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Found 26 Skills
Comprehensive scientific literature search across PubMed, arXiv, bioRxiv, medRxiv. Natural language queries powered by Valyu semantic search.
General-purpose deep research with multi-source synthesis and confidence-scored findings. Auto-classifies complexity from quick lookup to exhaustive investigation. Cross-validates across independent sources with anti-hallucination verification, contradiction detection, and bias auditing. Produces synthesis products with evidence chains and provenance. Resumable journal sessions. Use when investigating technical topics, academic questions, market analysis, competitive intelligence, architecture decisions, technology evaluation, fact-checking, literature review, or trend analysis. NOT for code review (use honest-review), strategic decisions (use wargame), multi-perspective debate (use host-panel), or simple factual Q&A answerable in one search.
Search arXiv for academic papers. Use when users want to find research papers, preprints, or academic articles on any topic. Supports filtering by date, category, and author.
Search arXiv physics, math, and computer science preprints using natural language queries. Powered by Valyu semantic search.
This skill should be used when user asks to "search for papers", "find research papers", "search arXiv", "search PubMed", "find academic papers", "search IEEE", "search Scopus", or "look up scientific literature".
Web search, content extraction, crawling, and research capabilities using Tavily API
Conduct exhaustive, citation-rich research on any topic using all available tools: web search, browser automation, documentation APIs, and codebase exploration. Use when asked to "research X", "find out about Y", "investigate Z", "deep dive into...", "what's the current state of...", "compare options for...", "fact-check this...", or any request requiring comprehensive, accurate information from multiple sources. Prioritizes accuracy over speed, cross-references claims across sources, identifies conflicts, and provides full citations. Outputs structured findings with confidence levels and source quality assessments.
Search for scientific papers, preprints, and publications on arXiv. Extract metadata, abstracts, and download full-text PDFs or HTML versions of papers. Use when the user asks to find research papers, literature, or specific arXiv IDs.
ONLY use when user explicitly says 'deep research', 'exhaustive', 'comprehensive report', or 'thorough investigation'. Slower and more expensive than parallel-web-search. For normal research/lookup requests, use parallel-web-search instead.
Search academic papers across arXiv, PubMed, Semantic Scholar, bioRxiv, medRxiv, Google Scholar, and more. Get BibTeX citations, download PDFs, analyze citation networks. Use for literature reviews, finding papers, and academic research.
General-purpose web search using DuckDuckGo and AI-synthesized search engines. Use this skill for web searches, current information, fact-checking, news, and research on any topic where live internet data is needed. Supports all languages. Three modes: fast web results, AI-synthesized answers (IAsk.ai, great for deep questions and academic research), and Monica AI synthesis. Trigger on: "search for", "look up", "find information about", "what is the latest", "search the web", "find out about", "what happened with", "current status of", "recent news", "is X still true", "查一下", "搜索", "查资料", "上网查", "検索して", "調べて", any question requiring real-time or post-training web data. Do NOT trigger for: code exploration, local file analysis, codebase-internal questions, or well-established facts fully covered by training knowledge. Note: if the `agent-reach` skill is also available, prefer `ddg-search` for pure web search tasks; prefer `agent-reach` when the task involves social platforms (Twitter, Reddit, YouTube, WeChat, Bilibili, etc.) or platform-specific APIs.
One industry → One ecological terrain map card (PNG). Built on the reference frame theory from *A Thousand Brains*: Lay out an industry as an overlookable 'ecological terrain' — value flows through the landscape like a river, then mark two spots on the terrain: 'Bottlenecks' (narrow passes/dams where flow/capacity constricts) and 'Value Capture Points' (treasure piles where profits accumulate). The terrain reveals power structures at a glance: Places that control flow are often not where money accumulates. Includes base rates (scales) for three key indicators + three 'Big Questions' (frontier topics). Powered by deep real-network research, maps are AI-generated (default -a Animal Crossing warm cute style, optional -c pixel+cyber style), with Jigang Ji standing on the terrain overlooking. Use when user says '行业地图', '产业地图', '生态地形图', '画一下这个行业', 'industry map', 'map this industry', '行业版图', '产业链地图', '/ljg-map', or provides an industry/domain name wanting its terrain mapped. Style: Default -a Animal Crossing, add -c for cyber style. NOT FOR: Ranked search for generators in a domain (use ljg-rank), book dissection (use ljg-book), individual project investment analysis (use ljg-invest), deep dive into a single concept (use ljg-think).