「search」の検索結果

企業の事業内容、競争優位、経営陣、リスクを価値投資の視点で調べ、財務データの照合と複数シナリオの評価に基づく価格帯・判断を研究レポートにまとめます。

• 投資前に企業を詳しく調べたいとき
• 競争優位と経営陣の評価
• 複数シナリオでの企業価値比較

投資調査の結果を、事業の仕組みや反対意見、株価評価の根拠が伝わるレポートに整え、新規投資家と保有者それぞれの売買条件まで明確にするスキル。

• 長い投資調査レポートを再構成したいとき
• 企業の収益構造と競争優位を説明
• 弱気の見方とリスクの観測項目を補強

未上場企業の事業・財務・競争・リスク・技術を複数エージェントで調べ、公開情報を照合しながら、推定企業価値と判断に残る不確実性を整理するスキル。

• 未上場企業の事業とリスクを調べたいとき
• 調達時の評価額と事業価値を比べたいとき
• 採用や特許から経営動向を探りたいとき

機械学習の学習指標や設定をW&Bに記録し、実験結果を比較・可視化します。学習条件の自動探索、データやモデルの版管理、チームでの結果共有まで支援します。

• 学習指標の記録と可視化
• 学習条件を変えた実験の比較
• より良い学習条件を自動探索したいとき

調査・執筆・分析などを担うAIエージェントをCrewAIで組み合わせ、成果を引き継ぎながら作業する仕組みを構築。順次実行や管理役による分担、記憶の設定を案内します。

• 調査・執筆・編集の担当を連携
• 管理役による専門エージェントの分担
• 分析結果に応じた処理の分岐

言語モデルの出力を正規表現や文法で制約し、JSONや日付などの形式を整えるほか、分類・情報抽出・複数段階の処理をPythonで組み立てるスキル。

• 決めた構造のJSONを生成したいとき
• 日付・メール・識別子の形式を指定
• 固定ラベルで文章を分類したいとき

画像の説明文生成、画像への質問応答、文章からの画像検索をBLIP-2で実装するスキル。モデル選びから一括処理、メモリ使用量の調整まで案内します。

• 複数画像の説明文を生成したいとき
• 画像への質問応答を実装したいとき
• 文章から画像を検索したいとき

LLMの知識・推論・コード生成などを60以上の共通評価課題で検証し、モデル間の性能比較や学習途中の変化の追跡、研究向けの結果整理を支援します。

• 知識・推論の共通課題でモデルを比較
• 学習途中のモデル性能を追跡したいとき
• 研究報告用に評価結果を整理したいとき

Audit Google Ads measurement, Search, Shopping, Performance Max, Demand Gen, YouTube-linked inventory, keywords and search terms, negative-keyword generation or review, creative assets, bidding, budgets, settings, and policy. Use for Google Ads, AdWords, Search campaigns, search terms reports, broad negatives, Shopping, Performance Max, PMax, Demand Gen, GAQL, or Google conversion tracking. Read-only; use ads-optimize to change campaigns.

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。

This skill helps users extract structured video list data and comment data from YouTube using the BrowserAct API. The Agent should proactively apply this skill when users request searching for YouTube videos and their comments, analyzing viewer sentiment for a specific video topic, gathering audience feedback on AI or automation, extracting a list of top videos and their viewer reactions, compiling YouTube video data along with user opinions, retrieving competitor video titles and related audience discussions, monitoring public response to specific YouTube search keywords, summarizing comments from search results for market research, tracking viewer engagement metrics and replies for trending topics, collecting YouTube video URLs and author details alongside community discussions, or automating the extraction of YouTube comments without manual scraping.

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。

This skill helps users automatically extract structured article details and full content from Zhihu via the BrowserAct API. Agent should proactively apply this skill when users express needs like: searching for Zhihu articles on a specific topic, tracking industry trends on Zhihu, monitoring public relations or sentiment on Zhihu, collecting competitor updates, getting the latest reports on specific keywords, monitoring brand exposure in Zhihu media, researching market hot topics, summarizing daily Zhihu industry news, retrieving hot events from the past week, extracting structured data for market research, finding full Zhihu articles for AI agents, extracting full article body from Zhihu links.

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。

Searches Meta Ad Library (Facebook/Instagram/WhatsApp ads) by keyword or Facebook page ID and extracts ad details including creatives, copy, CTA, publisher platforms, spend, impressions, reach estimates, and page transparency info. Use when user mentions Meta Ad Library, Facebook ads scraper, Instagram ads data, FB ad library, search Facebook ads, get ads from a Facebook page, scrape Meta ads, Facebook advertising data, ad creative extraction, competitor ads analysis, brand ads monitoring, Meta advertising transparency, political ads Facebook, housing ads Facebook, view all ads from a page, facebook ads search, fb ads library api, facebook ad archive, instagram ad data, get ad creatives.

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。

X (Twitter) keyword-based reply posting: search tweets by keyword, read each tweet's content, generate contextual replies from a configured brand persona, and post replies to the reply area. Use when user wants to batch reply to X tweets by keyword, auto-comment on X topic tweets, drive traffic via X comments, X comment outreach, search X tweets and leave comments, bulk reply to Twitter search results, keyword comment on Twitter, post replies on X search page, Twitter keyword comment marketing, X reply campaign, engage with X discussions, or comment on tweets matching a topic.

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。

Search LinkedIn job listings and extract full job details. Supports filtering by work type (remote/on-site/hybrid), contract type (full-time/part-time/contract/internship), experience level, date posted, and company. Returns job title, company, location, work type, contract type, experience level, posted date, applicant count, job description, salary, and direct job URLs. Use when user mentions linkedin jobs, linkedin job search, scrape linkedin jobs, extract linkedin job listings, find jobs on linkedin, job openings, job postings linkedin, linkedin career search, job hunting linkedin, linkedin vacancy, jobs remote linkedin, work from home jobs linkedin, linkedin scraper jobs, linkedin job data, linkedin hiring, collect job leads linkedin.

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。

This skill is designed to help users automatically extract business data from Google Maps search results. The Agent should proactively apply this skill when the user makes the following requests searching for coffee shops in a specific city, finding dentists or medical clinics nearby, tracking competitors' locations in a certain area, extracting business leads from Google Maps lists, gathering restaurant data for market research, finding hotels or accommodation options in a region, locating specific services like coworking spaces or gyms, monitoring new business openings in a neighborhood, collecting contact information and addresses for sales prospecting, analyzing price ranges and cuisines of local eateries, getting ratings and review counts for a list of businesses, exporting local business data into a CRM or database.

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。

Search 10 academic paper databases via REST APIs for research papers, preprints, and scholarly articles. Covers PubMed, PMC (full text), bioRxiv, medRxiv, arXiv, OpenAlex, Crossref, Semantic Scholar, CORE, Unpaywall. Use when searching for papers, citations, DOI/PMID lookups, abstracts, full text, open access, preprints, citation graphs, author search, or any scholarly literature query. Triggers on mentions of any supported database or requests like "find papers on X" or "look up this DOI".

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 "generate daily paper", "search arXiv for EEG papers", "find EEG decoding papers", "review brain-computer interface papers", or wants to create paper summaries for EEG/brain decoding/speech decoding research. This skill automates searching arXiv for recent papers on EEG decoding, EEG speech decoding, or brain foundation models, reviewing paper quality, and generating structured Chinese/English summaries.

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。

Plan, draft and refine research papers with reproducible analysis and publication-ready 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。

Structured literature review using a parallel fleet of Librarian agents. Searches top journals, working paper repositories (NBER, SSRN, IZA), and traces citation chains from key papers. Make sure to use this skill whenever the user wants to survey existing research on a topic — not to find datasets or write a paper. Triggers include: "review the literature", "find related papers", "what's been done on X", "search for papers on", "do a lit review", "find papers about", "what papers should I cite", "who has written about this", "survey the literature", "find prior work on", or any request to locate and summarize academic publications on a topic.

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。

Main orchestration workflow for systematic literature research - search, evaluate, traverse, synthesize

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。

This skill covers applied microeconomic empirical methods and research design. Use when the user is selecting an identification strategy, comparing estimators, running diagnostics, designing a research study, or evaluating an empirical strategy. Triggers on "which method", "what estimator", "how to choose", "method comparison", "empirical strategy", "research design", "applied micro", "identification strategy", "power analysis", "design-based", "model-based", "minimum detectable effect", "specification".

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。

Recommend AND run open-source AI tools, agents, Claude Code / Codex skills, and MCP servers for any stage of a literature review — searching, reading, extracting, synthesizing, screening, citation-checking, and paper writing. Use when the user asks "what tool should I use to..." OR "install/run/use <tool> to ..." for research/lit-review work: automating a survey or related-work section, PDF→Markdown extraction for LLMs (MinerU/marker/docling), PRISMA / systematic review (ASReview), citation-backed Q&A over PDFs (PaperQA2), wiring papers into Claude/Cursor via MCP (arxiv/paper-search/zotero servers), or chatting with a Zotero library. Ships a launcher (scripts/litrun.py) that installs each tool in an isolated venv and runs it. Curated catalog of 70+ vetted projects. 支持中英文（用于「文献综述工具选型」与「一键安装/运行」）。

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。

Industry and market research. Market sizing, structure, competition, regulation, supply chains, pricing, M&A. Produces a single compact, source-cited research report with Porter's Five Forces, HHI / CR4, PESTLE, and trade flows. Supports UK, US, EU, Australia, and global scope, with multi-geography comparison.

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。