調査、論文、教育、資格学習（4,132 件）
概要と使いどころ
Initialise a project for knowledge base use. Appends the [Knowledge Base] section to the project's CLAUDE.md, creates the library/ directory structure, optionally seeds with three example library files from the Agentic SDLC research, and reports next steps. Run once after installing sdlc-knowledge-base.
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 the project knowledge base. Wraps the research-librarian agent. The librarian reads the shelf-index, identifies the 2-4 most relevant library files for the question, deep-reads only those, and returns structured evidence with citations. Stateless — reads the index fresh on every query.
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 with cross-verification and source tiering. Use when investigating technologies, comparing tools, fact-checking claims, evaluating architectures, or any task requiring verified information. Triggers on "조사해줘", "리서치", "research", "investigate", "fact-check", "비교 분석", "검증해줘".
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。
Identify the source of an image or video frame — TV show episode, movie scene, geographic location, or original publication. This skill should be used when the user asks to identify where an image is from, trace a screenshot back to its source, geolocate a photo, find what show or movie a frame is from, or do a reverse image search. Chains Google Vision, Picarta geolocation, and Gemini in parallel with graceful degradation. Triggers on: reverse image search, identify source, what show is this, where was this taken, trace image, identify video, what movie, which episode, geolocate photo, image source.
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Investigate datasets and resolve entities using OpenPlanter methodology — cross-reference heterogeneous sources, build Admiralty/ACH confidence-tiered evidence chains, and apply OSINT tradecraft. Triggers on entity resolution, cross-reference datasets, evidence chain, OSINT investigation, structured investigation.
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。
Unified web and social media search across 5 providers (Brave, Tavily, Xpoz, Exa, Firecrawl). Auto-routes queries to the best API, supports parallel multi-provider search with deduplication, AI-generated answers, and social media search. Triggers on web search, find news, search Twitter, search Reddit, social media search, multi-provider search, omnisearch, research news, OSINT, search for, look up, find information about.
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 the web and fetch page contents with Keenable AI — web search, page extraction, point-in-time queries, prompt-driven content extraction. Use when searching the web for current information, fetching webpage contents, extracting specific data from URLs, or researching topics with citations. Triggers on: web search, search the web, fetch page, read URL, find pages about, current information, Keenable, keen search, research with sources, look up, latest news, find information, check online, what is, who is.
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。
Scrape web pages to clean markdown using Firecrawl v2 — handles JS-heavy pages, site crawls, URL mapping, document parsing (PDF/DOCX/XLSX), LLM-powered extraction, autonomous agent scraping, and post-scrape browser interaction (Interact API). Free keyless mode available for search/scrape/parse/interact (no API key needed). Prefer over WebFetch for quality and completeness. Triggers on scrape URL, fetch page, crawl site, extract content, parse document, web to markdown, DeepWiki, Firecrawl.
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。
Academic research skill for Biblical Hebrew, Semitic linguistics, cuneiform studies, and comparative Ancient Near Eastern research. Provides Sefaria API for Hebrew Bible, CDLI/ORACC for cuneiform databases, and web discovery via Omnisearch, Exa, Firecrawl, and Obscura for finding scholarly sources across JSTOR, Perseus, Persée, Google Scholar, and academia.edu. Triggers on Hebrew quotes, cuneiform, Sefaria, ANE research, Minoan, search for scholarship, find papers, literature review, scholarly search, academic search, Genesis/Tehom, Ugaritic, Talmudic sources, extract from PDF, OCR academic.
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, build literature reviews, and synthesize research findings — combines Exa MCP (research_paper category, arxiv filtering) with arxiv-mcp-server for paper discovery, download, and deep analysis. Triggers on academic paper, literature review, research synthesis, arxiv, find papers, scholarly search.
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 the web with Exa AI — neural search, content extraction, similar page discovery, quick research with citations, and async pro research with structured output. Covers all Exa endpoints (/search, /contents, /findSimilar, /answer, /research/v0/tasks). Triggers on web search, find pages, similar pages, research with citations, Exa, neural search.
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。
Scrape pages locally with anti-bot bypass, TLS impersonation, and adaptive element tracking — no API keys, no cloud. Handles Cloudflare protection, CSS/XPath element extraction, and survives site redesigns. Complements firecrawl (cloud) with 100% local execution. Triggers on Cloudflare bypass, anti-bot scraping, stealth fetch, local scraping, Scrapling.
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。
Scaffold and run Karpathy-style autoresearch loops in any git repo. This skill should be used when setting up autonomous code improvement, generating adversarial eval harnesses, running hypothesis-implement-eval-keep/discard loops, or checking autoresearch progress. Triggers on "autoresearch", "autonomous improvement", "eval loop", "hypothesis loop", "self-improvement loop".
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。
CORE learning workflow — use this whenever the user has a source note open (paper, post, book, lecture, course, clipping) and wants to extract knowledge, understand what they just read, or build it into their vault. Triggers on "process this note", "process this paper", "extract concepts", "what can I learn from this", "atomize this", "add this to my vault", "what's important here", or when the user shares a note and asks for help understanding it. Do NOT wait for an explicit /process command — if the user is engaging with a source note and wants to go deeper, this skill applies.
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 a topic and create a new note in the vault. Use this skill whenever the user wants to learn about a topic they don't know yet, investigate a question, explore an idea, or asks "what is X", "research X", "tell me about X", "I want to understand X", "look into X". Also triggers on /research. This is for BROAD research (web + vault) — for academic papers specifically, use /paper-discover 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。
Use when searching for academic papers related to a topic, finding papers similar to one already in the vault, or discovering research gaps. Triggers on "find papers", "related papers", "paper search", "literature", "what papers should I read about X".
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, iterative, multi-source research that explores a topic from multiple perspectives, detects contradictions, and produces a comprehensive vault note with fact-level citations and a confidence map. Use this skill whenever the user says /deep-research, "deep research X", "research X thoroughly", "investigate X deeply", "I need to really understand X", or wants research that goes beyond a quick web search. Also use when the user wants to understand a complex, contested, or multi-faceted topic, compare competing approaches with evidence, or build a comprehensive mental model they can trust for decisions. This is heavier than /research — it searches web, academic papers, Reddit, and the vault, then loops through exploration and critique rounds until the evidence base is solid. When in doubt between /research and /deep-research, prefer this one if the topic is complex, contested, or the user wants depth over speed.
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 sources need to be converted into a claim ledger with confidence levels.
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。
Agent Brain /brain-research: the decision depends on external evidence or unfamiliar domain 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。
Agent Brain /brain-brief: after intake, research, and grill have enough signal.
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 repeated wins or failures should become durable memory, wiki, or skill updates.
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。
Agent Brain /brain-learn: after repeated success/failure, a tricky fix, or a shipped 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。
Specialized research and analysis prompt methodology for Claude. Provides 11 tested approaches (3 identity, 4 reasoning, 4 output) for data analysis, policy research, systematic evidence review, investigative research, and research-specific deliverables. Use when building prompts for quantitative data interpretation, evidence-based policy recommendations, literature reviews, causal analysis, hypothesis-driven investigation, or briefing documents. Trigger on: "prompt for data analysis," "research prompt," "policy brief prompt," "literature review prompt," "prompt for investigating," "systematic review prompt," "build a prompt for evidence synthesis," "causal analysis prompt," "briefing document prompt." Also use when user describes a research or analytical task and needs a structured Claude prompt for it. Do NOT use for evaluating existing prompts (use rootnode-prompt-validation if available) or auditing Claude Projects (use rootnode-project-audit if available).
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。
为中文微信公众号文章分析内容并生成清晰易懂、真实 3D 毛毡质感且图文一体的头条长封面、1:1 分享页封面与正文配图，同时给出每张正文图应插在哪个原句之后。用于用户提供文章、Markdown 或正文，并要求“公众号封面”“分享封面”“方形封面”“毛毡配图”“文章插图”“为正文配图”“只做封面”“生成 N 张配图”“推荐配图数量”等任务；未提供文章标题时默认根据核心命题生成合适的封面文字，正文图未指定画幅时默认 16:9，也支持用户明确指定 4:3 或 3:4，并使用少量毛毡文字帮助单图理解；适配方法论、教程、专业干货、商业科技、情感叙事、个人成长、生活方式、教育与母婴等内容。
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。