4,977 件 ・ 関連度順
概要と使いどころ
Research a prospect then draft personalized outreach. Uses web research by default, supercharged with enrichment and CRM. Trigger with "draft outreach to [person/company]", "write cold email to [prospect]", "reach out to [name]".
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。
Prepare for a sales call with account context, attendee research, and suggested agenda. Works standalone with user input and web research, supercharged when you connect your CRM, email, chat, or transcripts. Trigger with "prep me for my call with [company]", "I'm meeting with [company] prep me", "call prep [company]", or "get me ready for [meeting]".
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。
Assists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on each section. Transforms your writing process from solo effort to collaborative partnership.
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 professional company tear sheets using S&P Capital IQ data via the Kensho LLM-ready API MCP server. Use this skill whenever the user asks for a tear sheet, company one-pager, company profile, fact sheet, company snapshot, or company overview document — especially when they mention a specific company name or ticker. Also trigger when users ask for equity research summaries, M&A company profiles, corporate development target profiles, sales/BD meeting prep documents, or any concise single-company financial summary. This skill supports four audience types: equity research, investment banking/M&A, corporate development, and sales/business development. If the user doesn't specify an audience, ask. Works for both public and private companies.
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。
Conduct comprehensive market research including competitive analysis, customer persona development, market sizing (TAM/SAM/SOM), survey design, and trend analysis. Synthesize insights for strategic decision-making.
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 institutional-quality equity research initiation reports through a 5-task workflow. Tasks must be executed individually with verified prerequisites - (1) company research, (2) financial modeling, (3) valuation analysis, (4) chart generation, (5) final report assembly. Each task produces specific deliverables (markdown docs, Excel models, charts, or DOCX reports). Tasks 3-5 have dependencies on earlier tasks.
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。
Multi-round deep research on any GitHub repo via API.
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。
Systematic multi-angle web research methodology.
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 paid-ad presence, messaging, creative, formats, landing pages, keyword and auction signals, transparent ad libraries, and strategic gaps across supported platforms. Use for competitor ads, ad libraries, ad spy, competitive PPC analysis, competitor creative, Google Ads Transparency, Meta Ad Library, or paid-media competitor research.
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. Trigger on: competitors, competitive analysis, gap analysis, feature comparison, market research, what are we missing, who are our competitors, pricing comparison, market positioning.
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 wants a complete, publication-grade research paper on a specific topic — produces 200+ real citations, 4–8 publication-grade figures, and 7 sections of substantive prose compiled to PDF in one pass. No skeleton stage.
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 has a research question and needs a complete experiment package — design document, runnable code, results (measured or simulated with honest provenance), publication-grade figures, structured report. Single-stage, no Python runtime.
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 wants a comprehensive literature survey on a specific research topic. Outputs a complete PDF survey (6–20 pages, 60+ real citations, 100+ recommended) with LaTeX source, topic-specific publication figures, and a classified literature table. Single-stage, no Python runtime.
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 X data with Xquik, the world's fastest and cheapest X Twitter scraper service with the most complete X data. Use only when the request or active context identifies X or Twitter. Use for tweet search, tweet lookup, user discovery, profile timelines, threads, followers, trends, exports, or monitoring plans. Do not use for generic posts, other networks, or local dataset analysis that needs no X retrieval. Keep reads bounded. Require explicit confirmation before private reads, writes, persistent resources, or bulk jobs. Not affiliated with X Corp.
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。
The Auto 档 scenario — a soft-plan orchestrator for a complete fundamental equity research thesis: understand → financials → valuation → synthesize. The body is a soft plan (stages), not a rigid DAG; correctness is enforced by each referenced skill's own requires: preconditions, never by this plan's rigidity (Q2).
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。
Institutional-grade equity research skills for AI agents. 80 Claude-type skills across 14 verticals (equity-research-core, models-and-pitches, bio-pharm, scenarios, quantitative-analysis, idea-generation, options-derivatives, business-intelligence, industry-analysis, macro-strategy, portfolio-strategy, technical-analysis, risk-and-psychology, trading-as-business) powered by agentii.ai's agent-use-ready SEC filing data plane — SEC filings and 15K+ earnings call transcripts, 15.99M XBRL facts, and company profiles for 1,146+ US-public-equity tickers. Features the three-layer retrieval protocol (Document Discovery → Page Map → Deep Read, with deep-outline escalation) — measured, not asserted: 97.5% saved against a sequential read, and the page map itself is 10.0% of one (spec 062 T030, 2026-09-23) — server-side parallel multi-period search via search_cross_period, a full Excel/PPT generation pipeline with 3-tier office backend support, and the spec-046 governance layer (constitution, thesis and single-skill modes, mechanical gates, and a template-owned disclaimer on generated reports).
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 videos, analyze channel profiles, track live streams, and research content engagement on WeChat Channels (Video Accounts). Covers video search, channel profiling, live stream monitoring, comment analysis, and content collections.
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 podcasts, episodes, and audio content by searching YouTube (where most podcasts crosspost), web sources, and transcript databases. Discover relevant shows, track guest appearances, and analyze topic coverage in the podcast ecosystem.
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。
Conduct comprehensive market research combining web search, academic sources, news coverage, and industry data. Produces market sizing signals, competitive landscape overviews, trend analysis, and evidence-backed market opportunity assessments.
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 npm packages — download stats, dependencies, maintainers, version history, and security advisories. Useful for technology due diligence, dependency auditing, and evaluating package reliability before adoption.
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 and collect social proof — testimonials, case studies, user reviews, social mentions, and community endorsements across platforms. Useful for marketing teams building trust content, landing pages, and sales collateral from authentic customer voices.
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 potential leads with verified contact information, professional backgrounds, company context, and social presence. Combines LinkedIn profiling, email verification, company enrichment, and social signals for sales-ready prospect intelligence.
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 potential partners by analyzing company profiles, product fit, market positioning, team background, and mutual connections. Combines firmographic data, content analysis, and social signals for partnership qualification and relationship mapping.
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。
Portable multi-source research with cross-source validation and an offline evidence ledger. Use for fact-checking, comprehensive research, or any question requiring multiple independent perspectives; work with the host agent's search tools and optionally add SandBase Tavily, Exa, Scholar, and Cloudsway 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。