5,498 件 ・ 関連度順
概要と使いどころ
Perform basic penetration testing and security assessments. Use reconnaissance, vulnerability discovery, and exploitation techniques. Use when validating security controls or assessing system security.
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。
Deploy, manage, and optimize vector databases for AI applications. Covers Qdrant, Weaviate, pgvector, and Pinecone — collection management, indexing strategies, backup, and performance tuning for production RAG and semantic search 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。
Administer MySQL/MariaDB databases. Configure replication and optimize performance. Use when managing MySQL deployments.
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。
Administer PostgreSQL databases. Configure replication, backups, and performance tuning. Use when managing PostgreSQL deployments.
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 and deploy serverless functions on AWS Lambda. Configure triggers, manage permissions, and optimize performance. Use when implementing serverless 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。
Implement feature flags for progressive feature rollout using LaunchDarkly, Unleash, or custom solutions. Control feature visibility, perform A/B testing, and enable trunk-based development. Use when implementing gradual rollouts, feature toggles, or experimentation platforms.
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。
Configure CircleCI workflows and orbs for continuous integration and deployment. Create config.yml pipelines, use orbs for reusable configurations, and optimize build performance. Use when working with CircleCI for CI/CD automation.
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 systematically with root-cause analysis before fixes. Use for bugs, test failures, unexpected behavior, performance issues, CI failures, or system investigation.
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。
5 expert personas debate proposed changes before implementation. Catches architectural, security, performance, and UX issues early. Use before major features or risky changes.
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。
Perform a full codebase review, categorize findings by severity, file GitHub issues, then fix each issue in an isolated git worktree and submit PRs. Use this skill when the user asks to audit the codebase, do a comprehensive code review, find and fix security/quality/reliability issues, or run a proactive health check across the entire repository.
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。
Perform a comprehensive code health check on a directory. Use when the user asks to analyze code quality, find issues, or get a health report.
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 code review for bugs, security, style, and 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。
Triage TestFlight crashes, beta feedback, and performance diagnostics using asc. Use when the user asks about TF crashes, TestFlight crash reports, beta tester feedback, app hangs, disk writes, launch diagnostics, or wants a crash summary for a build or app.
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。
Code and product quality gates for shipping with confidence. Runs code review, QA testing, performance checks, and security audits. Use when the user says 'review my code', 'is this ready to ship', 'check quality', 'run QA', 'test this', 'security check', 'pre-launch review', or wants a quality assessment before deploying.
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。
Run an independent code review using the OpenAI Codex CLI in headless mode. Gets a second opinion from a different model family (the current Codex models) on recent changes, a PR, a commit, or the whole app — covering bugs, regressions, security, data consistency, UX/state bugs, performance risks, and testing gaps. Saves a severity-prioritised report to .jez/reviews/. Triggers: 'codex review', 'review with codex', 'independent code review', 'what does codex think', 'get codex to review'.
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。
当代码涉及循环内查询、批量 ID 查询、IN 子句、BFS/递归遍历、嵌套 service 调用时触发。防止 N+1 查询、IN 子句过长、递归内存炸裂等性能陷阱。
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。
当代码涉及循环内查询、批量 ID 查询、IN 子句、BFS/递归遍历、嵌套 service 调用时触发。防止 N+1 查询、IN 子句过长、递归内存炸裂等性能陷阱。
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。
Lightweight WebGL/WebGPU game engine with entity-component architecture and visual editor integration. Use this skill when building browser-based games, interactive 3D applications, or performance-critical web experiences. Triggers on tasks involving PlayCanvas, entity-component systems, game engine development, WebGL games, 3D browser applications, editor-first workflows, or real-time 3D rendering. Alternative to Three.js with game-specific features and integrated development environment.
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。
Fast, lightweight 2D rendering engine for creating interactive graphics, particle effects, and canvas-based applications using WebGL/WebGPU. Use this skill when building 2D games, particle systems, interactive canvases, sprite animations, or UI overlays on 3D scenes. Triggers on tasks involving PixiJS, 2D rendering, sprite sheets, particle effects, filters, or high-performance canvas graphics. Alternative to Canvas2D with WebGL acceleration for rendering thousands of sprites at 60 FPS.
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。
Lightweight 3D effects for decorative elements and micro-interactions using Zdog, Vanta.js, and Vanilla-Tilt.js. Use this skill when adding pseudo-3D illustrations, animated backgrounds, parallax tilt effects, decorative 3D elements, or subtle depth effects without heavy frameworks. Triggers on tasks involving Zdog pseudo-3D, Vanta.js backgrounds, Vanilla-Tilt parallax, card tilt effects, hero section animations, or lightweight landing page visuals. Ideal for performance-focused designs.
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。
Meta-skill for combining Three.js, GSAP ScrollTrigger, React Three Fiber, Motion, and React Spring for complex 3D web experiences. Use when building applications that integrate multiple 3D and animation libraries, requiring architecture patterns, state management, and performance optimization across the stack. Triggers on tasks involving library integration, multi-library architectures, scroll-driven 3D experiences, physics-based 3D animations, or complex interactive 3D 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。
Run scoped or final cross-media consistency checks for mathematical-modeling artifacts, comparing canonical numbers, symbols, parameters, decisions, files, and paper claims without performing full-workspace audits for low-risk changes.
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。
Perform the final submission-level audit of mathematical-modeling workflow integrity, evidence quality, anti-fabrication, paper coherence, figures, references, and contest readiness after consistency and completeness audits pass.
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。
High-performance C JSON parsing, creation, and modification with yyjson. Use when working with yyjson documents, string copy-vs-borrow ownership, dangling c_str() bugs, yyjson_alc allocators, or writer output freeing.
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。