for SLDS, LDS, base components, optimization, and testing. Use this skill whenever the user mentions building a new LWC from Figma, building an LWC from a PRD, generating an LWC from a design or screenshot, or migrating an Aura component as a fresh LWC build. DO NOT TRIGGER when refactoring an existing LWC (use experience-lwc-generate), for Aura → LWC in-place migration (out of scope for this skill), for standalone SLDS token or styling work (use design-systems-slds-apply), or for standalone data-layer work (use experience-lds-best-practices-apply or experience-lds-data-requirements-generate).
Use when the user asks for a BPMN diagram, swimlane diagram, business process map, or workflow diagram with roles/lanes and phases. Builds with the declarative layout engine using canonical mxgraph.bpmn stencils (events, gateways, typed tasks) in horizontal swimlanes (pool → lanes × phases), validates (BPMN semantic rules plus geometry), runs a render-based vision self-check. Default output is .drawio; PNG/SVG only on request.
Check whether an SDK version supports a RevenueCat feature, whether an SDK upgrade is required, why an SDK-gated feature is not working, or how much of a project's recent subscriber base is on incompatible SDK versions. Use for questions about RevenueCat SDK compatibility, feature gates, minimum SDK versions, SDK adoption, upgrade impact, and rollout risk.
Apply bulletproof-react conventions when writing, organizing, or reviewing React or TypeScript apps. Covers feature-based folder structure, API layers, state management categories, testing strategy, error handling, auth, and performance. Use whenever the user creates a new React feature, sets up project structure, asks "where does this go" or "how should I organize this", decides where state lives, writes data-fetching or auth code, or asks for a React architecture review. Triggers on "feature folder", "React project structure", "should I use Redux", "how to structure API calls".
Identify opportunities and risks from changes in prosperity, prices, orders, inventory, and profits across the upstream and downstream of the industrial chain, helping to determine which links are benefiting, under pressure, or about to transmit impacts. Suitable for industrial chain research, prosperity tracking, and chain-based stock selection.
Build and sharpen a project's domain model. Use when discussing codebase terminology, writing or editing a CONTEXT.md, or recording or editing an ADR.
Judge a change before it lands: a branch, a pull request, a diff against a base point, or uncommitted work. Says what was not inspected rather than calling it clean. Covers what was actually asked for, security and abuse paths, whether the tests prove what they claim, broken contracts and callers outside this repository, and stale docs. Every finding at file:line, and it never edits. Use when the user says "review this", "check this before I commit", "does this hold up", or hands over a branch before opening it. Not for explaining code, formatting-only passes, running the linter or tests, or responding to a review of your own work.
Atomic Skill for Brand Gene Style Extraction. Based on product images and user-provided brand gene parameters (main color, font, platform, region, language), extract a unified brand visual language (Brand DNA) and output structured brandGeneJson for consumption by downstream atomic skills. Keywords: brand gene extraction, brand gene extract, brand DNA, brand visual definition, brand tone extraction, brand style extraction, visual identity extraction. Called by the image layout layer (linkfox-aigc-imagegen-cloth / product image layout path) in Step 3; triggered when the user says "extract brand gene", "define brand style", "brand gene", or "brand visual".
AI Text Generation Tool: Uses large language models to generate text content based on prompts, supporting combined understanding of images/videos/text. Available models include GEM_3_FLASH (fast response) and GEM_3_1_PRO (high-quality complex analysis). Triggered when users mention phrases like "AI text generation", "AI writing", "text generation", "help me write a paragraph", "text generation", "generate text", "write with AI", "AI analyze image content", "image recognition", "video analysis".
通过卖大律检测产品是否存在 TRO（临时限制令）与知识产权（商标/专利/版权）侵权风险，输入产品主图（支持图片 URL 或 Base64 data URI），可补充参考图、参考文本、IP 关键词，返回总体风险等级、高风险侵权项与低风险 IP 清单（含 TRO 原告、立案日期、法院案号、案件数）、0-10 数值风险分及 AI 生成的法律评估报告。当用户提到 TRO 检测、TRO 风险、TRO 侵权、知识产权侵权检测、商标侵权、专利侵权、版权侵权、IP 风险检测、产品合规检测、卖大律、product TRO detection, IP infringement risk, trademark/patent/copyright infringement check 时触发此技能。即使用户未明确提及"卖大律"或"TRO"，只要用户提供产品图片并希望评估其在商标、专利、版权或 TRO 方面的侵权风险，也应触发此技能。