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概要と使いどころ
Achieve aggressive v3 performance targets: 2.49x-7.47x Flash Attention speedup, 150x-12,500x search improvements, 50-75% memory reduction. Comprehensive benchmarking and optimization suite.
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。
Survey the codebase, pick ONE high-leverage deepening opportunity (filtering out anything already proposed), and publish it as a PRD-shaped GitHub issue via /to-prd-project. Designed to run unattended in the daily architecture-review workflow.
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, improve, or audit analytics tracking and measurement. Also use when the user mentions "set up tracking," "GA4," "Google Analytics," "conversion tracking," "event tracking," "UTM parameters," "tag manager," "GTM," "analytics implementation," or "tracking plan." For A/B test measurement, see ab-test-setup.
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 edit, review, or improve existing marketing copy. Also use when the user mentions 'edit this copy,' 'review my copy,' 'copy feedback,' 'proofread,' 'polish this,' 'make this better,' or 'copy sweep.' This skill provides a systematic approach to editing marketing copy through multiple focused passes.
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。
Reviews Swift/iOS code for adherence to modern Swift idioms, Apple platform best practices, architecture patterns, and code quality standards. Use when user mentions best practices, code review, clean code, refactoring, or wants to improve code quality.
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。
Guides you through comprehensive iOS/Swift app planning and analysis. Use for new apps (concept to architecture) or existing apps (audit current state, plan improvements, evaluate tech stack). Covers product planning, technical decisions, UI/UX design, and distribution strategy.
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。
Generates value-moment-first onboarding flows for iOS/macOS apps — the default architecture races a new user to the first felt experience of the app's promised outcome, branching on whether they can experience it right now or need to plan for later. The classic paged welcome-carousel tour is an explicit fallback for genuinely explain-first apps. Use when user wants to add onboarding, welcome screens, first-launch experience, or improve activation/trial conversion.
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。
Interface copy that works — voice/tone, the PACE framework, alert anatomy, naming features, empty states, error messages, and the small-word edits that measurably improve UX. Distilled from Apple's writing sessions (2017–2026). Use when writing or reviewing any user-facing text — labels, alerts, onboarding, notifications, empty states, paywalls — or naming a feature.
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。
SGC is a semi-supervised pipeline for gene clustering in gene co-expression networks. SGC consists of multiple novel steps that enable the computation of highly enriched modules in an unsupervised manner. But unlike all existing frameworks, it further incorporates a novel step that leverages Gene Ontology information in a semi-supervised clustering method that further improves the quality of the computed modules.
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 creation of effective visualizations is a fundamental component of data analysis. In biomedical research, new challenges are emerging to visualize multi-dimensional data in a 2D space, but current data visualization tools have limited capabilities. To address this problem, we leverage Gestalt principles to improve the design and interpretability of multi-dimensional data in 2D data visualizations, layering aesthetics to display multiple variables. The proposed visualization can be applied to
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 new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
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 running single-variable cold email experiments. Defines experiment types (list-only, copy-only, combined), confidence weighting, minimum sample sizes, and success criteria. Use when the user wants to improve a campaign, test a new list vs old one, or compare copy variants. Prevents the
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。
Adds Smartlead-compatible spintax to cold email sequences for deliverability. Use this skill whenever the user asks to add spintax, spin text, add variations, or improve deliverability of email copy — especially when they mention Smartlead, cold email sequences, or paste HTML email content. Also trigger when the user says "spintax", "spin", "variations", "deliverability spintax", or references adding randomized alternatives to email copy. Works with both plain text and HTML input.
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 you need to turn a product or service into a compelling, high-converting offer. Trigger on "offer", "why would someone buy", "improve conversions", "value proposition".
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。
Remove vague, corporate, or AI-sounding language and replace it with clear, specific, human wording. Trigger on "improve copy", "sounds generic", "too fluffy".
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 keyword rank tracking and performance analysis. Comprehensive ranking factor analysis, change diagnosis, improvement strategy development, and competitive position monitoring. Use when the user asks about keyword rankings, position tracking, ranking changes, or competitive analysis.
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 search ranking optimization and A9 algorithm mastery. Comprehensive SEO strategy, indexing optimization, keyword ranking improvement, and search visibility enhancement. Use when the user asks about Amazon SEO, A9 algorithm, search ranking, or product discoverability.
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。
Return rate reduction — root cause analysis, listing accuracy, packaging improvements, size guides
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。
Deep Amazon review analysis for competitive intelligence and product improvement. Extract sentiment patterns, recurring complaints, feature requests, and competitive insights from customer feedback. Turn reviews into actionable product development and marketing strategies. Use when the user asks about review analysis, customer feedback, product complaints, sentiment analysis, or what customers think about products.
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 real run evidence, validation failures, source drift, platform drift, and user feedback to plan and, only after explicit approval, apply structural upgrades to an existing skill. Use when the user asks to improve an existing skill from recent runs, recurring failures, outdated sources, excessive bloat, changed platform behavior, or validated workflow feedback. Do not use to create a brand-new skill or to execute the business workflow itself.
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 high-quality JUnit 5 tests with AssertJ assertions. Use when user says "add tests", "write tests", "improve test coverage", or when reviewing/creating test classes for Java 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。
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。
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。