5,538 件 ・ 関連度順
概要と使いどころ
Diagnose database latency with explain plans, index ownership, and query-shape review. Use when a query is slow, an index is missing, or scans and N+1 patterns appear.
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 Redis as cache and coordination infrastructure with TTL, eviction, and latency-aware key design. Use when implementing Redis caching, key invalidation, or Redis performance work.
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。
Apply PostgreSQL standards for migrations, indexing, transactions, and ORM boundaries. Use when editing entities, Prisma schema, migrations, RLS, or query-performance work for PostgreSQL.
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。
OWASP Top 10 audit checklists for Web Applications (2021), APIs (2023), and Mobile (2024). Use when performing any security review, PR review, or codebase audit touching web, mobile, or API 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。
Enforce Red-Team verification and adversarial protocol audit. Use only when verifying completion, performing self-scans, or checking protocol violations; do not activate for ordinary implementation, configuration, or unit-test requests.
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。
Apply motion design principles for mobile apps covering timing curves, transitions, gestures, and performance-conscious animations. Use when implementing screen transitions, gesture-driven interactions, shared-element animations, or optimizing animation frame rates on iOS, Android, or Flutter.
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。
Probe for hardcoded secrets, injection surfaces, unguarded routes, business logic flaws, and platform-specific weaknesses across backend (Node, Go, Java, Python, Rust), frontend (React, Angular, Vue), and mobile (iOS, Android, Flutter) codebases. Use when performing security audits, vulnerability scans, secrets detection, or penetration testing.
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。
Validates bounded cybersecurity exercise observations against approved scope, expected behavior, runtime controls, and redacted evidence. Use when performing safe offline validation or authorized runtime checks with explicit stop and status gates.
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。
Standardizes mobile UI audits, performance/scroll checks, RTL verification, and state-specific testing on iOS/Android.
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。
OWASP LLM Top 10 (2025) audit checklist for AI applications, agent tools, RAG pipelines, and prompt construction. Use when performing any security review touching LLM client code, prompt templates, agent tools, or vector stores.
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。
Build high-performance declarative UI with Jetpack Compose. Use when writing Composable functions, optimizing recomposition, hoisting state, or working with LazyColumn and side effects; defer deep-link and navigation routing to android-navigation.
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。
Optimization techniques including OnPush, @defer, and Image Optimization. Use when optimizing Angular rendering, deferring blocks, or improving Core Web Vitals.
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。
Performs quality control, citation validation, and fact-checking before human review. Use after research is complete to verify all sources and claims before production.
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; 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。
Use when anything in a Phoenix app is slow, times out, or uses too much memory, even if the cause looks obvious. Load…
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 anything in a Phoenix app is slow, times out, or uses too much memory, even if the cause looks obvious. Load it before analyzing or fixing: it runs measured Ecto, LiveView and OTP checks and ranks fixes.
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。
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。
Use when anything in a Phoenix app is slow, times out, or uses too much memory, even if the cause looks obvious. Load it before analyzing or fixing: it runs measured Ecto, LiveView and OTP checks and ranks fixes.
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。