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概要と使いどころ
Use when the user asks Codex to research, find learning materials, process "素材：" links, "请你读" / "精读" a material, build a material radar, or use multi-source information retrieval for career learning and Agent infra tracking. Do not use the career/Agent-infra routing bias for user-directed `整理笔记` into a named note.
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 an explicitly requested Marin question or coordinate a multi-session experiment; find prior work, assess evidence, and record results in the task's existing durable surface.
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。
External research workflow for docs, web, APIs - NOT codebase exploration
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 agent for external documentation, best practices, and library APIs via MCP tools
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, analyze, and prioritize keywords for SEO and GEO content strategies from a seed keyword or niche. Identifies high-value opportunities based on search volume, competition, intent, and business relevance. Generates topic clusters. For building a dated editorial calendar from your own Search Console data, use `content-planner` instead — this skill is seed-driven keyword discovery, not calendar scheduling. Use when asked to "find keywords", "keyword research", "keyword analysis", "search volume", "keyword difficulty", "content ideas from a seed", or any keyword discovery task.
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 to evaluate a creator, influencer, or brand audience using public profile signals, TikTok audience demographics, follower/following data, comments, geography, language, and content fit. Helps judge sponsorship and market fit.
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 to turn public social videos, transcripts, posts, or creator research into reusable content assets such as LinkedIn posts, X threads, short-form scripts, newsletters, blog outlines, carousels, or content calendars.
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 to find creators, influencers, affiliates, or social accounts in a niche for outreach, partnerships, sponsorships, UGC, seeding, or competitive research. Produces scored prospect lists from public social 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。
Deep web research for VCO: multi-hop search+browse+extract with an auditable action trace and a structured report (WebThinker-style).
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 competitive research proposals for NSF, NIH, DOE, DARPA, and Taiwan NSTC. Agency-specific formatting, review criteria, budget preparation, broader impacts, significance statements, innovation narratives, and compliance with submission requirements.
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 slide decks and presentations for research talks. Use this for making PowerPoint slides, conference presentations, seminar talks, research presentations, thesis defense slides, or any scientific talk. Provides slide structure, design templates, timing guidance, and visual validation. Works with PowerPoint and LaTeX Beamer.
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。
Open-ended scientific ideation partner. Use for research gaps, mechanism exploration, interdisciplinary connections, assumptions, possible research directions, and lightweight literature matrix or A+B paper-combination idea mapping. For structured testable hypotheses and validation plans, use hypothesis-generation 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。
Query and analyze scholarly literature using the OpenAlex database. This skill should be used when searching for academic papers, analyzing research trends, finding works by authors or institutions, tracking citations, discovering open access publications, or conducting bibliometric analysis across 240M+ scholarly works. Use for literature searches, research output analysis, citation analysis, and academic database queries.
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 research posters using HTML/CSS that can be exported to PDF or PPTX. Use this skill ONLY when the user explicitly requests PowerPoint/PPTX poster format. For standard research posters, use latex-posters instead. This skill provides modern web-based poster design with responsive layouts and easy visual integration.
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 FRED (Federal Reserve Economic Data) API for 800,000+ economic time series from 100+ sources. Access GDP, unemployment, inflation, interest rates, exchange rates, housing, and regional data. Use for macroeconomic analysis, financial research, policy studies, economic forecasting, and academic research requiring U.S. and international economic indicators.
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 comprehensive market research reports and industry/competitive analysis in the style of top consulting firms. Use for market sizing, competitive landscape, market entry, investment thesis, strategic recommendations, and consulting-style business reports. Do not use for scientific reports, paper writing, LaTeX submission/PDF builds, EDGAR/FRED/Treasury/Data Commons data retrieval, or biomedical literature evidence work.
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 clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug development, clinical research, and evidence synthesis.
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。
Ensure thorough validation, error recovery, and transparent reasoning in research tasks with multiple tool calls
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 explicitly requests research with Baizhi Agent Toolkit. Discover the connected MCP tools and their current schemas, agree a request budget, and produce a sourced result without exposing credentials.
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 browser-grounded social research without remote account mutations through Jev Social when a user wants posts, profiles, comments, video evidence, or a source-linked report from Instagram, TikTok, or LinkedIn and the local socai CLI reports support for that platform. Do not use for publishing, engagement actions, or general web 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。
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。
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。
Get research-backed architecture advice for your knowledge system. Describe your use case, constraints, and goals — get specific recommendations grounded in TFT research with rationale for each decision. Triggers on "/recommend", "what would you recommend", "architecture advice", "knowledge system for".
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。