「competitor」の検索結果

Use when a task needs the judgment of a Driver/Sales Worker on a direct-store-delivery (DSD) route — negotiating a shelf-facing or planogram change with a store manager, resizing a standing order after a shelf or demand change, deciding whether to pull code-dated product before a stale credit hits, reconciling a route's revenue-per-stop against cost-per-stop, or deciding whether to fight for shelf space back from a competitor.

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Comprehensive SEO analysis for any website or business type. Orchestrates 52 sub-skills (52 active): full site audits, technical SEO (CWV/INP), schema, E-E-A-T content quality, images, sitemaps, GEO for AI Overviews, llms.txt generation, AI crawler audit, plus live GSC and Ahrefs MCP data. GSC: overview, drops, opportunities, brand-vs-nonbrand, cannibalization, compare, content-decay, index-issues, new-keywords. Ahrefs: overview, backlinks, keywords, competitors, content-gap, broken-links, new-links, anchor-analysis, dr-history, top-pages. Cross-MCP: serp, content-brief, brand-radar, site-audit-pro, report. Local: log-analysis, ai-content-check, internal-links, local, migration-check, obsidian-kb. AI Readability: llms-txt, robots-ai. Performance: lighthouse-audit, core-web-vitals, page-experience. Quality & AI Search: rich-results, ai-optimization, eeat-audit, helpful-content. Triggers on: "SEO", "audit", "schema", "Core Web Vitals", "sitemap", "E-E-A-T", "AI Overviews", "GEO", "technical SEO", "content quality", "structured data", "GSC", "Ahrefs", "backlinks", "keywords", "search console", "domain rating", "local SEO", "migration", "lighthouse", "pagespeed", "LCP", "INP", "CLS", "page experience", "interstitials", "mobile friendly", "rich results", "rich snippets", "schema eligibility", "AI optimization", "AI search readiness", "EEAT", "trust signals", "helpful content", "people-first", "content quality gate".

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Analyze SERP for a keyword using Ahrefs live data: ranking pages, DR scores, traffic estimates, and content angle analysis. Use when user says "SERP analysis", "who ranks for", "SERP breakdown", "competitors ranking for keyword", "serp overview", "what's ranking for", "show me the SERP for", or "SERP competition for".

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Feature discovery agent — mines project docs, memory, user feedback, and competitor gaps to surface the highest-leverage features to build next. Outputs a prioritized feature backlog.

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Analyzes App Store and Play Store listing optimization -- keyword research, title optimization, screenshot conversion analysis, A/B testing setup, review sentiment analysis, competitor gaps, and localization 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。

Competitive intelligence and market positioning analysis. Researches competitors, compares features, pricing, and tech stacks, then produces a prioritized gap analysis with actionable 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。

Use when deciding WHERE to point SEO effort, not how to write a page. Triggers: a new site or brand with no rankings and no authority ("cold start", "starting from zero", "nobody knows us"), deciding what to double down on, a page or cluster that ranks but earns nothing, hunting emerging or newly-coined keywords before competitors arrive, "should we build a cluster or one page", "what do we write next", "we get impressions but no clicks", "our traffic plateaued despite publishing", whether to chase a head term at all, or turning any of it into recurring automation. Also use when asked why an SEO effort stalled despite consistent output. NOT for writing an article, keyword expansion mechanics, or auditing a single tactic for penalty risk.

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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。

Analyze a site's backlink profile, anchors, toxic signals, competitors, gaps, and disavow candidates. Use only when links or referring domains are the requested focus.

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Live SEO data via DataForSEO MCP server: SERP analysis, keyword research (volume, difficulty, intent, trends), backlink profiles, on-page analysis, competitor and content analysis, business listings, AI visibility (LLM mention tracking), and domain analytics. Requires DataForSEO extension installed. Use when user says "dataforseo", "live SERP", "keyword volume", "backlink data", "AI visibility check", or "real search data".

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Establish durable brand and voice context for cross-skill consumption. Generates BRAND.md (audience, positioning, do/don't editorial rules, taboo phrases, competitor differentiation) and VOICE.md (existing persona JSON re-expressed as readable prose), both written to the project root. When present, the blog orchestrator auto-loads these files for write, rewrite, brief, outline, calendar, and strategy workflows. Pairs with blog-persona, which manages the structured persona JSON. Use when user says "blog brand", "create brand context", "brand voice doc", "BRAND.md", "VOICE.md", "establish editorial brand", "brand guidelines for blog".

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Extracts and analyzes competitors' ads from ad libraries (Facebook, LinkedIn, etc.) to understand what messaging, problems, and creative approaches are working. Helps inspire and improve your own ad campaigns.

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Use with DecisionsAI when a ticket or workflow needs internet research — social posts, articles, video subtitles, GitHub, RSS, or competitor scans. Routes through Agent Reach upstream tools; run agent-reach doctor first.

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Track AI visibility — measure whether a brand is mentioned and cited by AI assistants (Gemini, ChatGPT, Perplexity) for target prompts. Runs scans, tracks mention/citation rates over time, detects trends, and identifies opportunities. Uses Gemini API free tier (with grounding) as primary method, web search as fallback. Use when a user wants to: check if AI models mention their brand, track AI citation changes over time, measure AEO content effectiveness, monitor competitor AI visibility, or audit their brand's presence in AI-generated answers. Pairs with aeo-prompt-research-free (identifies prompts) and aeo-content-free (creates/refreshes content). This skill closes the loop by measuring results.

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 ads from ad libraries (Facebook, LinkedIn, etc.) to understand messaging strategies, pain points highlighted, and creative approaches that resonate with audiences.

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。

Product Discovery through an 18-task methodology in 6 blocks — from market analysis to an investor-ready financial plan. Use when someone wants to run Product Discovery, validate a startup, assess a market hypothesis, prepare for an investment round, or raises an adjacent topic — idea validation, niche sizing, competitor teardown, product-market fit, pitch preparation, startup unit economics, geographic expansion into a new country, go-to-market for SEA / Asia / MENA. People rarely name PD explicitly; they say 'is there a market for this', 'assess my idea', 'I need a deck for an angel', 'we are entering Thailand/Singapore/UAE, how do we size it'. Use the skill in those cases too. Three modes: Light (~45 min, idea stage), Full (~2-3 h, MVP with customers), Geographic Expansion (~2 h, product entering a new geography). Produces 3-4 artifacts in /mnt/user-data/outputs/: one-pager.pptx, financial-plan.xlsx, presentation.pptx, optionally interview-guide.docx.

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 for read-first Amazon Sponsored Products optimization, product-aware growth, preflight readiness, and post-change monitoring reviews that can run standalone from static exports or use Rocketcart MCP as an optional Amazon Ads plus product-intelligence layer. Guides Codex to inspect Rocketcart profiles, live SP campaigns, product ads/ASIN context, category rank/BSR movement, competitor signals, product readiness, budget and targeting drift, snapshots/changelogs, and proposed approval-gated action rows without executing writes by default.

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。

Do market research, user research, and product validation on Reddit with semantic search across 50K+ subreddits, 20M+ posts, and 40M+ comments via reddapi.dev - search by meaning, not keywords, no Reddit OAuth or app registration needed. Use when the user wants to research what people say on Reddit, find user pain points and complaints, validate a product or niche idea, do competitor and market research, track subreddit trends over a date range, or discover which subreddits discuss a topic. Also use when the user mentions 'Reddit research', 'Reddit 调研', 'search Reddit', 'subreddit discovery', 'niche validation', 'pain points', 'user complaints', or 'Reddit trends'. Requires REDDAPI_API_KEY. For B2B lead scoring, see reddit-leads; for a bare API reference, see reddit-search-api.

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Use for first principles thinking, or when the user questions an inherited default: "why do we do it this way?", "is this cost really necessary?", "should we copy what competitors do?". Strips analogies and rebuilds from fundamentals. Skip for convention-following checklists.

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Use for SWOT analysis, or when the user wants to assess where a team, product or company stands: "strengths and weaknesses", "should we enter this market?", "review our position", "competitor comparison". Turns findings into actions. Skip for detailed planning or pure market sizing.

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Prices research, tests, surveys, dashboards and experiments before running them, by computing how much the result would raise expected utility - which is zero whenever no outcome would change the decision. Use when someone proposes an A/B test, user survey, market study, competitor analysis, analytics build, consultant, pilot, or "let's gather more data", and when deciding how large a study needs to be.

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Use when comparing this package to a peer / competitor — ours-vs-theirs verdict table, axis selection, adoption queue. Triggers on 'how do we compare to X', 'should we adopt their pattern'.

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 mapping competitors, naming defensibility, and finding white-space — moat reasoning, where-to-play, where-not-to-play. Triggers on 'who are we competing with', 'what's our moat'.

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。

Quando o usuário quer criar páginas de comparação com concorrentes ou alternativas para SEO e ativação de vendas. Use também quando o usuário menciona 'página de alternativas', 'página vs', 'comparação com concorrentes', 'página de comparação', '[Produto] vs [Produto]', '[Produto] alternativa', ou 'landing pages competitivas'. Cobre quatro formatos: alternativa singular, alternativas plurais, você vs concorrente, e concorrente vs concorrente. Enfatiza pesquisa profunda, arquitetura de conteúdo modular e tipos de seção variados além de tabelas de recursos.

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。