693 件 ・ 関連度順
概要と使いどころ
Adapt designs to work across different screen sizes, devices, contexts, or platforms. Implements breakpoints, fluid layouts, and touch targets. Use when the user mentions responsive design, mobile layouts, breakpoints, viewport adaptation, or cross-device compatibility.
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Use when you need to address review or issue comments on an open GitHub Pull Request using the gh CLI.
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AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.
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This skill should be used when the user asks to "implement LLM-as-judge", "compare model outputs", "create evaluation rubrics", "mitigate evaluation bias", or mentions direct scoring, pairwise comparison, position bias, evaluation pipelines, or automated quality assessment.
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6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.
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Search 8,400+ AI and ML jobs across 489 companies, inspect listings and employers, match roles, and view salary and market stats via AI Dev Jobs MCP
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You are a frontend designer-engineer, not a layout generator.
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Advogado criminalista especializado em Maria da Penha, violencia domestica, feminicidio, direito penal brasileiro, medidas protetivas, inquerito policial e acao penal.
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Foundation model for image segmentation with zero-shot transfer. Use when you need to segment any object in images using points, boxes, or masks as prompts, or automatically generate all object masks in an image.
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Guardian Angel gives AI agents a moral conscience rooted in Thomistic virtue ethics. Rather than relying solely on rule lists, it cultivates stable virtuous dispositions— prudence, justice, fortitude, temperance—that guide every interaction. The foundation is caritas: willing the good of the person you serve. From this flow the cardinal virtues as practical habits of right action and sound judgment. v3.0 introduced virtue-based disposition as the primary evaluation layer, providing deeper coherence than checklists alone. The agent's character becomes the safeguard. v3.1 adds: Plugin enforcement layer with before_tool_call hooks, approval workflows for ambiguous cases, and protections for sensitive infrastructure actions.
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Answer a question from the structured wiki before searching the web — "query the wiki", "what do we know about", synthesis request, cross-project research. Returns cited synthesis with wikilinks and counter-arguments.
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Ingest raw sources into the structured wiki — "ingest", "add this to my wiki", new files in raw/, clippings, sources, ideas, nightly ingest. Produces pages with YAML frontmatter and a mandatory Counter-Arguments section.
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Perform a final quality pass fixing alignment, spacing, consistency, and micro-detail issues before shipping. Use when the work is functionally complete and needs finishing touches—not when the hierarchy, structure, tone, or technical foundation still need major changes.
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Core C# and .NET language fundamentals. Navigation skill covering coding standards, language patterns, async/await, dependency injection, configuration, and foundational runtime concepts. Entry point for developers building .NET applications. Keywords: csharp, dotnet, fundamentals, coding standards, async, patterns, dependency injection, configuration, basics
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Red team engagement planning is the foundational phase that defines scope, objectives, rules of engagement (ROE), threat model selection, and operational timelines before any offensive testing begins.
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This skill details how to conduct cloud security audits using Center for Internet Security benchmarks for AWS, Azure, and GCP. It covers interpreting CIS Foundations Benchmark controls, running automated assessments with tools like Prowler and ScoutSuite, remediating failed controls, and maintaining continuous compliance monitoring against CIS v5 for AWS, v4 for Azure, and v4 for GCP.
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Apple's approach to interface design and fluid, physical motion, translated for the web. Use when building or reviewing gesture-driven UI, spring animations, drag/swipe/sheet interactions, momentum and interruptible transitions, translucent materials and depth, typography (optical sizing, tracking, leading), reduced-motion, or the design foundations (feedback, spatial consistency, restraint) behind Apple-style interfaces.
日本語の概要は準備中です。原文の説明を表示しています。
Foundational impossibility result proving consensus cannot be guaranteed in asynchronous systems with even one faulty process
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Foundational distributed computing algorithms for consensus, coordination, and fault tolerance
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Guides the practical path from 'we have no design system' or 'we have a mess' to a real, functional design system. Component inventory, design token extraction, headless UI adoption (Radix, React Aria, Headless UI), migration order of operations, and the assessment-to-rollout pipeline. Activate on 'design system from scratch', 'bootstrap design system', 'no design system', 'design system migration', 'headless UI adoption', 'component audit', 'design token extraction', 'design system strategy'. NOT for building specific components once a system exists (use design-system-creator), not for generating token files/configs (use design-system-generator).
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Foundational concurrent computation model where actors communicate exclusively through asynchronous message passing
日本語の概要は準備中です。原文の説明を表示しています。