1.6万 件 ・ 関連度順
Frontend development guidelines for React/TypeScript applications. Modern patterns including Suspense, lazy loading, useSuspenseQuery, file organization with features directory, MUI v7 styling, TanStack Router, performance optimization, and TypeScript best practices. Use when creating components, pages, features, fetching data, styling, routing, or working with frontend code.
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。
Use when receiving code review feedback (especially if unclear or technically questionable), when completing tasks or major features requiring review before proceeding, or before making any completion/success claims. Covers three practices - receiving feedback with technical rigor over performative agreement, requesting reviews via code-reviewer subagent, and verification gates requiring evidence before any status claims. Essential for subagent-driven development, pull requests, and preventing false completion claims.
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。
Diagnosis loop for hard bugs and performance regressions. Use when the user says "diagnose"/"debug this", or reports something broken/throwing/failing/slow.
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。
Create beautiful, accessible user interfaces with shadcn/ui components (built on Radix UI + Tailwind), Tailwind CSS utility-first styling, and canvas-based visual designs. Use when building user interfaces, implementing design systems, creating responsive layouts, adding accessible components (dialogs, dropdowns, forms, tables), customizing themes and colors, implementing dark mode, generating visual designs and posters, or establishing consistent styling patterns across applications.
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。
Use when validating, benchmarking, or monitoring LLM application performance. Keywords: RAG evaluation, LLM-as-a-judge, CI/CD gating, trajectory scoring, test suites, prompt quality.
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。
Process and generate multimedia content using Google Gemini API. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understand images (captioning, object detection, OCR, visual Q&A, segmentation), process videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extract from documents (PDF tables, forms, charts, diagrams, multi-page), generate images (text-to-image, editing, composition, refinement). Use when working with audio/video files, analyzing images or screenshots, processing PDF documents, extracting structured data from media, creating images from text prompts, or implementing multimodal AI features. Supports multiple models (Gemini 2.5/2.0) with context windows up to 2M tokens.
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。
Prismatic API access patterns and GraphQL reference. Covers the two-tier access hierarchy (MCP tools → Prism CLI), CLI usage rules, GraphQL query patterns, pagination, authentication, and managing platform resources programmatically.
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。
This skill should be used when the user needs to analyze a Dell Boomi export, parse Boomi Component XML files, migrate from Boomi to Prismatic, convert Boomi processes to CNI flows, map Boomi shapes to Prismatic equivalents, or interpret Boomi connector settings, transform maps, and process properties. Relevant when the user says "analyze this Boomi export", "migrate from Boomi", "parse Boomi XML", "convert Boomi process to Prismatic", or "what does this Boomi shape map to".
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。
Core knowledge for migrating integrations from other platforms (Boomi, Cyclr) to Prismatic Code Native Integrations. Provides the standard integration schema, schema-to-spec mapping, confidence scoring, and migration-aware code generation patterns. Use when the user says "migrate", "convert from Boomi/Cyclr", "parse this export".
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。
Use when writing Swift code for Apple platforms - iOS, macOS, visionOS. Covers Swift 6 concurrency, actors, Sendable, async/await, SwiftUI, MVVM architecture, Metal GPU programming, RealityKit ECS, visionOS scenes, interpolation/animation, advanced collection types, property wrappers, Combine bridging, error handling, testing, and API design patterns.
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。
Author, review, or batch-produce SVG icon hover gestures and icon↔icon morphs (Hugeicons/Lucide/Phosphor). Use for animated icon, icon hover, per-icon gesture, icon morph, menu↔cross, stroke-dashoffset draw-on, pathLength, transform-box. Not for page transitions, Lottie, or general UI chrome motion.
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。
Debug LangChain and LangGraph agents by fetching execution traces from LangSmith Studio. Use when debugging agent behavior, investigating errors, analyzing tool calls, checking memory operations, or examining agent performance. Automatically fetches recent traces and analyzes execution patterns. Requires langsmith-fetch CLI installed.
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。
Optimize multi-agent systems with coordinated profiling, workload distribution, and cost-aware orchestration. Use when improving agent performance, throughput, or reliability.
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。
Systematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration.
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。
Guide for managing the Agent Registry - database-backed agent configuration system. Use when asked to "configure agents", "manage skills", "set tool permissions", "create context rules", or when working with agent assignments per platform/chat. Covers dashboard UI, API endpoints, CLI commands, and MCP tools.
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。
Expert quantitative analyst specializing in financial modeling, algorithmic trading, and risk analytics. Masters statistical methods, derivatives pricing, and high-frequency trading with focus on mathematical rigor, performance optimization, and profitable strategy development.
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。
Visual context analyzer for AI agents. Provides screenshots, accessibility scans, DOM snapshots, and element descriptions for web pages. Use when you need to see what a web page looks like, analyze accessibility issues, inspect DOM structure, or get detailed element information. Triggers on requests like "take a screenshot", "check accessibility", "what does this page look like", "analyze the UI", "inspect this element", or any visual/UI analysis task.
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。
Generates Claude Code plugin agent .md files: writes YAML frontmatter (name, model, color, tools, hooks, disallowedTools), crafts system prompts, and creates triggering example blocks with context and commentary. Validates agent structure against naming, length, and format constraints. Use when the user asks to create an agent, add an agent, write a subagent, configure agent frontmatter, design agent system prompts, set agent tools or colors, build an autonomous agent, or add agent hooks.
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。
Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.
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。
Expert IoT engineer specializing in connected device architectures, edge computing, and IoT platform development. Masters IoT protocols, device management, and data pipelines with focus on building scalable, secure, and reliable IoT solutions.
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。
Guides agents and users to create standards-compliant agent definitions using templates in markdown frontmatter format, ensuring context gathering, clarity, and proper metadata. Forces agents to ask clarifying questions when context is insufficient. Token-efficient documentation required. All content must be in English. Trigger: When creating a new agent definition, setting up project agents, or documenting agent workflows.
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。
Creates specialized AI agents with optimized system prompts using the official 4-phase SOP methodology from Desktop .claude-flow, combined with evidence-based prompting techniques and Claude Agent SDK implementation. Use this skill when creating production-ready agents for specific domains, workflows, or tasks requiring consistent high-quality performance with deeply embedded domain knowledge.
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。
Interactive element picker for web pages. Opens a browser with click-to-select UI overlay. Use when you need to let users visually select DOM elements, identify element selectors, or get detailed element information interactively. Triggers on "select an element", "pick element", "let me choose", "which element", or any interactive element selection task. Integrates with agent-eyes for visual context.
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。
Validate custom agent file format and structure
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。