2,583 件 ・ 関連度順
概要と使いどころ
When the user wants to analyze competitors' App Store strategy, find keyword gaps, or understand competitive positioning. Also use when the user mentions "competitor analysis", "competitive research", "keyword gap", "what are my competitors doing", or "compare my app to". For keyword-specific research, see keyword-research. For metadata writing, see metadata-optimization.
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。
When the user wants to set up, interpret, or improve their app analytics and tracking. Also use when the user mentions "analytics", "tracking", "metrics", "KPIs", "App Store Connect analytics", "install tracking", "funnel", "attribution", or "how is my app performing". For A/B testing, see ab-test-store-listing. For retention metrics, see retention-optimization.
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。
When the user wants to discover, evaluate, or prioritize App Store keywords. Also use when the user mentions "keyword research", "find keywords", "search volume", "keyword difficulty", "keyword ideas", or "what keywords should I target". For implementing keywords into metadata, see metadata-optimization. For auditing current keyword performance, see aso-audit.
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。
When the user wants to localize their App Store listing for international markets. Also use when the user mentions "localization", "translate my app", "international markets", "expand to new countries", "localize metadata", or "which countries should I target". For keyword research in specific markets, see keyword-research. For metadata writing, see metadata-optimization.
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。
Memory management, profiling, optimization techniques, and Instruments usage for high-performance iOS apps
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。
Analyze Swift and mixed-language compile hotspots using build timing summaries and Swift frontend diagnostics, then produce a recommend-first source-level optimization plan. Use when a developer reports slow compilation, type-checking warnings, expensive clean-build compile phases, long CompileSwiftSources tasks, warn-long-function-bodies output, or wants to speed up Swift type checking.
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 data races, convert callback-based code to async/await, implement actor isolation patterns, resolve Sendable conformance issues, and guide Swift 6 migration. Use when developers mention: (1) Swift Concurrency, async/await, actors, or tasks, (2) "use Swift Concurrency" or "modern concurrency patterns", (3) migrating to Swift 6, (4) data races or thread safety issues, (5) refactoring closures to async/await, (6) @MainActor, Sendable, or actor isolation, (7) concurrent code architecture or performance optimization, (8) concurrency-related linter warnings (SwiftLint or similar; e.g. async_without_await, Sendable/actor isolation/MainActor lint).
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 asks to "优化简历", "resume optimization", "简历诊断", "tailor resume to JD", "改简历", "resume review", "简历优化助手", or when the user mentions "校招", "社招", "ATS", "JD匹配", "Word批注", shares a .docx resume path alongside a job description, or wants to match their resume to a specific job posting. Also triggers on "resume expert", "HR feedback", "interview prep with resume".
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。
Patterns for scaling read-heavy Convex apps to millions of users. Use when optimizing bandwidth, reducing query costs, fixing slow queries, creating digest tables, replacing reactive subscriptions with one-shot fetches, adding compound indexes, debouncing writes, rate-controlling backfills, or running npx convex insights. Trigger when users mention "scale", "bandwidth", "performance", "optimize", "slow queries", "expensive queries", "digest table", "denormalize", or "thundering herd" in the context of Convex.
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。
Set up and run reinforcement learning with verifiable rewards (RLVR/GRPO) for math, code, or custom environments using the Tinker API. Use when the user wants to do RL training, GRPO, reward-based optimization, or train with verifiable rewards.
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。
Set up and run Direct Preference Optimization (DPO) training on preference datasets using the Tinker API. Use when the user wants to train with preference data, chosen/rejected pairs, or DPO.
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 comprehensive FiveM resource security, performance, and compatibility audits. Detects backdoors, RATs, SQL injection, event exploitation, NUI vulnerabilities, dupes, crash/DoS vectors, npm and build-chain supply chain attacks, and malware patterns across ESX, QBCore, QBox, ox_lib, and ND_Core frameworks, on both GTA V Legacy and Enhanced builds. Use whenever a FiveM/cfx resource is being reviewed — even if not explicitly asked — including: audit FiveM script, review FiveM security, optimize FiveM resource, check FiveM performance, FiveM code review, review Lua script security, audit ESX resource, audit QBCore resource, audit QBox resource, check for exploits, FiveM vulnerability scan, GTA V Enhanced migration check, resmon optimization, or asking whether a leaked, cracked, nulled or unknown-origin script is safe to run.
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。
Web browser game development principles. Framework selection, WebGPU, optimization, PWA.
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。
PC and console game development principles. Engine selection, platform features, optimization 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。
TypeScript and JavaScript expert with deep knowledge of type-level programming, performance optimization, monorepo management, migration strategies, and modern tooling. Use PROACTIVELY for any TypeScript/JavaScript issues including complex type gymnastics, build performance, debugging, and architectural decisions.
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。
Postgres performance optimization and best practices from Supabase. Use this skill when writing, reviewing, or optimizing Postgres queries, schema designs, or database configurations.
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 website and web application performance including loading speed, Core Web Vitals, bundle size, caching strategies, and runtime 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。
When the user wants to optimize signup, registration, account creation, or trial activation flows. Also use when the user mentions "signup conversions," "registration friction," "signup form optimization," "free trial signup," "reduce signup dropoff," or "account creation flow." For post-signup onboarding, see onboarding-cro. For lead capture forms (not account creation), see form-cro.
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。
Prisma ORM expert for schema design, migrations, query optimization, relations modeling, and database operations. Use PROACTIVELY for Prisma schema issues, migration problems, query performance, relation design, or database connection issues.
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 guide on prompt engineering patterns, best practices, and optimization techniques. Use when user wants to improve prompts, learn prompting strategies, or debug agent behavior.
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。
When the user wants help with paid advertising campaigns on Google Ads, Meta (Facebook/Instagram), LinkedIn, Twitter/X, or other ad platforms. Also use when the user mentions 'PPC,' 'paid media,' 'ad copy,' 'ad creative,' 'ROAS,' 'CPA,' 'ad campaign,' 'retargeting,' or 'audience targeting.' This skill covers campaign strategy, ad creation, audience targeting, and optimization.
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。
Performance profiling principles. Measurement, analysis, and optimization techniques.
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。
Autonomously deep-scan entire codebase line-by-line, understand architecture and patterns, then systematically transform it to production-grade, corporate-level professional quality with optimizations
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。
When the user wants to create, optimize, or analyze a referral program, affiliate program, or word-of-mouth strategy. Also use when the user mentions 'referral,' 'affiliate,' 'ambassador,' 'word of mouth,' 'viral loop,' 'refer a friend,' or 'partner program.' This skill covers program design, incentive structure, and growth optimization.
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。