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概要と使いどころ
Trigger machine account authentication with PetitPotam (MS-EFSR) and Coercer (MS-RPRN, MS-DFSNM, MS-FSRVP, MS-EVEN) via Coercer's scan/coerce/fuzz modes, feeding the coerced NTLM auth into a relay against AD CS Web Enrollment (ESC8), LDAP (RBCD), or SMB. Use in authorized engagements to complete a coercion-relay chain against a Domain Controller, or to validate coercion detections and signing/EPA mitigations.
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 a competitive analysis brief for one or more competitors or a feature area. Use when informing product strategy or feature prioritization, building sales battle cards, prepping board or investor materials, or deciding where to differentiate vs. achieve parity.
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 marketing skill for positioning, GTM strategy, competitive intelligence, and product launches. Use when the user asks about product positioning, go-to-market planning, competitive analysis, target audience definition, ICP definition, market research, launch plans, or sales enablement. Covers April Dunford positioning, ICP definition, competitive battlecards, launch playbooks, and international market entry. Produces deliverables including positioning statements, battlecard documents, launch plans, and go-to-market strategies.
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。
Brainstorm product positioning ideas differentiated from competitors. Identifies top competitors and generates positioning statements with rationale. Use when developing product positioning, differentiating from competitors, or crafting brand positioning 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。
Build an evidence-cited SWOT of one company — yours or a competitor's — from public sources, ending with the S-O/W-T crossings. Use for strategy reviews, board prep, or competitor depth.
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。
Orchestrate a complete competitive analysis across six steps, from landscape to strategic direction. Use when you need the full picture, not a single scan or card.
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。
Trustpilot customer reviews scraper for any company listed on trustpilot.com — given a company domain (e.g. shopify.com, apple.com, shopwagandtail.com) plus optional filters (page number, single star rating 1-5, single language ISO code, verified-only flag, has-company-reply flag, date period last30days/last3months/last6months/last12months, free-text keyword search, and reviewer countryCode client-side filter), extracts paginated reviews with 20+ fields per review: reviewId, reviewUrl, reviewTitle, reviewDescription, reviewRatingScore (1-5), reviewDate (ISO publishedDate), reviewDateOfExperience, reviewLabel, isReviewVerified, reviewer (display name), reviewerId, reviewersCountry (ISO Alpha-2), reviewLanguage, reviewCompanyResponse (the company reply text), plus pagination metadata (currentPage, totalPages, totalCount). Optional flags add reviewer profile metadata (reviewerNumberOfReviews, reviewerProfileIsVerified), reply analysis dates (companyReplyPublishedDate, companyReplyUpdatedDate), extended metadata (reviewSource, reviewVerificationSource, reviewLikes), and review photos. Use when user mentions Trustpilot reviews, scrape Trustpilot, get reviews from Trustpilot, Trustpilot review scraper, Trustpilot customer reviews, extract Trustpilot reviews, Trustpilot review data, download Trustpilot reviews, paginate Trustpilot, paginated Trustpilot reviews, filter Trustpilot reviews by star, filter Trustpilot by language, verified reviews Trustpilot, has reply Trustpilot, company response Trustpilot, Trustpilot reply analysis, brand monitoring Trustpilot, sentiment analysis Trustpilot, competitor reviews Trustpilot, bulk reviews from a Trustpilot page, batch download reviews, trustpilot.com reviews scraping, fake review research Trustpilot, Trustpilot dataset, persona research from Trustpilot reviews, Trustpilot keyword search reviews, Trustpilot date range reviews, review export Trustpilot. Also applies to comparing review trends across competitors, training data for LLM sentiment classifiers, monitoring competitor response time, exporting reviews for BI dashboards, lead generation from active reviewers, ML / fake-review detection, and aggregator sites that display third-party reviews.
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。
Scrapes Amazon product data from ASINs using browseract.com automation API and performs surgical competitive analysis. Compares specifications, pricing, review quality, and visual strategies to identify competitor moats and vulnerabilities.
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 products, launch history, and acquisition evidence from public sources or supplied materials. Use when evaluating growth claims, comparing competitors, or choosing growth experiments. Produces a cited brief that separates observations, attributed claims, estimates, and hypotheses.
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 asks to "track our share of voice", "what share of the conversation do we own vs competitors", or "trend our SOV this quarter"; computes SOV% = brand mentions ÷ (brand + competitor panel mentions) per platform per period on a LOCKED competitor panel — a panel switch invalidates the trend (restart the series and log the break; the ECHO O3 rule) — plus a sentiment-weighted SOV variant (sentiment labeled Estimated unless human-coded) and a Wikipedia-pageviews attention-share alternative; built from keyless listening connectors, gdelt.py news echo, and user exports — public counts only, closed platforms are never scraped. Not for backlink or offsite SEO signals — use offsite-signal-analyzer. 声量份额/竞品声量对比/提及份额/注意力份额
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 asks to "track competitor influencer marketing", "see who my rivals partner with", or "benchmark my influencer program"; produces a competitor partnership roster, campaign and content-strategy breakdown, performance estimates, and a gap/opportunity list. Not for finding your own new creators — use influencer-discovery. 竞品达人合作追踪/竞品营销分析
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 asks to "build battle cards", "prep the sales team for launch", or "write the internal launch FAQ"; produces the internal enablement kit for a sales-led launch — battle cards vs each named alternative (where we win / where they win / trap questions, every fact traceable), a sales talk track derived from the PR-FAQ spine, an objection-handling table (objection → response → evidence), internal FAQ + CS macros, and an internal launch announcement with embargo discipline. Not for the external message house — use message-house-builder; not for competitor tracking itself — use competitor-tracker or competitor-analysis; not for outbound sequences — use cold-outbound-sequencer. 销售赋能/battle card/销售叙事/异议处理/内部FAQ
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 asks to "analyze competitors" or "竞品分析"; benchmarks competitor keywords, content, backlinks, AI citations, and traffic share into strengths, weaknesses, and an action plan. Not for a pairwise topic-coverage gap map — use content-gap-analysis. 竞品分析/竞争对手
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。
Discover what customers truly need by analyzing the "job" they hire your product to do. Use when the user mentions "customer discovery", "why customers churn", "what job does this solve", "competing against luck", "product-market fit", "switching behavior", "milkshake moment", or "functional vs emotional jobs". Also trigger when investigating why users choose competitors, designing features around real customer needs, or reframing a value proposition. Covers JTBD interviews, competition analysis, and jobs-oriented roadmaps. For product positioning, see obviously-awesome. For rapid validation, see design-sprint. For non-leading interview technique, see mom-test.
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。
SERP-informed outline generation with H2/H3 heading hierarchy, competitive content gap analysis, section-by-section word count targets, chart and image placement markers, optional FAQ question planning, and internal linking zones. Skeleton only: structure, H2/H3 hierarchy, word counts, optional FAQ slots. Use blog-brief instead if you need full competitive analysis, statistics research, and image suggestions. Lighter than a full content brief, generates article skeleton and structure only, ready for /blog write to consume. Use when user says "outline", "blog outline", "content outline", "structure blog", "plan sections", "article skeleton", "heading structure", "SERP analysis", "competitive outline", "plan article".
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 choose, change, or evaluate their App Store / Google Play category and subcategory — including primary vs secondary category trade-offs, chart-rank competitive analysis, category-driven discoverability, and how category choice affects featuring eligibility. Use when the user mentions "which category", "App Store category", "primary category", "secondary category", "change my category", "Health & Fitness vs Lifestyle", "Productivity vs Utilities", "rank higher in a smaller category", "category chart", "subcategory", "Play Store category", or "should I switch categories". For full ASO health beyond category, see aso-audit. For competitor analysis within the chosen category, see competitor-analysis. For chart movements within categories, see market-movers.
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。
Formats content to be eligible for featured snippets and SERP features. Creates snippet-optimized content blocks based on best practices. Use PROACTIVELY for question-based content.
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 website's SEO visibility, keyword rankings, traffic estimates, and competitive positioning. Uses web search probes, SimilarWeb (free tier via web), and site: queries to build an SEO profile without requiring paid tool subscriptions. Useful for competitive intel, gap analysis, and reverse-engineering a company's organic acquisition 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。
Find leads by scraping engagers from a competitor's top LinkedIn posts. Given one or more company page URLs, scrapes recent posts, ranks by engagement, selects the top N, extracts all reactors and commenters, ICP-classifies, and exports CSV. Use when someone wants to "find leads engaging with competitor content" or "scrape people who interact with [company]'s LinkedIn posts".
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 a specific competitor across their website, reviews, ads, social presence, and pricing — then produce a structured sales battlecard with positioning traps, objection handlers, landmine questions, and win/loss themes. Chains web research, review mining, and ad intelligence. Use when sales needs competitive ammo or when entering a new market with established incumbents.
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 competitors, analyze their messaging, and generate a positioning document with category definition, differentiation claims, value propositions, and proof points. Chains web research, competitor site analysis, and review mining to produce a positioning doc ready for website copy and sales deck use. Use when a product marketing team needs to define or refresh positioning ahead of a launch, rebrand, or competitive shift.
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 and run ongoing competitive intelligence monitoring for a client. Tracks competitor content, ads, reviews, social, and product moves.
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 competitor price tracking and monitoring workflows. Track price changes, detect promotions, analyze pricing patterns, and get alerts for competitive price movements.
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。
E-commerce product description generator for any platform. Generates optimized titles, bullet points, descriptions, and backend keywords using competitor research + keyword scoring + FABE copywriting. Two modes: (A) Create — generate listing from product specs with optional competitor analysis, (B) Optimize — improve existing listing with keyword gap analysis. Supports Amazon, eBay, Walmart, Shopify, Etsy, TikTok Shop, Lazada, Shopee. No API key required. Use when: (1) writing a new product listing, (2) analyzing what makes competitors rank, (3) improving an underperforming listing.
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。