$ skills --list
Explorar y descubrir skills de agentes IA
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Explorar y descubrir skills de agentes IA
Showing 43741-43760 of 44358 skills
优化程序员 Markdown 简历，包括改进技术描述、量化项目成果、突出技术亮点、优化技能展示。当用户说"优化简历"、"改进简历"、"重写简历"、"让简历更专业"、"提升简历质量"，或提供简历文件需要优化时使用。
UI design system toolkit for creating consistent, accessible, and scalable interfaces. Includes design token generation, component documentation, responsive design calculations, and developer handoff tools. Use for creating design systems, maintaining visual consistency, and facilitating design-dev collaboration.
Autonomous decision-making CLI for strategy development (project)
Create and manage long-running background processes with start/stop/status controls, logging, and monitoring. Use for batch processing jobs, data pipelines, continuous services, or any long-running tasks.
Manages content with Contentful headless CMS and Content Delivery API. Use when building content-driven applications with structured content models, CDN delivery, and enterprise content management.
Core Shopify Liquid templating best practices for performance, maintainability, and clean code
Use when building React UIs with shadcn/ui that need cohesive, distinctive styling beyond defaults - provides systematic approach to theme tokens, component variants, related component groups, animations, and design system coherence. Transforms uniform shadcn into memorable branded experiences.
This skill should be used when the user asks about "touch input", "BoardInput", "BoardContact", "piece detection", "glyph", "glyph recognition", "simulator", "Board hardware", "contact phases", "Piece Set", "touch system", "Board SDK", "multi-touch", "noise rejection", or discusses Board hardware integration and input handling.
Reusable Liquid snippet patterns with proper documentation and parameter handling
Build and deploy this Next.js admin dashboard application. Use when building, deploying, or preparing the project for production.
Competitive analysis framework for CollectiveGood positioning. Researches companies in AI validation,human-in-the-loop systems, clinical AI evaluation spaces. Produces comprehensive competitive assessmentscovering business model, technology, market positioning, and differentiation opportunities.USE WHEN user says "competitive analysis", "assess competitor", "compare to [company]","market positioning", or requests research on companies in CollectiveGood's space.
Use before committing staged changes when you need to verify all related documentation is current - systematically checks README, CLAUDE.md, CHANGELOG, API docs, package metadata, and cross-references rather than spot-checking only obvious files
Multi-agent development workflow system. Load when orchestrating development tasks, spawning subagents, or managing workflow phases.
When you need check documentation about Ruby classes, modules, and methods use this skill to get full details. Avoid check source code or use `ruby -e` for documentation unless absolutely necessary.
GitHub Actions workflow automation for intelligent CI/CD pipelines with adaptive optimization. Use for workflow creation, pipeline optimization, security scanning, failure analysis, and automated deployment strategies.
Build Vue 3 UI extensions for Directus with modern patterns, real-time data, and responsive design
LLM fine-tuning with LoRA, QLoRA, and instruction tuning for domain adaptation.
Multi-agent development workflow system for structured task execution. Use when working with tasks in .tasks/ directory, when user invokes /task, /explore, /research, /spec, /build, /review, or /refactor commands, or when Claude needs to understand the task orchestration system. Provides workflow state management, sub-agent coordination, and session persistence.
Processes images with Sharp, the high-performance Node.js library for resizing, converting, and optimizing images. Use when building image pipelines, generating thumbnails, or optimizing uploads server-side.
Research pipeline for topology-aware GNN representation learning on power grids using the PowerGraph benchmark. Use when (1) building physics-guided GNNs for power flow (PF), optimal power flow (OPF), or cascading failure prediction, (2) implementing self-supervised pretraining for power systems, (3) evaluating cascade explanation fidelity against ground-truth masks, or (4) conducting reproducible ML-for-power-systems research. Triggers include "PowerGraph", "power flow GNN", "OPF surrogate", "cascade prediction", "physics-guided GNN", "grid analytics ML", "power system representation learning".