「search」の検索結果

財務指標による銘柄の絞り込みと投資テーマの調査を組み合わせ、買い・空売りの候補を5〜10件選び、根拠やリスク、調査の優先順位を整理するスキルです。

• 割安・成長・優良株の条件で銘柄を探したいとき
• 投資テーマから受益企業を見つけたいとき
• 業績や会計の懸念から空売り候補を探したいとき

上場・非上場企業の事業や財務情報を集め、株式調査、M&A、買収候補の検討、営業面談など、読み手の目的に合わせた簡潔なWord資料にまとめるスキル。

• 株式調査向けの企業概要作成
• M&A・買収候補の企業調査
• 営業面談の事前準備

PostgreSQLのSQLやデータ設計を見直し、実行計画とインデックスの改善から、JSONB・全文検索・高度な集計・保守の検討まで支援するスキル。

• 遅いクエリの調査とインデックス選定
• JSONB検索や全文検索の見直し
• 累計・順位を求める集計SQLの作成

context-maticの使い方を対話形式で学び、利用可能なAPIの一覧から選んで、プロジェクトの言語に合う認証方法やデータ構造、呼び出し例を確認するスキル。

• context-maticの用途を知りたいとき
• プロジェクトで使えるAPIの確認
• APIの認証方法や導入手順の把握

学術論文や調査レポートから投資指標と売買戦略を抽出し、過去データによる検証、結果の評価・保存、運用中の有効性低下の監視までを既存ツールでつなぐスキル。

• 論文から投資指標を抽出したいとき
• 売買ルールを過去データで検証
• 研究結果の評価と保存

未上場企業を事業・財務・競争・技術など六つの視点から調べ、企業価値の幅と上場・売却の可能性を整理します。情報の信頼度や不足も明示する調査の枠組みです。

• 未上場企業の事業と価値を調べたいとき
• 売上や資金調達情報の矛盾の確認
• 企業の説明と採用・特許動向の照合

Web search and research using Perplexity AI. Use when user says "search", "find", "look up", "ask", "research", or "what's the latest" for generic queries. NOT for library/framework docs (use Context7) or workspace questions.

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。

Deep-research a topic end to end and produce a permanent, reusable knowledge asset: archive every primary source verbatim (gated by the user's privacy/retention posture), write one 1:1 summary per source, then synthesize a single self-contained compendium page. Depth is a dial (base synthesis → grounded primaries → books + counter-canon → saturation), each level an idempotent superset of the one below. Distinct from data-research (structured trackers) and perplexity-research (web deltas): this produces prose knowledge synthesis backed by an archived source corpus.

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Audits and fixes both halves of being found — classic search and AI answers. Search side: rankings, site structure, page speed, titles and descriptions, and content that answers what customers search for. AI side: whether assistant crawlers can reach the site, pages render without JavaScript, an llms.txt file, schema.org data, and presence in the directories assistants read. For online stores it also runs a bulk catalog cleanup, rewriting product titles, descriptions, alt text, and SEO fields in approved batches. Works on any public website with no connector. Use this whenever the owner talks about being found online, including "nobody finds us on Google," "how do I show up in ChatGPT," "make my website AI friendly," "SEO audit," "GEO," "AEO," "AI search visibility," "my competitor ranks above me," "fix my product listings," or "I asked an AI about my industry and we weren't in the answer."

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Research a target company and optionally a specific contact - company overview, recent news, likely priorities, and fit against your ICP. Cross-references existing CRM records. Use when the user asks to "research [company]", "look into [company]", "prospect research on [company]", "look up [person]", "intel on [prospect]", "who is [person] at [company]", or "tell me about [company]" when the company is a prospect rather than an existing account.

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Use when managing the money for an internal R&D program or portfolio — building a multi-period program budget with the F&A (indirect) split, tracking burn rate and runway against value-inflection milestones, or routing R&D cost items to a capitalize-vs-expense determination. Every budget output surfaces its assumptions block; capitalize-vs-expense is decision-support only and routes to a named finance owner — it never books an entry or decides accounting treatment. Distinct from finance/financial-analysis (corporate DCF, close, valuation) and research/grants (funding discovery — this manages money already won).

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。

Google SEO APIs: Search Console (Search Analytics, URL Inspection, Sitemaps), PageSpeed Insights v5, CrUX field data with 25-week history, Indexing API v3, and GA4 organic traffic. Provides real Google field data for Core Web Vitals, indexation status, search performance, and organic traffic trends. Use when user says "search console", "GSC", "PageSpeed", "CrUX", "field data", "indexing API", "GA4 organic", "URL inspection", or "real CWV data".

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 and analyze research papers, find related work, summarize key ideas. Use when user says "find papers", "related work", "literature review", "what does this paper say", or needs to understand academic papers.

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。

Run an end-to-end workflow that chains `research-refine` and `experiment-plan`. Use when the user wants a one-shot pipeline from vague research direction to focused final proposal plus detailed experiment roadmap, or asks to "串起来", build a pipeline, do it end-to-end, or generate both the method and experiment plan together.

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。

Workflow 1: Full idea discovery pipeline. Orchestrates research-lit → idea-creator → novelty-check → research-review to go from a broad research direction to validated, pilot-tested ideas. Use when user says \"找idea全流程\", \"idea discovery pipeline\", \"从零开始找方向\", or wants the complete idea exploration workflow.

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 patent databases and academic literature for prior art relevant to an invention. Use when user says "现有技术检索", "prior art search", "专利检索", "check patents", or wants to find relevant prior art.

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 published venue papers (IEEE, ACM, Springer, etc.) via Semantic Scholar API. Complements /arxiv (preprints) with citation counts, venue metadata, and TLDR. Use when user says "search semantic scholar", "find IEEE papers", "find journal papers", "venue papers", "citation search", or wants published literature beyond arXiv preprints.

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 and rank research ideas given a broad direction. Use when user says "找idea", "brainstorm ideas", "generate research ideas", "what can we work on", or wants to explore a research area for publishable directions.

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, download, and summarize academic papers from arXiv. Use when user says "search arxiv", "download paper", "fetch arxiv", "arxiv search", "get paper pdf", or wants to find and save papers from arXiv to the local paper library.

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 academic papers via OpenAlex API for open citation data, institutional affiliations, and funding information. Use when user says "openalex search", "search openalex", "open citation graph", or wants comprehensive academic metadata beyond arXiv/Semantic Scholar.

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。

Control LLM output with regex and grammars, guarantee valid JSON/XML/code generation, enforce structured formats, and build multi-step workflows with Guidance - Microsoft Research's constrained generation framework

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。

OpenAI's model connecting vision and language. Enables zero-shot image classification, image-text matching, and cross-modal retrieval. Trained on 400M image-text pairs. Use for image search, content moderation, or vision-language tasks without fine-tuning. Best for general-purpose image understanding.

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。

Write publication-ready ML/AI papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM. Use when drafting papers from research repos, structuring arguments, verifying citations, or preparing camera-ready submissions. For systems venues (OSDI, NSDI, ASPLOS, SOSP), use systems-paper-writing instead.

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。

Framework for state-of-the-art sentence, text, and image embeddings. Provides 5000+ pre-trained models for semantic similarity, clustering, and retrieval. Supports multilingual, domain-specific, and multimodal models. Use for generating embeddings for RAG, semantic search, or similarity tasks. Best for production embedding generation.

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。