2,150 件 ・ 関連度順
概要と使いどころ
A distinctive GPU shader background rendered in dependency-free WebGL — a marketing-grade hero backdrop. One per view; scrim behind text. Renders a static frame under prefers-reduced-motion.
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。
A distinctive GPU shader background rendered in dependency-free WebGL — a marketing-grade hero backdrop. One per view; scrim behind text. Renders a static frame under prefers-reduced-motion.
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。
A distinctive GPU shader background rendered in dependency-free WebGL — a marketing-grade hero backdrop. One per view; scrim behind text. Renders a static frame under prefers-reduced-motion.
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。
A living GPU shader background rendered in dependency-free WebGL — a distinctive, marketing-grade hero backdrop. One per view; put a scrim behind text. Renders a static frame under prefers-reduced-motion.
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。
A distinctive GPU shader background rendered in dependency-free WebGL — a marketing-grade hero backdrop. One per view; scrim behind text. Renders a static frame under prefers-reduced-motion.
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。
A living GPU shader background rendered in dependency-free WebGL — a distinctive, marketing-grade hero backdrop. One per view; put a scrim behind text. Renders a static frame under prefers-reduced-motion.
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。
Clean up translation-ese and AI-writing tics in Korean prose so it reads like a person wrote it — content (facts, numbers, proper nouns, quotes) stays 100% unchanged, only style and rhythm are touched. Single-pass, done in this session. Triggers — AI 티 없애줘, 번역투 고쳐줘, 한글 자연스럽게 윤문해줘, sounds like a machine translation, remove AI tells from this Korean text, make this Korean read naturally. Not for: marketing copy generation (write it clean the first time — see rules/korean-writing-quality.md), English text, plain spell-check (see korean-spell-check), or book-length manuscripts.
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 sales collateral, pitch decks, one-pagers, objection handling docs, or demo scripts. Also use when the user mentions 'sales deck,' 'pitch deck,' 'one-pager,' 'leave-behind,' 'objection handling,' 'ROI calculator,' 'demo script,' 'talk track,' 'sales playbook,' 'proposal template,' or 'buyer persona card.' For competitor battle cards and comparison pages, see competitor-alternatives. For marketing website copy, see copywriting. For cold outreach emails, see cold-email.
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, improve, or increase conversions on any marketing page — including homepage, landing pages, pricing pages, feature pages, or blog posts. Also use when the user says "CRO," "conversion rate optimization," "this page isn't converting," "improve conversions," or "why isn't this page working." For signup/registration flows, see signup-flow-cro. For post-signup activation, see onboarding-cro. For forms outside of signup, see form-cro. For popups/modals, see popup-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。
Generates App Store release documentation including submission guide, assets, privacy compliance, and marketing strategy. Creates RELEASE_SPEC.md for app launch. Use when preparing for App Store submission.
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。
Turn drafted legal docs (privacy policy, terms) into hosted pages and set the App Store Connect Privacy Policy / Support / Marketing URLs via the ASC REST API. Use at Phase 6 / submission, after legal drafts exist. The App Privacy "nutrition label" stays manual (Apple exposes no API) — this prints the exact answers to click.
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 user-facing changelog from recent commits/PRs across watched repos - write it in-repo (Keep a Changelog format) or open a cross-repo changelog PR on a docs/marketing repo.
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。
Produces a copy-ready clause about a company adding people to one specific department in the last 6 months, plus the department-level headcount counts that drive the segment gate. Triggers on "they're hiring", "hiring surge", "growing their sales team", "scaling the team", "headcount growth", "who added SDRs", "companies that just built a marketing team". Outputs hiring_surge_line, a lowercase second-person clause that completes "Noticed <line>."
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。
Cialdini's seven principles of compliance (the classic six — reciprocation, commitment-consistency, social proof, liking, authority, scarcity — plus Unity, added 2016) and Pre-Suasion. Use when crafting ethical persuasion (marketing, sales, negotiation), defending against manipulation, or designing systems that need cooperation. Includes replication-crisis caveats and known factual corrections (Bickman parking-meter numbers, Hofling modern replication, Drive Carefully condition disambiguation, Genovese myth).
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。
Builds lead generation systems using Alex Hormozi's Core Four framework (warm outreach, content, cold outreach, paid ads), lead magnets, and Rule of 100. Use when designing customer acquisition, scaling advertising, choosing marketing channels for revenue stage, building referral programs, or fixing low lead flow. Covers lead magnets, LTGP:CAC math, More Better New scaling, and Lead Getters (referrals, employees, agencies, affiliates).
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。
Define a brand's target audience with deep personas, psychographics, and ICP (Ideal Customer Profile). Use when the user says "target audience", "ideal customer", "customer persona", "audience persona", "ICP", "who is our customer", "define our audience", "audience research", "buyer persona", "who should we be targeting", "audience profile", "customer profile", "who buys this", or needs to understand their audience more deeply before investing in brand or marketing work.
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 mentions GPT Image 2.0 or GPT Image 2.5, gpt-image-2, gpt-image-2.5, gpt_image_2_5, GPT-Image-2 prompts, the Flare / Sunburst variants, a transparent-background image, or wants to generate an image with GPT Image 2.0 or 2.5. Covers when to prefer GPT Image 2.5 over 2.0 (transparent background, xhigh/max quality, extra aspect ratios — from platform and OpenAI facts), the CLI-vs-MCP disagreement on gpt_image_2, the three-format prompt taxonomy (Format A structured JSON for UI mockups and layout-dense images; Format B dense cinematic prose for single-subject scenes; Format C auto-derive meta-prompt for theme-only concepts), per-format craft patterns, output conventions, the 6-item pre-delivery checklist, and cross-surface workflow context (companion static-ads-workflow.md for ad recreation; higgsfield-marketing-studio cross-surface-workflow.md §3 for ms_image / DTC Ads Higgsfield-native alternative).
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 high-converting landing page copy and structure. Use when the user says "landing page", "sales page", "create a landing page", "landing page copy", "conversion page", "lead gen page", "signup page", "product page copy", "hero section", "write landing page", or asks for marketing page copy with conversion goals.
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。
Research and enrich B2B leads using the Apollo.io API. Use when the user says "find leads", "prospect research", "company enrichment", "find decision makers", "B2B leads", "lead research", "enrich contacts", "find VP of marketing at", or asks about finding people at specific companies or in specific roles.
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。
Manages Ahrefs API usage in Python using `ahrefs-python` library. Use when working with SEO / marketing related tasks or with data including backlinks, keywords, domain ratings, organic traffic, site audits, rank tracking, and brand monitoring. Covers `ahrefs-python` usage including AhrefsClient / AsyncAhrefsClient, typed request/response models, error handling, and all API sections.
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 a demand generation strategy and multi-channel campaigns. Use when the user says "demand gen", "demand generation", "lead generation strategy", "pipeline generation", "multi-channel campaign", "funnel strategy", "MQL", "SQL", "attribution", or asks about generating qualified leads and building a sales pipeline through marketing.
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。
Send messages and interactive cards to Feishu (飞书) and Lark channels via webhooks or Bot API. Create rich-text announcements, marketing updates, and team notifications. Trigger phrases: "post to feishu", "feishu message", "lark message", "feishu webhook", "lark webhook", "send to feishu", "send to lark", "feishu bot", "lark bot", "飞书", "飞书机器人".
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 Glasser to retrieve live marketing data through one prepaid account when a task needs SERPs, keyword metrics, ad libraries, community posts, company data, or another external API and no suitable free source or existing integration is available. Prefer the user's own integrations; Glasser fills data gaps and every run has a disclosed cost.
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。