「optimize」の検索結果

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.

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Orchestrate the polish team: coordinates performance-analyst, technical-artist, sound-designer, and qa-tester to optimize, polish, and harden a feature or area for release 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。

Set up GEPA prompt optimization for an ORC 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。

Full-funnel paid advertising operations for B2B SaaS. Use this skill for PPC strategy, Google Ads optimization, LinkedIn Ads, social media advertising, programmatic buying, creative strategy, attribution modeling, budget allocation, budget pacing and planned-vs-delivered reconciliation, audience overlap and campaign self-competition audits, suppression lists, ROAS improvement, media spend optimization, and the media no auction sells — newsletter and podcast sponsorships, community and industry-publication placements, paid review-site listings on G2 and Capterra, and pay-per-lead content syndication. It also covers buying on the AI answer surface — ads inside Google AI Overviews and AI Mode that existing Search, Shopping and Performance Max campaigns already serve into with no opt-out, no placement targeting and no segmented reporting, and ChatGPT Ads and Microsoft Copilot as separate opt-in platforms with their own plan-tier reach limits, no negative keywords, and a landing-page crawler gate. It also owns the conversion signal the bidding algorithms learn from — CRM pipeline stages (SQL, opportunity, closed-won) sent back to Google Ads, LinkedIn, Meta and Microsoft Ads through offline conversion import, enhanced conversions for leads, the Google Data Manager API and the LinkedIn Conversions API, with click-ID capture, stage values, dedupe, EEA consent signals and retractions. It also gates connected TV (CTV) and streaming video for B2B — whether a reach medium belongs in the plan, how a vendor ties a TV household to a target account (member data, IP-to-account graph or contextual), the server-side ad insertion (SSAI) fraud questions, Programmatic Guaranteed deals, and a holdout lift test because CTV has no click. It also runs person-led paid social — LinkedIn Thought Leader Ads and Meta partnership ads that put spend behind an employee's or creator's post — on a paid-usage term, an in-post disclosure check and an end-date register, because the platform approval carries no term. Also triggers on: CTV, connected TV, OTT, streaming TV ads, should we run CTV, LinkedIn CTV, B2B CTV, account-based CTV, SSAI fraud, thought leader ads, boost an employee's post, sponsor a creator's post, partnership ads, whitelisting, creator usage rights, PPC, Google Ads, LinkedIn Ads, social ads, programmatic, ad creative, attribution, media budget, paid campaigns, ROAS, CPA, ad spend, newsletter sponsorship, podcast sponsorship, community sponsorship, sponsor a newsletter, content syndication, pay-per-lead, cost per lead vendor, media kit, rate card, insertion order, direct buy, publisher partnership, make-good, G2 paid listing, Capterra ads, review site advertising, sponsorship ROI, budget pacing, we underspent our budget, are our campaigns competing with each other, audience overlap, self-competition, campaign cannibalization, suppression list, exclusion list, ad frequency across channels, how many ad accounts do we have, ads in AI Overviews, AI Mode ads, ChatGPT Ads, OpenAI Ads Manager, Copilot ads, conversational ads, should we advertise on ChatGPT, can we buy our way into the AI answer, our ads are showing in AI Overviews and we cannot report on it, context hints, OAI-AdsBot, our ad landing page fails review, robots.txt is blocking our ads, our paid leads are junk, Google Ads is optimizing for the wrong leads, offline conversion import, OCI, enhanced conversions for leads, send CRM stages back to Google Ads, upload SQLs to LinkedIn, LinkedIn Conversions API, LinkedIn CAPI, Meta conversion leads, CRM to ad platform, gclid, li_fat_id, msclkid, value-based bidding, optimize for pipeline not form fills, low match rate, conversion lag.

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Creates feature branches with optimized short naming, auto-incrementing, and commit type detection (feat/fix/refactor). Supports manual descriptions and auto-generation from uncommitted git changes. Use when user requests to create branch, start new branch, make branch, checkout new branch, switch branch, new task, start working on, begin work on feature, begin feature, create feature branch, run /create-branch command, or mentions "branch", "feature", "new feature", "feat", "fix", or "checkout".

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 an Obsidian knowledge base from a sitemap — bulk-fetch pages via Python, generate Obsidian-optimized MD notes with parallel agents

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Generate SEO-optimized competitor comparison and alternatives pages. Covers "X vs Y" layouts, "alternatives to X" pages, feature matrices, schema markup, and conversion optimization. Use when user says "comparison page", "vs page", "alternatives page", "competitor comparison", "X vs Y", "alternatives page", "versus page", "comparison matrix", or "feature comparison".

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Audit a site or page against Google's OFFICIAL AI optimization guidance — readiness for AI Overviews and AI Mode, grounded in Google's published ai-optimization-guide and ai-features docs (not third-party GEO theory). Use when user says "AI optimization", "AI Overviews", "AI mode", "AI search readiness", "optimize for AI", or "GEO audit".

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Optimize content for AI Overviews (formerly SGE), ChatGPT web search, Perplexity, and other AI-powered search experiences. GEO analysis enriched with Ahrefs Brand Radar AI visibility data when available. Includes brand mention signals, AI crawler accessibility, llms.txt compliance, passage-level citability scoring, and platform-specific optimization. Use when user says "AI Overviews", "SGE", "GEO", "AI search", "LLM optimization", "Perplexity", "AI citations", "ChatGPT search", "AI visibility", or "Brand Radar".

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。

基于域健康报告和沙盘Gap记录，识别断裂模式，生成具体的补全行动方案：新Skill提案/现有Skill修改建议/缺失触发链路描述。与 skill-evolution-planner-meta 的区别：后者基于历史日志做宏观演进规划；本Skill基于具体Gap证据做定向修复。触发词：「优化[域名]域」「修复[域名]域Gap」「[域名]域自优化」「根据健康报告生成修复方案」。通常由 skill-closure-verifier-meta 调用，也可独立触发。

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。

元级闭环验证编排器。读取五域形式化描述（DOMAIN-REGISTRY + NODE-IO-CONTRACTS），两阶段（Phase 1预想/Phase 2实际）执行沙盘验证，调用 skill-domain-health-check 检查传播完备性，调用 skill-domain-self-optimizer 生成修复方案，输出带证据链的全系统闭环验证报告。这是整个Skill体系自我验证的最高入口。触发词：「运行元验证」「闭环验证」「验证Skill体系传播完备性」「系统闭环检查」「全域验证」「元系统运行」。

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。

Implements concurrent Go patterns using goroutines and channels, designs and builds microservices with gRPC or REST, optimizes Go application performance with pprof, and enforces idiomatic Go with generics, interfaces, and robust error handling. Use when building Go applications requiring concurrent programming, microservices architecture, or high-performance systems. Invoke for goroutines, channels, Go generics, gRPC integration, CLI tools, benchmarks, or table-driven 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。

High-throughput inference on FriendliAI — optimized serving engine for low-latency, cost-efficient LLMs.

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 serverless inference on Fireworks AI — open models, fine-tuning, and function-calling optimized endpoints.

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。

Program language models instead of prompting them — DSPy signatures, modules, and optimizers that tune prompts automatically.

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。

Increase conversion rates — CRO audits, A/B testing, landing page optimization, and experimentation programs.

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 content for AI answer engines (AEO/GEO): citation-friendly structure, factual precision, and measuring AI visibility. Use when AI search drives discovery.

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 a CDN with optimized caching, SSL/TLS, security headers, and cache invalidation — auto-detects hosting provider and app type, generates CloudFront, Cloudflare, or Vercel config with per-content-type cache rules, edge functions, and compression. Use when deploying a static site, SPA, SSR app, or adding a CDN layer to an existing API.

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 human-sounding, SEO-optimized blog posts for skills-hub.ai. Use when: 'write a blog post', 'draft a post', 'update blog', 'blog about', 'write about'. Supports styles: tutorial, deep_dive, opinion, listicle, case_study.

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Comprehensive K-12 or higher-ed system analysis: predict student dropout risk with early warning indicators, optimize curriculum alignment and pacing, personalize learning paths for at-risk and diverse populations, and audit school operations for resource efficiency..

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Full nonprofit operational health analysis: validate impact measurement methodology and theory of change, optimize fundraising channels and campaign ROI, audit grant management for compliance and proposal quality, and assess donor retention with churn prediction and stewardship workflows..

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Full autonomous design pipeline — builds fast, then the safety net polishes it. Chains: design-setup → design-build → (design-audit ∥ design-optimize) → design-polish → design-animate. Ships production-grade interfaces end to end.

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Generate a production-grade Product Detail Page (PDP) optimized for the 2026 conversion benchmarks — 4-8% target vs 1.5-3% average. Triggers: "product page", "PDP", "product detail page", "Shopify product page", "ecommerce 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。

Generate a production-grade Vehicle Routing Problem (VRP) solver using Google OR-Tools — supports CVRP (capacity), VRPTW (time windows), VRPPD (pickup + delivery), multi-depot, multi-trip, heterogeneous fleet, driver hours-of-service (HOS) compliance.

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。