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概要と使いどころ
Extracts text and metadata from 1000+ file formats using Apache Tika server REST API. Handles PDF OCR via Tesseract integration, Office document parsing, and email archive extraction with MIME detection.
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。
Wraps Apache Tika Server REST API for extracting structured text from PDFs, DOCX, PPTX, and 1,200+ file formats. Outputs clean markdown with metadata preservation using Tika /rmeta/text endpoint and recursive parsing mode.
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。
Extracts text and metadata from 1400+ file formats via Apache Tika Server REST API. Handles PDF, DOCX, PPTX, email archives, and embedded document extraction with MIME type detection.
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 publish or schedule a LinkedIn post through Publora: text, a multi-image grid, a video, a PDF document, or @mentions. Not for analytics, reactions, comments or reshares (use linkedin-analytics), and not for other platforms.
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 research-paper figure Skill Factory: build, patch, package, or use reusable specialized paper-figure-making skills from lawful literature/corpus evidence. Generated skills must use a specialized-skill-first workflow, full-feasible local PDF coverage where available, startup-plan-only first replies, target-paper candidate/final image isolation, mandatory image-embedded visual-structure explanation, mandatory non-target concept/modeling example display for abstract visual decisions, saved subtype/style illustration atlases, ChatGPT web Create image / ChatGPT Images 2.0 rendering, Codex $imagegen-first rendering, sample-image transfer rules, all-step/current-position state footers, and a mandatory first-round diverse candidate board followed by P6b/P6c paper-local best-practice optimization before final prompt construction.
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。
将量化分析或已有 JPG/PNG、HTML、PDF 发布为 Quant Buddy 可分享活页或实时看板，并支持创建、更新、复用、验收和公开链接交付。适用于个股画像、估值财务、指数异动、多因子筛选、商品日报、模板、分享壳及卡片等页面。 用户提供 QuantBuddy 活页 URL 并要求解读时也使用。显式调用 /quant-buddy-view、/qbv、qbv 或 QBV，且请求并非纯咨询、代码维护或文档解释时，默认按可分享活页任务处理。 输入可唯一识别的 A 股名称、简称或代码，或简单要求单股综合分析（如“贵州茅台”“600519”“分析一下贵州茅台”）均默认请求个股快页；先通过 QBS 验证并回复完整个股分析，再同轮 new_asset_page，无需用户补说“生成页面”。 WebAgent 宿主要求金融问题统一交付问答与活页时，一次性行情、涨跌幅、估值、概念解释和口语近况问题也在 QBS 首答后交接本技能。无此宿主约定时一次性问题由 QBS 回答；复盘、监控、画图、回测、K线等操作仍默认有活页意图。明确不要网页或只回复文字时不建页。
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。
Simulate rigorous, fair peer review on a paper — in two modes. (A) Red-team YOUR OWN draft before submission to predict the reviews you'll get and get a fix list. (B) Review SOMEONE ELSE'S paper when you're an assigned reviewer or helping your advisor — produce a fair, venue-formatted, submission-ready review. Use whenever the user gives a paper (PDF, .tex, .md, arXiv link, or pasted text) and wants to predict reviews, find weaknesses before reviewers do, stress-test a submission, OR write a real review of another paper. Grounded in official NeurIPS/ICLR/ACL reviewer guidelines; every criticism pinned to a location, and checked against ACL's H1–H17 list of illegitimate critiques. 两种模式:审自己的稿(投稿前红队)/ 审别人的稿(当审稿人或帮导师),按会议官方标准评,绝不脑补、绝不发不正当批评。
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 for visual explanations and documents. Triggers: diagrams, charts, interactive models, HTML reports, infographics, 시각화, 그려줘, 문서 만들어줘, 보고서, PDF 생성.
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。
Scores and strengthens startup pitch decks (pre-seed through Series A) against 35 investor-grade criteria grounded in Sequoia, DocSend, YC, a16z, and Carta data. Use when the user has shared a pitch deck (PDF, PPTX, markdown, pasted slide text, or a link to one) and asks for a review, score, feedback, or critique. A full review takes about 15–25 minutes, 40 or more for a long investor deck, so for a general pitch question with no deck, answer briefly in chat and offer the review instead of starting it. When it runs, score with the rubric, never with deck advice from memory.
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。
Convert files to Markdown using Microsoft's MarkItDown library
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。
Operating guide for construction project documents — load before reading drawings, specs, schedules, RFIs, submittals or bids. Data-access rules (never read PDFs directly; rasterize first), AgentCM graph-guided vision, drawing and cross-reference conventions, document precedence. Triggers: 'construction project', 'drawings', 'specs', 'sheet', 'RFI', 'submittal'.
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。
Extract data from subcontractor bid PDFs and produce a comparison spreadsheet. Feeds into /bid-evaluator. Triggers: 'tabulate bids', 'bid comparison', 'compare bids', 'buyout analysis', 'bid tab'.
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 search Turkish academic journals on DergiPark (keyword or advanced field search by title/author/abstract/DOI/ORCID/year/etc.), read a DergiPark article PDF as text, or extract an article's references — drives the user's own Chrome (no CAPTCHA solving needed) by injecting JavaScript.
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。
Hunt Server-Side Template Injection (SSTI) in Jinja2, Twig, Freemarker, Velocity, Smarty, ERB, Handlebars, Mustache, and Spring (SpEL). Use when input is reflected in a way that suggests template rendering — error pages, email templates, PDF generators, dynamic content systems.
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。
Orchestrate the full PaperOrchestra (Song et al., 2026, arXiv:2604.05018) five-agent pipeline to turn unstructured research materials (idea, experimental log, LaTeX template, conference guidelines, optional figures) into a submission-ready LaTeX manuscript and compiled PDF. TRIGGER when the user asks to "write a paper from my experiments", "turn this idea and these results into a paper", "generate a conference submission", "run paper-orchestra on X", or otherwise wants the end-to-end paper-writing pipeline. Coordinates the outline-agent, plotting-agent, literature-review-agent, section-writing-agent, and content-refinement-agent skills.
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 near the end of EZ_math_model intake when external/user-corpus contains user-provided papers, notes, PDFs, datasets, or examples that should become a local AGENTS.md reference index.
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。
Stage source files into library/raw/, converting non-markdown formats via markitdown (PDF/DOCX/PPTX/XLSX/HTML/CSV) or pandoc (TeX/EPUB/RST/ORG). Adds provenance frontmatter. No agent dispatch.
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。
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。
Build and query fully local RAG knowledge bases from documents (PDF, MD, code, etc.) using RLAMA and Ollama — no cloud, no data leaving the machine. Triggers on 'local knowledge base', 'search documents', 'document Q&A', 'RAG query', 'ingest files', 'semantic 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。
Build interactive live slide decks with Vite + React 19, TanStack Router, WebGPU shaders, Framer Motion orchestration, 1920x1080, access-gated SPA. 39 components (layout, interaction, graphics, chrome, navigation), direction-aware slide transitions, presenter mode with speaker notes and BroadcastChannel sync, Playwright PNG/PDF export, YAML-driven authoring, Cloudflare/Vercel/Netlify deploy. Triggers on: slide deck, presentation, pitch deck, investor deck, product demo, conference talk, live slides, WebGPU slides, interactive presentation, presenter mode, speaker notes, overwatch deck.
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 slide presentations from topics, URLs, PDFs, git repos, or vault notes. Use this skill when the user asks to make slides, create a presentation, build a deck, or says "slides about X". Handles research, synthesis, outline, and creation. Default output is reveal.js HTML; pptx available on request. Also handles editing existing slide decks (HTML or pptx). Triggers on /slides, /slide-maker, or any request involving presentation creation.
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。
Analyze a book (EPUB/PDF) and generate detailed chapter-by-chapter notes with extracted key concepts. Use when given a book file path to process.
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 codebases (text, structural/AST, files by name, PDFs/archives, code stats) or building context before a 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。