590 件 ・ 関連度順
概要と使いどころ
Map any industry's competitive landscape using company databases, academic research, news coverage, LinkedIn activity, and job market signals. Produces industry overviews with key players, market segments, growth indicators, and emerging disruptors.
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。
Monitor brand mentions, sentiment, and reputation across Twitter, Reddit, news, and social platforms through SandBase. Use when asked for brand monitoring, reputation tracking, social listening, PR coverage analysis, or competitive brand intelligence.
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 companies with employee reviews, product reviews, industry classification, and competitive landscape through Akta. Covers company enrichment, employee satisfaction signals, product feedback, industry mapping, and news monitoring.
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 competitor advertising strategies through Facebook Ad Library, Google SERP ads, and social media sponsored content. Covers creative analysis, messaging patterns, targeting signals, and campaign frequency for competitive marketing intelligence.
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。
Comprehensive domain analysis combining WHOIS ownership, DNS infrastructure, SSL security, SEO performance, tech stack, site structure, and backlink profile. One-stop domain intelligence for acquisition research, security assessment, and 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。
Research competitor pricing strategies by extracting pricing pages, comparing product listings on Google Shopping and Amazon, and analyzing market positioning. Produces pricing benchmarks, tier comparisons, and feature-per-price 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。
Kaggle-first end-to-end competition workflow for scored submissions. Use when Codex must run Kaggle or competitive ML workflows through scored submission, including code competitions, validation, metrics, policy-safe public notebook/discussion intel, tabular/text/image modeling, tuning, ensembling/stacking, proactive multi-notebook architectures, producer notebooks that train models and export private Kaggle artifact datasets, downstream consumer notebooks, Kaggle GPU offload, kagglehub access, hidden-test debugging, and public score retrieval.
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。
Conduct market research, competitive analysis, investor due diligence, and industry intelligence with source attribution and decision-oriented summaries. Use when the user wants market sizing, competitor comparisons, fund research, technology scans, or research that informs business 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。
Research competitor paid-ad presence, messaging, creative, formats, landing pages, keyword and auction signals, transparent ad libraries, and strategic gaps across supported platforms. Use for competitor ads, ad libraries, ad spy, competitive PPC analysis, competitor creative, Google Ads Transparency, Meta Ad Library, or paid-media competitor research.
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。
Kaggle-first end-to-end competition workflow for scored submissions. Use when Codex must run Kaggle or competitive ML workflows through scored submission, including code competitions, validation, metrics, policy-safe public notebook/discussion intel, tabular/text/image modeling, tuning, ensembling/stacking, proactive multi-notebook architectures, producer notebooks that train models and export private Kaggle artifact datasets, downstream consumer notebooks, Kaggle GPU offload, kagglehub access, hidden-test debugging, and public score retrieval.
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。
Assess competitor defensibility and define our own moat strategy during PRD v0.3 Commercial Model. Triggers on requests to analyze competitor moats, define our defensibility, assess switching costs, identify vulnerabilities, find wedge opportunities, or when user asks "what's our moat?", "how defensible are they?", "where can we compete?", "switching costs?", "defensibility", "who to target". Consumes Competitive Landscape (v0.2) CFD- entries. Outputs CFD- entries for competitor moats and BR- entries for targeting rules and our defensibility 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。
World-class game UI design expertise combining the clarity of Nintendo's UI philosophy, the immersive diegetic interfaces of Dead Space and Metroid Prime, and the competitive readability principles from esports titles. Game UI is the invisible bridge between player intent and game response. Great game UI serves the player without breaking immersion. It communicates critical information at a glance during intense action, guides new players without patronizing veterans, and adapts gracefully from 4K monitors to handheld screens and from keyboard to touch to controller. The best game UI designers understand that every pixel of screen space is sacred - borrowed from the game world itself. Use when "game ui, game interface, hud design, heads up display, game menu, inventory ui, health bar, stamina bar, game hud, minimap, crosshair, reticle, button prompt, controller ui, gamepad navigation, diegetic interface, in-world ui, quest tracker, damage numbers, cooldown indicator, radial menu, game tooltip, game-ui, hud, game-interface, game-menu, controller-ui, diegetic, game-design, accessibility, console, mobile-games" mentioned.
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。
Master the AI tools that transform customer support from cost center to competitive advantage. Automate routine queries, empower agents, and delight customers at scale. Use when "customer support, helpdesk, ticketing system, chatbot, knowledge base, support automation, CSAT, customer service, support, helpdesk, chatbot, knowledge-base, customer-service, automation" mentioned.
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。
Identify true SEO competitors and quantify the gap, powered by the DataForSEO Labs API. Returns the top 10 competing domains by SERP overlap, with shared and unique keywords, traffic estimates, and a Competitive Score (0-100) showing how dominant the target is in its category.
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 professional, client-ready PDF SEO report from a saved DataForSEO-powered audit. Produces a polished PDF with score gauges, prioritized action plan, keyword opportunity tables, and competitive landscape — ready to send to a client.
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。
Extract and analyze competitor advertising from public ad libraries (Facebook Ad Library, Google Ads Transparency Center, TikTok, LinkedIn). Identifies messaging patterns, creative formats, pain points targeted, and positioning gaps. Use for competitive intelligence, campaign planning, and creative inspiration.
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。
Conduct deep OSINT research on individuals. Build full digital footprint, psychoprofile (MBTI/Big Five), career history, social graph with confidence scores. Recursive self-evaluation until completeness threshold is met. Includes internal intelligence (Telegram history, email, vault contacts) before going external. Use when: "osint", "досье", "research person", "find everything about", "пробей", "разведка", "due diligence", "background check", "digital footprint", "найди всё про", "собери информацию", "кто это", "профиль человека". NOT for: company/product research without a named person, competitive analysis, market research, content generation, or general web scraping tasks.
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 competitive SEO content briefs with per-section word counts, competitor scoring, keyword density guidance, and page-type templates. Supports both new page briefs and improve-existing-page briefs. Use when user says "content brief", "write a brief", "content outline", "blog brief", "service page brief", "brief for", "writing brief", "content plan", or "outline for".
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。
Strategic SEO planning for new or existing websites. Industry-specific templates, competitive analysis, content strategy, and implementation roadmap. Use when user says "SEO plan", "SEO strategy", "SEO planning", "content strategy", "keyword strategy", "content calendar", "site architecture", or "SEO roadmap".
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。
Blog strategy development including topic cluster architecture with hub-and-spoke design, audience mapping, competitive landscape analysis, AI citation surface strategy across ChatGPT/Perplexity/AI Overviews, distribution channel planning (YouTube, Reddit, review platforms for GEO), content scoring targets, measurement framework, and content differentiation through original research and first-hand experience. Use when user says "blog strategy", "content strategy", "blog positioning", "what should I blog about", "blog topics", "content pillars", "blog ideation".
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 practitioner's toolkit for thinking and communicating as a designer in a business context — reading financials, mapping competitive landscapes, and defending design decisions in the language of value.
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 competitor comparison or alternative pages for SEO and sales enablement. Also use when the user mentions 'alternative page,' 'vs page,' 'competitor comparison,' 'comparison page,' '[Product] vs [Product],' '[Product] alternative,' 'competitive landing pages,' 'how do we compare to X,' 'battle card,' or 'competitor teardown.' Use this for any content that positions your product against competitors. Covers four formats: singular alternative, plural alternatives, you vs competitor, and competitor vs competitor. For sales-specific competitor docs, see sales-enablement.
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 detailed content briefs for blog posts with target keywords, content outlines, competitive analysis, recommended statistics, image and chart suggestions, word count targets, internal linking architecture, template recommendations (12 types), TL;DR drafts, citation capsule planning, information gain prompts, and multi-channel distribution plans. Briefs are optimized for Google rankings and AI citations (GEO/AEO). Use when user says "content brief", "blog brief", "write brief", "outline blog", "plan blog post", "blog outline", "content outline".
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。
Runs evidence-aware, multi-provider research with the Librarium v2 CLI. Use for deep research, competitive research, answer-engine visibility checks, or questions needing grounded multi-source coverage.
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。