「sel」の検索結果

Amazon keyword research and market opportunity analysis for sellers. Retrieve autocomplete suggestions (long-tail keywords), analyze competitor landscape, and assess market opportunity for any keyword on 12 Amazon marketplaces (US/UK/DE/FR/IT/ES/JP/CA/AU/IN/MX/BR). No API key required. Make sure to use this skill whenever the user mentions Amazon product research, finding products to sell on Amazon, Amazon keyword ideas, niche analysis, competition analysis for Amazon, market opportunity on Amazon, comparing Amazon keywords, evaluating whether a product is worth selling, Amazon autocomplete data, seasonal demand for Amazon products, or anything related to researching what to sell on Amazon — even if they don't explicitly say 'keyword research'. Also trigger when the user asks vague questions like 'is this a good product to sell?', 'what's the competition like for X on Amazon?', 'should I sell X or Y?', or 'what are people searching for on Amazon?'.

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。

Dung khi can brief mot CHUOI NHIEU SLIDE — carousel Facebook, Instagram, LinkedIn hoac bo anh doc theo mach: hook o slide 1, xay gia tri o giua, CTA o slide cuoi, kem huong dan render HTML preview de duyet concept truoc khi vao production. Kich hoat khi user nhac 'brief carousel', 'lam carousel', 'bo slide dang Facebook', 'tach bai nay thanh carousel', 'brief slide', 'render carousel xem truoc', 'post nhieu anh'. Khong dung cho — mot anh tinh don le thi dung skill 42-brief-hinh-anh; slide thuyet trinh ban hang thi dung skill 71-sales-enablement; huong dan thao tac tren Canva thi dung skill 45-brief-canva.

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 a multi-slide carousel is needed for Instagram, Facebook, or LinkedIn — a narrative arc with the hook on slide one, value through the middle, CTA on the last, headline, body, visual direction, and background per slide, plus an HTML preview to approve the concept before production. Trigger on 'carousel brief', 'make a carousel', 'turn this into slides', 'LinkedIn carousel', 'slide by slide breakdown', 'preview the carousel first'. Not for — a single static image, see `42-image-brief-global`; the caption posted with it, see `37-social-caption-global`; production steps inside Canva or Figma, see `45-design-tool-brief-global`; scoring the finished slides, see `47-design-review-global`.

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。

心理咨询 / 心理治疗(临床实践者视角 — 接案与评估 / 个案概念化 / 主流流派技术(CBT 与第三浪潮 / 精神动力 / 人本存在 / 家庭系统 / 创伤治疗) / 伦理边界与危机干预 / 督导与个人成长 / 执业形态与经营 — 涵盖中国大陆行业现状 + 欧美持照体系,两套体系差异极大) (Psychotherapy & counseling — 心理咨询师 / 心理治疗师的临床实践(接案评估 / 个案概念化 / 主流流派技术 / 伦理与危机干预 / 督导成长 / 私人执业经营)) Master OS — automated mastery of Psychotherapy & counseling — 心理咨询师 / 心理治疗师的临床实践(接案评估 / 个案概念化 / 主流流派技术 / 伦理与危机干预 / 督导成长 / 私人执业经营): top builders' mental models, tool stack, current workflows, jargon, and where to keep up. Trigger this skill when the user works on Psychotherapy & counseling — 心理咨询师 / 心理治疗师的临床实践(接案评估 / 个案概念化 / 主流流派技术 / 伦理与危机干预 / 督导成长 / 私人执业经营) problems and wants industry-grade thinking, tool selection, or workflow guidance. 触发词：「心理咨询」「心理治疗」「psychotherapy」「counseling」「therapist」

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。

Query TikTok Shop store (seller) details, retrieving a complete store profile by sellerId with total sales, multi-period (1d/7d/30d/90d) sales and GMV, followers, rating, review count, positive feedback rate, delivery rate, response rate, in-store product count, promoting creator count, promotional video count, livestream count, price range, product categories, and estimated listing time. Trigger when users mention TikTok store detail, TikTok seller detail, TikTok store analysis, TikTok store data, TikTok store profile, TikTok Shop store detail, TikTok seller detail, Nexscope store profile. Even if the user does not explicitly mention "Nexscope" or "TikTok", trigger this skill whenever their need involves querying the full detail/profile of a specific TikTok Shop store (with a known sellerId).

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。

Nexscope Ozon category product search: fetches the product list for a given Ozon category ID, returning category-level aggregates (total sales, total revenue, average price, average rating, seasonality) and per-product sales, price, rating, review count, brand, seller, and fulfillment method. Use for category selection analysis, category bestseller mining, category capacity and price band analysis, seasonality assessment. Trigger when the user mentions Ozon category products, Ozon category analysis, Ozon category selection, Ozon category bestsellers, Ozon category total sales, Ozon category average price, Ozon category search, Ozon category products, category best-sellers, category analysis. Also trigger when the intent is to view products and category-level summary data within an Ozon category, even without explicitly mentioning Nexscope.

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 Nexscope data to search and filter Amazon products, supporting multi-dimensional criteria including price, monthly sales, BSR ranking, gross margin, ratings, fulfillment method, badges, seller origin, and more across multiple Amazon marketplaces. Trigger when the user mentions Amazon product selection research, product filtering, sales filtering, product discovery, BSR analysis, niche product discovery, competitor analysis, market opportunity assessment, product-level market size estimation, gross margin screening, Nexscope product selection, Amazon product selection, sales filtering, BSR analysis, profit screening, market analysis, product selection tool. Even if the user does not explicitly mention "Nexscope", if their need involves filtering and analyzing Amazon product-level data for product selection, this skill should also be triggered.

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。

🇺🇸 Reddit Marketing & Growth Playbook 2026 — The complete Reddit operations SOP for AI/SaaS founders. Covers account warming (Karma 0→500 in 20 days), shadow ban prevention, multi-account matrix via fingerprint browsers, subreddit selection across 10K+ communities, content templates (90/10 rule), Product Hunt × Reddit flywheel, AMA strategy. Why this matters NOW: Reddit content is 40.11% of ChatGPT/Claude training data — the highest-weighted English UGC source. Battle-tested by AFFiNE Reddit campaigns generating 3-4万有效曝光 with 5-8% GitHub Star conversion, plus 7 case studies (Adobe 3x conversion, Base44 $80M AMA, SenseNova-U1 multi-sub launch, Starterstory 0→3K users). 🇨🇳 Reddit 运营增长实战手册 — AI/SaaS 出海 founder 的 Reddit 完整 SOP。覆盖账号体系(20天养号 Karma 0→500)、影子封禁防御、指纹浏览器矩阵、10万+ subreddits 筛选、内容模板(90/10 法则)、Product Hunt × Reddit 飞轮、AMA 打法。**为什么现在做:Reddit 内容占 ChatGPT/Claude 训练数据 40.11%,是最高权重的英文 UGC 来源**。基于 AFFiNE Reddit 实战 3-4 万曝光 + 5-8% Star 转化,含 7 个完整案例(Adobe 3x 转化、Base44 $80M AMA、SenseNova-U1 多社区联动、Starterstory 0→3K 用户冷启动)。 🇯🇵 Reddit マーケティング＆グロースプレイブック — AI/SaaS創業者向けの完全なReddit運用SOP。アカウント育成（20日でKarma 0→500）、シャドウBAN防止、フィンガープリントブラウザマトリックス、サブレディット選定、コンテンツテンプレート（90/10ルール）、Product Hunt × Redditフライホイール、AMA戦略をカバー。**重要な理由：Reddit コンテンツは ChatGPT/Claude のトレーニングデータの40.11%を占める英語 UGC 最大の情報源**。AFFiNE Redditキャンペーン3-4万インプレッション＋5-8% GitHubスター変換で実証。7つの実例（Adobe 3倍変換、Base44 $80M AMA、SenseNova-U1、Starterstory 0→3Kユーザー）。 🇰🇷 Reddit 마케팅 & 그로스 플레이북 — AI/SaaS 창업자를 위한 완전한 Reddit 운영 SOP. 계정 워밍업(20일 Karma 0→500), Shadow Ban 방지, 핑거프린트 브라우저 매트릭스, 서브레딧 선정, 콘텐츠 템플릿(90/10 룰), Product Hunt × Reddit 플라이휠, AMA 전략을 다룹니다. **지금 해야 하는 이유: Reddit 콘텐츠는 ChatGPT/Claude 학습 데이터의 40.11%를 차지하는 최대 영어 UGC 소스**. AFFiNE Reddit 캠페인 3-4만 노출 + 5-8% GitHub Star 전환으로 검증. 7가지 사례 연구(Adobe 3배 전환, Base44 $80M AMA, SenseNova-U1, Starterstory 0→3K 사용자). Triggers: "reddit marketing" | "reddit growth" | "reddit ads" | "reddit advertising" | "reddit strategy" | "reddit promotion" | "subreddit marketing" | "reddit playbook" | "reddit SOP" | "reddit shadow ban" | "shadow ban prevention" | "reddit karma" | "reddit AMA" | "reddit product launch" | "reddit AI training data" | "reddit GEO" | "AFFiNE reddit case" | "Base44 AMA" | "SenseNova Reddit" | "subreddit selection" | "r/SaaS posting" | "r/MachineLearning self-promotion" | "fingerprint browser matrix" | "AdsPower reddit" | "reddit account farming" | "reddit 90/10 rule" | "reddit content strategy" | "reddit indie founder" | "reddit cold start" | "Reddit 运营" | "Reddit 营销" | "Reddit 防封" | "Reddit 矩阵号" | "Reddit 出海" | "Reddit 引流" | "Reddit 冷启动" | "影子封禁" | "Reddit Karma" | "Reddit 养号" | "Reddit AMA" | "Reddit マーケティング" | "Reddit グロース" | "Reddit 마케팅" | "Reddit 그로스"

Establish and maintain longitudinal baselines of CLI binary contents across versions. Covers marker selection by category (API / identity / config / telemetry / flag / function), weighted scoring, threshold-based system-presence detection, and per-version baseline records. Use when tracking a feature's lifecycle across releases, when probing for dark-launched or removed capabilities, or when verifying that a scanning tool itself still catches known-good markers on old binaries.

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 this skill to select the right Salesforce integration pattern — from point-to-point to event-driven to hub-and-spoke — by applying the official Salesforce two-axis decision framework (integration type × timing) to a business integration scenario. Trigger keywords: integration pattern decision, choose integration approach, Salesforce integration architecture, when to use platform events vs API, integration type selection. NOT for implementation of any specific integration pattern (use domain-specific integration skills), MuleSoft architecture (use architect/mulesoft-anypoint-architecture), or middleware vendor selection. More triggers: integration decision record, Bulk API vs REST for a nightly load, external Id upsert, Named Credential vs Remote Site Setting, platform event vs CDC, who calls whom.

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Mint a new YYYY-MM-DD-exact-coding-baseline snapshot under research/workflow-dev/export/. Detects the current best correctness- oriented workflow from research/workflow-dev/workflow-construction.md (or takes an explicit source-workflow argument) and transforms it from a lab workflow into a consumer-ready one on three axes: strips lab-only measurement content, re-enables human-in-the-loop checkpoints, and converts auto-loading config into an explicitly-invoked skill. Supports both promoted EXACT Coding lines: Opus/Hybrid and SOL/Predictive TDD. Exports Claude Code, pi, OpenCode, cursor-agent and, for SOL, Copilot. Trigger when the user says "exact-coding baseline export", "neue exact-coding baseline", "exact-coding-baseline-export", or asks to refresh the baseline snapshot.

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。

Check the latest Claude (Anthropic), OpenAI Codex, and Google Gemini model releases from official primary sources, update model selections in this dotfiles repo, and update the Claude Code, Codex, and Gemini CLIs through their configured managers. Every run checks both the model settings and CLI for the selected provider, then scans the invoking repository for hardcoded model IDs. Use when the user asks to "モデル更新", "モデルを最新に", "最新モデル確認", "Codex/Claude Code/Gemini CLI本体の更新", "model bump", "update models", or "update agent CLIs". Do NOT use for one-off model selection in a single conversation, general model questions, or unrelated package updates.

Redux Toolkit selector rules against re-renders, recalculation warnings, and render loops. Use when writing useSelector/useAppSelector or createSelector, deriving state in a connected component, or seeing 'Selector returned a different result when called with the same parameters'.

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 three-card social-media carousel laid out as 1080×1080 squares — three cinematic, on-brand panels with display headlines that connect across the series ("onwards." → "to the next one." → "looking ahead."). Each card has a brand mark, a number / total, a caption, and a "loop" affordance. Use when the brief asks for a "carousel post", "social carousel", "Instagram carousel", "LinkedIn series", "X thread cards", or "三连发".

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。

When the user wants to design, construct, or improve an offer — the thing they actually sell — including value framing, bonus stacking, guarantee design, scarcity/urgency, naming, and payment structure. Also use when the user mentions 'offer,' 'offer design,' 'build an offer,' 'grand slam offer,' 'irresistible offer,' 'value stack,' 'bonus stack,' 'guarantee,' 'risk reversal,' 'money-back guarantee,' 'scarcity,' 'urgency,' 'high-ticket offer,' 'productize a service,' 'naming an offer,' 'payment plan,' 'down-sell,' 'upsell offer,' or 'why isn't my offer converting.' Best for services, agencies, courses, coaching, info products, high-ticket B2B, and direct-response. If you run pure self-serve SaaS, read pricing first — tiers and packaging do more work there. For price level itself (tiers, freemium, value metric), see pricing. For the page that presents the offer, see copywriting. For the launch moment, see launch. For sales collateral, 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。

Infuse social-emotional learning (SEL) into a concept-centered OpenMAIC classroom as a parallel learning goal. Use when the user asks to add emotional awareness, self-management, empathy, collaboration, relationship skills, resilience, or responsible decision-making to a subject lesson. Do not use when SEL itself should be the standalone content of a counseling, advisory, psychology, or homeroom lesson.

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Use when a project keeps its state in Superself (a `<!-- superself:begin` block in AGENTS.md or CLAUDE.md, or `self setup` resolves the directory to a registered project): read `self context` at session start, attach work to a work unit, report with evidence, and record confirmed decisions so the next session picks up where this one left off.

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General Counsel advisory for startups: contract review (MSA, SaaS, NDA, DPA, employment), IP strategy, term sheet decoding, and regulatory landscape mapping. Use when reviewing any contract or term sheet, deciding when to engage outside counsel, defining IP strategy, evaluating regulatory exposure (HIPAA, GDPR, FDA, fintech), or when user mentions general counsel, GC, legal review, contract risk, term sheet, IP assignment, or regulatory exposure. NOT a substitute for licensed counsel — surfaces questions to bring to qualified attorneys.

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Deploy a production self-hosted n8n end-to-end to a fresh Linux VM over SSH, using Docker Compose behind a Caddy reverse proxy with automatic HTTPS. Use whenever the user wants to self-host, install, set up, provision, or deploy n8n on their own server/VPS/box (Hetzner, DigitalOcean, AWS EC2, bare metal, etc.) — in either single/regular mode or queue mode with workers — or to update, back up, restore, or harden such an instance. This is for SELF-HOSTED n8n (Docker), not n8n Cloud and not building workflows. The skill makes the agent ask single-vs-queue first, collect the domain/SSH/timezone inputs, generate fresh secrets on the box, and bring the stack up with TLS. Trigger on "deploy n8n", "self-host n8n", "install n8n on my server", "n8n docker compose", "n8n queue mode / workers / scaling", "n8n reverse proxy / SSL", "back up / update my n8n", or "we don't want to give every user the OAuth client secret" / "enable the Sign in with Google button" (credential overwrites).

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This skill should be used when the harness, scaffold, workflow, or optimizer itself is the optimization target: recursive self-improvement (RSI) loops, meta-harnesses, self-improving harnesses that mine their own failures and propose bounded edits, evolutionary or population-based search over agent scaffolds, acceptance gates for self-modifying systems, and agentic context evolution where the mechanism that produces context is versioned and evolved. Route governance of a single autonomous loop (locked surfaces, durable logs, rollback, novelty gates, approval boundaries) to harness-engineering, measurement and quality-gate design to evaluation, judge design to advanced-evaluation, and remote sandbox infrastructure to hosted-agents.

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When the user wants to sell through social media, optimize LinkedIn for sales, build DM sequences, or convert content engagement into pipeline. Also use when the user mentions 'social selling,' 'LinkedIn selling,' 'LinkedIn DMs,' 'social prospecting,' 'LinkedIn Sales Navigator,' 'DM sequences,' 'LinkedIn outreach,' 'social pipeline,' or 'LinkedIn optimization.' This skill covers social selling strategy from profile optimization through DM-to-deal conversion. Do NOT use for technical implementation, code review, or software architecture.

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。

Deploy a production self-hosted n8n end-to-end to a fresh Linux VM over SSH, using Docker Compose behind a Caddy reverse proxy with automatic HTTPS. Use whenever the user wants to self-host, install, provision, or deploy n8n on their own server/VPS (Hetzner, DigitalOcean, AWS EC2, bare metal) — single/regular mode or queue mode with workers — or to update, back up, restore, or harden such an instance, or make Python Code nodes run on it (task runners). For SELF-HOSTED n8n (Docker), not n8n Cloud and not building workflows. The skill makes the agent ask single-vs-queue first, collect domain/SSH/timezone inputs, generate fresh secrets on the box, and bring the stack up with TLS. Trigger on "deploy n8n", "self-host n8n", "n8n docker compose", "n8n queue mode / workers", "n8n reverse proxy / SSL", "back up / update my n8n", "Python runner unavailable" / "n8nio/runners sidecar", or "we don't want to give every user the OAuth client secret" / "enable Sign in with Google" (credential overwrites).

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。

Extracts full item detail from any open eBay item URL, returning JSON with url, itemNumber, title, subTitle, categories, price, priceWithCurrency, currency, wasPrice, available, availableText, sold, image, images, seller, sellerUrl, sellerFeedbackCount, sellerPositiveRating, itemLocation, brand, type, mpn, upc, ean, condition, shippingCost, shipping, whyToBuy, and itemSpecifics (full label/value map). Works across all eBay regional TLDs. Use when user mentions eBay item page, eBay listing detail, eBay product page, eBay itm, ebay.com/itm, eBay item scraper, extract eBay item details, eBay item specifics, scrape eBay item, eBay sold count, eBay availability, eBay brand MPN UPC EAN, eBay item location, eBay seller feedback, eBay wasPrice, eBay hi-res images, eBay itemNumber, eBay per-item enrichment. Also applies to enriching item URLs from a listing, monitoring price and stock, competitive product research, brand catalog audits, and pulling full field set from an individual eBay 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。

Amazon product detail page scraper: extract full product data from any open Amazon product detail URL (any /dp/{asin} or /gp/product/{asin} page across all Amazon regional TLDs) — returns asin, url, title, brand, price, listPrice, stars, reviewsCount, starsBreakdown (5/4/3/2/1 star percentages), answeredQuestions, inStock, inStockText, delivery, fastestDelivery, returnPolicy, breadCrumbs, features (bullet points), description, bookDescription, thumbnailImage, highResolutionImages, galleryThumbnails, productOverview (Brand/Model/etc.), attributes (tech spec table), attributesMapped (flat key-value), bestsellerRanks (rank + category + url), variantAttributes (currently selected color/size/style), variantAsins, seller (name + id + url), isAmazonChoice, amazonChoiceText, monthlyPurchaseVolume, hasAPlusContent, hasBrandStory, aiReviewsSummary, reviewsLink, productPageReviews (sample), videosCount, locationText, loadedCountryCode. Works on amazon.com, amazon.co.uk, amazon.de, amazon.co.jp, amazon.fr, amazon.it, amazon.es, amazon.ca, amazon.com.au, amazon.in, amazon.com.mx, amazon.com.br, amazon.nl, amazon.se, amazon.sg, amazon.ae, amazon.sa, amazon.pl, amazon.tr, amazon.eg. Use when user mentions Amazon product page, Amazon /dp/, Amazon dp URL, Amazon ASIN scraper, Amazon product detail, Amazon PDP, Amazon product data, Amazon product info, Amazon product fields, Amazon product attributes, Amazon full field extraction, Amazon per-ASIN enrichment, Amazon rating breakdown, Amazon stars breakdown, Amazon bestseller rank, Amazon BSR, Amazon variants, Amazon variant ASINs, Amazon color size options, Amazon feature bullets, Amazon A+ content, Amazon brand story, Amazon AI review summary, Amazon bought in past month, Amazon monthly sales volume, Amazon Amazon's Choice badge, Amazon seller info, scrape Amazon product, enrich Amazon ASIN, Amazon ASIN details, Amazon product review data. Also applies to bulk ASIN enrichment from a list of URLs, competitive product research, brand catalog audits, price and stock monitoring per ASIN, and building a normalized product dataset from a list of Amazon URLs.

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。