shopify-snippet-library
Reusable Liquid snippet patterns with proper documentation and parameter handling
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Reusable Liquid snippet patterns with proper documentation and parameter handling
**Use this in every interaction** for validating implementation plans and todos, brainstorming before coding, creating TodoWrite todos for checklists, and reviewing work for completeness, clarity, and alignment...
This skill should be used when working with browser-rendered artifacts (i.e. Bun, React/React Native) to proactively validate that development work on localhost is being built appropriately and to support debug...
Write TypeScript and JavaScript code following best practices and coding standards. Use when developing or refactoring TypeScript/JavaScript code.
This skill should be used when the user asks to "add MCP server", "integrate MCP", "configure MCP in plugin", "use .mcp.json", "set up Model Context Protocol", "connect external service", mentions "${CLAUDE_PLU...
Generate and edit images using Gemini API (Nano Banana Pro). Supports text-to-image, image editing, multi-turn refinement, Google Search grounding for factual accuracy, and composition from multiple reference i...
Coordinate Tutopanda CLI and MCP to generate, edit, inspect, and preview documentary videos (video-audio-music blueprint with FinalVideo export). Use when users ask for Tutopanda to build, edit, or review movie...
Medical PowerPoint presentation generation with clinical data visualization. Creates professional presentations from FHIR resources, lab results, and clinical data. Use when generating patient summaries, care p...
FHIR R4 resource generation and validation for healthcare interoperability. Converts medical data into FHIR-compliant JSON resources (Patient, Observation, MedicationRequest, Condition, etc.). Use when creating...
Medical document OCR processing for extracting structured clinical data from medical images (prescriptions, lab results, clinical notes). Uses Google Cloud Vision for text extraction and medical NLP for entity...
Demonstrates proper skill structure and frontmatter format for marketplace skills
Build context-efficient, reusable skills using graph-based workflow orchestration with Claude Code subagents. Combines PocketFlow-inspired graph abstraction with multi-model optimization (Haiku for exploration,...
Multi-agent data science framework using DS-STAR (Data Science - Structured Thought and Action) architecture. Automates data analysis through collaborative AI agents with multi-model support (Haiku, Sonnet, Opu...
Tests marketplace visibility configurations and catalog tiers (preview catalog only)
Design and configure embedded Superset dashboards for internal tools and customer apps with theming, RLS, SSO, and scalable UX.
Helps COOs, BPM Leads, and Transformation teams plan and sequence BPM initiatives using the wiki content as a baseline.
Design, organize, and operate Deepnote projects as the InsightPulseAI Data Lab workspace for exploration, jobs, and Superset-ready summary tables.
Create onboarding, training, documentation, and enablement flows for admins, data teams, and business users of the InsightPulse Superset Data Lab.
Use Superset-style APIs to manage workspaces, users, datasets, charts, and dashboards as code for the InsightPulseAI Data Lab platform.
Turns BPM content into learning paths, micro-lessons, and exercises for analysts, managers, and process owners.
Acts as a guide through the BPM wiki, summarizing pages, comparing roles, and pointing users to the right article for their question.
Design, deploy, upgrade, and operate the InsightPulseAI Superset-based BI platform on the user's infrastructure with secure, stable, scalable configs.
Provides CTO-level guidance for AI-first products, platforms, and org design. Makes pragmatic, execution-focused decisions optimized for product moat, safety, and shipping velocity.
Turns raw BPM notes, spreadsheets, and wikis into clear, friendly documentation for the OpEx Docs site (Knowledge Base, HR, Finance).
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库,同一仓库的多个技能可能共享相同数值;它反映仓库关注度,不代表单个技能的安装量或质量评分。