3,183 件 ・ 関連度順
概要と使いどころ
Unified team skill for performance optimization. Coordinator orchestrates pipeline, workers are team-worker agents. Supports single/fan-out/independent parallel modes. Triggers on "team perf-opt".
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 the user wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI tasks.
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 experimental results analysis workflow for ML/AI research papers. Connects experimental data to publication-ready Results sections with statistical validation, visualizations, and quality checks. Triggers on "analyze experimental results", "generate results section", "statistical analysis of experiments", "compare model performance", "create results visualization".
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。
Project health audit and health check — architecture, performance; Use when assessing overall project health…
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。
Find Ecto N+1 queries and missing preloads. Use only when N+1 is suspected; not for broad database performance.
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。
Project health audit and health check — architecture, performance, tests, dependencies, code quality. Use when assessing overall project health, before releases, or after refactors.
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。
Detect N+1 query anti-patterns specifically — Repo calls inside Enum/for loops, missing preloads on associations. Use when N+1 is explicitly suspected, NOT for unrelated Ecto questions or wider database performance.
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。
Project health audit and health check — architecture, performance, tests, dependencies, code quality. Use when assessing overall project health, before releases, or after refactors.
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。
Detect N+1 query anti-patterns specifically — Repo calls inside Enum/for loops, missing preloads on associations. Use when N+1 is explicitly suspected, NOT for unrelated Ecto questions or wider database performance.
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。
Diagnose and fix performance problems in Shiny for Python apps — slow startup, sluggish interactions, blocking operations, and apps that struggle beyond a handful of concurrent users. Use when a Shiny for Python app is slow, hangs, recomputes too much, times out, or must support more users; when the user asks to "speed up", "optimize", or "make faster" a Python Shiny app; or when preparing a prototyped app for real-world traffic.
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。
Diagnose and fix performance problems in Shiny for R apps — slow startup, sluggish interactions, long-running blocking operations, and apps that struggle beyond a handful of concurrent users. Use when a Shiny app is slow, hangs, recomputes too much, times out, or needs to support more users; when the user asks to "speed up", "optimize", or "make faster" an existing Shiny app; or when preparing a prototyped app for real-world traffic.
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。
Pre-launch verification across infrastructure, security, legal, payment, email, analytics, and performance. Day-1 monitoring, rollback plan, incident response skeleton, and post-launch week-1 checklist.
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。
Agent reputation scoring, performance tier system, trust calibration, and task affinity matching
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。
Load testing with k6/Artillery, response time thresholds, memory leak detection, N+1 query detection, and CI integration.
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。
React, Next.js, TypeScript frontend patterns - component design, state management, performance
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。
k6 script templates, load profiles, response time thresholds, SLO validation, and performance testing strategies.
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。
PR size-based review depth, performance review checklist, architecture conformance checks, and framework-specific review 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。
Content marketing strategy - content audit, editorial calendar, SEO optimization, content funnel (TOFU/MOFU/BOFU), performance metrics, developer content, social media planning
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。
Autonomous experiment loop: hypothesize > modify > test > evaluate > keep/discard > repeat. Run N experiments automatically with measurable metrics. Works for performance optimization, A/B testing, prompt engineering, and any measurable improvement 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。
Chrome DevTools MCP ile browser debugging. Console, network, performance, DOM analizi.
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。
ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.
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。
Framework for measuring and tracking agent response quality over time. Detects regressions before they reach production. Use when evaluating agent changes, auditing quality, or establishing performance baselines.
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。
Builds dashboards, reports, and data-driven interfaces requiring charts, graphs, or visual analytics. Provides systematic framework for selecting appropriate visualizations based on data characteristics and analytical purpose. Includes 24+ visualization types organized by purpose (trends, comparisons, distributions, relationships, flows, hierarchies, geospatial), accessibility patterns (WCAG 2.1 AA compliance), colorblind-safe palettes, and performance optimization strategies. Use when creating visualizations, choosing chart types, displaying data graphically, or designing data 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。
Builds AI chat interfaces and conversational UI with streaming responses, context management, and multi-modal support. Use when creating ChatGPT-style interfaces, AI assistants, code copilots, or conversational agents. Handles streaming text, token limits, regeneration, feedback loops, tool usage visualization, and AI-specific error patterns. Provides battle-tested components from leading AI products with accessibility and performance built in.
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。