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概要と使いどころ
Discover and validate product ideas, analyze markets, scope MVPs, and optimize app store presence for iOS/macOS apps. Use when user asks to discover, validate, assess, scope, or analyze product ideas, market opportunities, or when they mention "product agent", "app idea validation", "should I build this", "MVP", "market analysis", or "ASO".
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。
iPadOS-specific patterns including Stage Manager, multi-window, drag and drop, keyboard shortcuts, pointer interactions, and Apple Pencil support. Use when building iPad-optimized features.
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 optimize configurable system parameters against a measurable scalar objective, especially for model training, inference, quantitative strategies, reinforcement learning, scientific workflows, or other expensive black-box evaluations where reading the project can improve trial selection.
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。
The analysis and visualization of alternative splicing (AS) events from RNA sequencing data remains challenging. SpliceWiz is a user-friendly and performance-optimized R package for AS analysis, by processing alignment BAM files to quantify read counts across splice junctions, IRFinder-based intron retention quantitation, and supports novel splicing event identification. We introduce a novel visualization for AS using normalized coverage, thereby allowing visualization of differential AS across
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 creating tailored resumes for job applications - researches company/role, creates optimized templates, conducts branching experience discovery to surface undocumented skills, and generates professional multi-format resumes from user's resume library while maintaining factual integrity
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。
Provides guidance for writing and benchmarking optimized CUDA kernels for NVIDIA GPUs (H100, A100, T4) targeting HuggingFace diffusers and transformers libraries. Kernels must be kernel-builder/ABI3-compliant: no pybind11, no setup.py, TORCH_LIBRARY_EXPAND bindings only. Supports models like LTX-Video, Stable Diffusion, LLaMA, Mistral, and Qwen. Includes integration with HuggingFace Kernels Hub (get_kernel) for loading pre-compiled kernels. Includes benchmarking scripts to compare kernel performance against baseline implementations.
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。
Provides guidance for writing and benchmarking optimized Triton kernels for AMD GPUs (MI355X, R9700) on ROCm, targeting HuggingFace diffusers (LTX-Video, SD3, FLUX) and transformers. Core kernels: RMSNorm, RoPE 3D, GEGLU, AdaLN. Includes XCD swizzle, autotune, diffusers integration patterns, and LTX-Video pipeline injection.
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。
Amazon Brand Analytics interpretation and strategic insights for Brand Registry owners. Decode Search Frequency Rank (SFR) data, analyze Market Basket patterns, interpret Item Comparison reports, and extract demographic insights to optimize product strategy and advertising spend. Works with Brand Analytics data from all Amazon marketplaces. Requires Brand Registry access. Use when: (1) analyzing Search Frequency Rank data for keyword opportunities, (2) interpreting Market Basket data for cross-sell and bundling, (3) understanding Item Comparison competitive positioning, (4) extracting customer demographic insights, (5) optimizing product portfolio based on customer behavior, (6) building data-driven advertising 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。
Plan, build, and optimize Google Ads campaigns — Search, Shopping, Performance Max, Display, and YouTube — including keyword research, match types, bidding strategy, Quality Score, ad extensions, conversion tracking, and ROAS optimization. Use when the user says "Google Ads", "Google advertising", "Google campaign", "search ads", "Google Shopping", "Performance Max", "PMax", "Google Display", "YouTube ads", "keyword targeting", "Google Ads strategy", "Google Ads optimization", "Google Ads account", "Google Ads not working", "search campaign", "Quality Score", "bidding strategy", "Google conversion tracking", or wants to run or improve paid advertising on Google.
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。
Plan, build, and optimize Meta advertising campaigns on Facebook and Instagram — campaign structure, audience targeting (core, custom, lookalike), creative formats, pixel setup, retargeting strategy, budget scaling, and ROAS optimization. Use when the user says "Meta ads", "Facebook ads", "Instagram ads", "Facebook advertising", "Meta advertising", "Meta campaigns", "Facebook campaign", "Instagram campaign", "Meta ad strategy", "ROAS", "Meta pixel", "Facebook pixel", "lookalike audiences", "Meta retargeting", "scaling Meta ads", "Facebook ad account", "Meta ads manager", "Facebook ads not working", or wants to run or improve paid social advertising on Facebook or Instagram.
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 generate a cinematic still image on Higgsfield, asks about shot framing, camera angle, or composition for image prompts, needs a specific shot type (close-up, wide shot, cowboy shot, etc.), or is working with [img] reference-based image generation. Covers distance & size shots, camera angles, and camera movement keywords optimized for AI image models (Soul 2.0, Nano Banana, Seedream, GPT Image, Flux, etc.).
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。
审查和优化已有 Skill。用于检查技能质量、触发边界、冗余指令或重构技能说明；不用于执行该技能的业务任务。
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。
Prompt 优化助手。适用于用户想优化提示词、改进 AI 指令、为特定任务设计更好的 prompt，或需要选择合适提示框架时使用。会根据任务场景匹配合适框架，必要时先追问关键信息，再输出更清晰、更可执行的提示词版本。
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 设计顾问与审查工具。基于 12-Factor AgentOps 最佳实践，用于：(1) 探讨 Agent 架构设计方案；(2) 审查现有 Agent/Skill/工作流的设计，发现问题，给出改进建议。触发词：审查我的 agent、帮我分析这个 skill、agent 设计、agent 优化、帮我 review 这个工作流、这个 agent 有什么问题、怎么设计 agent、agent 架构咨询。
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。
Review affiliate campaign results and improve strategy. Triggers on: "review my results", "what went wrong", "how to improve conversions", "analyze my campaign", "affiliate retrospective", "why am I not converting", "improve my strategy", "what should I change", "campaign review", "optimize my approach", "learn from my results", "post-mortem on my campaign".
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。
Write SEO-optimized affiliate blog articles, product reviews, comparison posts, listicles, and how-to guides. Triggers on: "write a blog post about", "review of [product]", "best [category] article", "comparison blog", "affiliate blog", "SEO article", "write a review", "product roundup", "blog content for affiliate", "how to use [product] blog post", "listicle about [category]", "[product] vs [product] blog", "content for my affiliate site".
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 SEO-optimized pages at scale using programmatic/template-based approaches. Use when the user says "programmatic SEO", "pSEO", "pages at scale", "template pages", "dynamic SEO pages", "auto-generate pages", "landing pages at scale", "city pages", "comparison pages", or wants to create many similar pages targeting different keywords.
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。
Generate a full SEO-optimized blog post. Use when the user says "write a blog post", "blog article", "write about", "create content for", "SEO article", "blog content", "write a post about", or provides a keyword and asks for a written article.
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 an SEO content brief for writers. Use when the user says "content brief", "SEO brief", "writing brief", "brief for", "writer brief", "outline for SEO", or asks about creating a structured brief to hand to a writer for producing search-optimized content.
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 pricing pages, pricing models, and pricing strategy. Use when the user asks about pricing, pricing pages, how to price a product, tiered pricing, freemium vs. paid, price testing, pricing psychology, or pricing page design. Trigger phrases include "pricing", "pricing page", "how to price", "pricing strategy", "freemium", "tiered pricing", "per-seat pricing", "usage-based pricing", "pricing experiment", "price anchoring", "pricing psychology", "pricing 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。
Write Google Ads copy and build campaign structures. Use when the user asks to create Google Ads, write ad copy for search or display, set up PPC campaigns, optimize Quality Score, choose bidding strategies, or generate responsive search ads. Trigger phrases include "Google Ads", "PPC", "search ads", "display ads", "Performance Max", "ad copy", "headlines and descriptions", "keyword match types", "ad extensions", "Quality Score".
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。
Analyzes your Claude Code conversation history to identify patterns, common mistakes, and opportunities for workflow improvement. Use when user wants to understand usage patterns, optimize workflow, identify automation opportunities, or check if they're following best practices.
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。
Train and optimize AI agents using Microsoft's Agent Lightning framework with reinforcement learning. Use when setting up agent training, instrumenting agents with tracing, configuring LightningStore, implementing reward functions, or optimizing prompts with RL/APO algorithms.
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。
Minimizes test count while preserving coverage. Detects byte-identical pairs, parametrize-inflation, language-guarantee tests, AST-shape tests, stale migration nets. Approval gate before any change.
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。