「search」の検索結果

Scientific research engine for hypothesis testing, literature gap analysis, experimental validation, and data-driven discovery. Enforces adversarial review (Reviewer 2), 32 quality gates, tree search over hypotheses, confounder harness for quantitative claims, and serendipity detection. TRIGGER when: user asks to analyze scientific data, test hypotheses, validate findings, search for research gaps, design experiments, or investigate results. DO NOT TRIGGER when: pure code review, documentation writing, devops tasks, general conversation, or non-scientific data transformation.

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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.

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Systematically document research findings, competitive analysis, market trends, and user insights in Notion. Build searchable research repository for data-driven decisions.

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Systematic literature review methodology for social science research. Use when conducting systematic reviews, research synthesis, meta-analyses, scoping reviews, or comprehensive literature searches across economics, political science, sociology, education, public health, and development. Produces structured notebook cells with search strategy, evidence table, thematic synthesis, and gap analysis.

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Research complex questions and synthesize relevant evidence into a clear, cited answer. Useful for competitive and market analysis, company research, prospect discovery, enrichment, historical comparisons, and evaluating conflicting claims. Adapt the depth and format to the question; use when a focused search or single-page read is insufficient.

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Research process for comparing frontier harnesses (Claude Code, Codex, OpenClaw, autoresearch, Prime Agent) with the original/upstream implementation and performing GAP analysis before feature implementation. Triggered by "research" ("리서치"), "gap", "frontier", "harness", "case study" ("사례 조사"), "pattern exploration" ("패턴 탐색"), "comparative analysis" ("비교 분석") keywords.

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Padrões especializados para implementação de busca Algolia, estratégias de indexação, React InstantSearch e ajuste de relevância. Use quando: adicionar busca, algolia, instantsearch, search api, funcionalidade de busca.

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Mecanismo de busca de similaridade vetorial de alto desempenho para RAG e busca semântica. Use ao construir sistemas RAG em produção que exigem busca de vizinhos mais próximos rápida, busca híbrida com filtragem ou armazenamento vetorial escalável com desempenho impulsionado por Rust.

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Route ordinary public-web information tasks to the correct Tavily CLI operation. Use when the task concerns publicly accessible webpages and needs web discovery, clean extraction, URL mapping, same-site crawling, or public-web-only research, but the exact Tavily operation is not yet clear or several operations must be sequenced. Prefer the specific leaf skill when intent is clear: tavily-search for discovery without a URL, tavily-extract for known URLs, tavily-map for URL/site-structure discovery, tavily-crawl for content from many pages on one site, tavily-research for cited multi-source synthesis, and tavily-dynamic-search for programmatic filtering with context isolation. Do not use for named social/community/media/career/code platforms, login or cookie-dependent content, platform-native discussions, or cross-platform collection; use Agent Reach there. Do not use for local files, Git operations, deployments, or ordinary code editing.

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Produce comprehensive synthesis with explicit citations from multiple ordinary public-web sources via the Tavily CLI. Use for detailed reports, comparisons, market or literature research, and questions whose answer requires multi-source web evidence rather than a quick lookup. Do not use for simple discovery (tavily-search), one known URL (tavily-extract), one-site URL discovery or bulk extraction (tavily-map/crawl), or research centered on named social, community, career, code, media, authenticated, or cross-platform sources (Agent Reach). Takes 30-120 seconds.

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MUST USE when user wants to 调研/research/搜索/search/查/找/look up anything on the internet — e.g. 全网调研 X / 帮我调研一下 X / 查一下 X / 搜搜 X / 看看大家怎么评价 X / X 上有什么讨论 / research this topic。 Also MUST USE when user mentions any platform or shares any URL/链接: 小红书/xiaohongshu/xhs, Twitter/推特/X, B站/bilibili, Reddit, V2EX, LinkedIn/领英/招聘/求职/jobs, YouTube, 小宇宙播客, 雪球/股票行情, RSS feeds, or a non-GitHub web URL. Multi-platform, multi-backend routing (OpenCLI / per-platform CLIs / APIs). Zero config for 6 channels. Run `agent-reach doctor --json` to see which backend serves each platform right now. NOT for: GitHub 相关操作（包括 GitHub URL、代码或仓库搜索、Issue、PR、 Actions 和 Release），由 github-cli 处理；写报告/数据分析/翻译等内容加工 （本 skill 只负责从互联网获取内容）；发帖/评论/点赞等写操作；已有专门 skill 的平台（先用专门 skill）。 【路由方式】SKILL.md 包含路由表和常用命令，复杂场景需按需阅读对应分类的 references/*.md。 分类：search / social (小红书/推特/B站/V2EX/Reddit) / career(LinkedIn) / web(网页/文章/RSS) / video(YouTube/B站/播客)。

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Multi-source deep research using firecrawl and exa MCPs. Searches the web, synthesizes findings, and delivers cited reports with source attribution. Use when the user wants thorough research on any topic with evidence and citations.

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Use when the user asks for deep or academic research — a literature review, PRISMA systematic review or meta-analysis, fact-check, evidence synthesis, APA 7 research report, or Socratic guidance to sharpen a vague research question. Runs a 13-agent pipeline with full, quick, review, lit-review, fact-check, socratic, and systematic-review modes.

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Solves complex, open-ended problems using an evolutionary search mechanism inspired by genetic algorithms. Generates a diverse population of candidate answers, scores them against a rubric, then iteratively applies selection, crossover, and mutation to breed progressively better solutions. Use this skill whenever the user wants to explore a solution space deeply, asks for the "best" answer to a subjective or multi-dimensional problem, wants to evaluate competing approaches and distill the strongest, or uses any of these triggers: "evolutionary search", "genetic algorithm", "evolve an answer", "breed solutions", "population-based search", or phrases like "give me multiple approaches and refine the best one". Also trigger when the problem is complex, open-ended, or has no obvious single correct answer and the user wants a high-quality, well-explored result, not just a quick response.

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Search, scrape, and interact with the web via the Firecrawl CLI. Use this skill whenever the user wants to search the web, find articles, research a topic, look something up online, scrape a webpage, grab content from a URL, get data from a website, crawl documentation, download a site, or interact with pages that need clicks or logins. Also use when they say "fetch this page", "pull the content from", "get the page at https://", or reference external websites. This provides real-time web search with full page content and interact capabilities — beyond what Grok can do natively with built-in tools. Do NOT trigger for local file operations, git commands, deployments, or code editing tasks.

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Deep research workflow that starts from a GitHub repo URL/slug, pulls upstream intel, then expands to Reddit + open web for community reception. Use whenever Ahmad gives a GitHub link and asks to understand it, see updates, audit the community, or compose a report. Trigger phrases include "research this repo", "report on this github", "what's happening upstream", "community reception", "compose a report on <repo>", and any message that contains a github.com URL plus a research/report ask.

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Choose the design and the numbers a research run can honestly claim — write the structured METHOD RECORD (databases, date of access, search string, criteria, screening counts) that r0 validates, pick the claim strength a design can actually carry, record a statistic as data rather than prose, route to the reporting guideline the design owes, and decide what to preregister. Use when a run's question, design, search or statistics have to be settled before the writing, or when a claim needs a strength or a number attached to it.

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Semantic + keyword search and connection-discovery across the user's own Apple Notes via the apple-notes MCP server. Use when the user wants to find, recall, or synthesize something from their notes, or surface non-obvious bridges/related notes. macOS, on-device.

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Full-text keyword search across every conversation at once (Telegram, Facebook, ChatGPT, Claude, notes, transcripts) over a local BM25/FTS5 catalog: instant, zero tokens, with snippets and chat-title hits. The exact-words lane, complementary to semantic search. Triggers: "/search <words>", "where did I write about <X>".

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Researches Reddit using a brand's Brand DNA to find promotable pain-point discussions, target subreddits, and real user search language. Produces a prioritized Reddit opportunity list for content seeding, helpful replies, and prompt research inspiration.

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Send one research question to as many independent LLMs as possible at once, each in its strongest reasoning mode with proof of that mode, then synthesize. Floor of 3 models, quorum of 4; late answers are collected later. Use for high-stakes questions where one model's view is not enough. Triggers: /hyper, hyper research, ask every LLM, max fan-out research.

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- Reverse image search across Yandex, Google Lens, Bing Visual Search, TinEye and Baidu to find where a picture came from and who published… Use when reverse image searching, identifying a photo, face, logo, product, uniform or building, tracing a profile picture or avatar, finding the oldest copy of an image, checking whether a photo is stock or a repost, or reverse-searching a video by keyframes

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特許分析・知的財産戦略支援スキル。先行技術調査、特許性評価、特許ポートフォリオ分析、 侵害リスク評価、ライセンス戦略策定を支援。特許出願戦略の立案から権利化まで包括的にサポート。 Use when conducting prior art searches, evaluating patentability, analyzing patent portfolios, assessing infringement risks, or developing IP strategies. Triggers: "patent search", "prior art", "特許調査", "patentability", "FTO", "特許ポートフォリオ", "IP strategy", "patent landscape".

Search the live web via Perplexity Search API. Use when you need current documentation, release notes, vendor pages, news, domain-constrained web search, or date/recency filtering. Not for local codebase search or stable docs already in context.

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。