661 件 ・ 関連度順
概要と使いどころ
AI-assisted generation of MCQs (multiple-choice questionnaires) with export to Moodle (GIFT, XML), Wooclap (Excel), Kahoot!, and Word. Supports light MCQs (gamified) and in-depth MCQs (evaluative), with single-answer and multiple-answer formats.
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。
Produces properly-formatted legal documents in Word (.docx). The user provides the substantive content (instructions, attached files, project knowledge); the skill handles document architecture and formatting. * No precedent or template required * Seven document families: agreements, corporate documents, litigation, memos, employment, policies, correspondence * Jurisdiction-agnostic — works across any legal system the user specifies * Multi-Chain numbering, defined-terms convention, structured recitals, atomic signature blocks * Also reformats existing .docx to a consistent house style * Works in Claude.ai, Cowork, and Claude for Word
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。
Turn an interpretive-ambiguity audit of a legal text — contract, statute, regulation, or judicial opinion — into a polished deliverable. Produces a multi-page website (default), a single-page interactive site, a Microsoft Word document, a PowerPoint deck, or a LaTeX/PDF. Use whenever a user has a stress-test result, ambiguity audit, or "where will this be litigated" scenarios and wants to publish, present, or share them. Triggers on "publish the audit," "make a report from this," "turn this into a website / deck / brief / Word doc," "make a Netlify site," "build slides of these ambiguities," "render the scenarios," "package this stress test," "produce a LaTeX version," and similar. Pairs with the ambiguity-stress-test skill (the underlying analysis) but works on any structured or semi-structured ambiguity analysis. Visual design is opinionated but the user can override colors, fonts, and brand label. Most formats need Python and a writable filesystem; single-file HTML works where the host has neither.
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。
Produces detailed law-school case briefs of United States judicial opinions in a fixed nine-section structure: memory jogger, facts, procedural history, judicial votes, holding, opinion-by-opinion analysis, five future-application hypotheticals, critique, and verified key quotations. Also builds vote tables, cross-case consistency tables, perspective-based critiques, and LaTeX in article, Beamer and casebook-chapter formats. Use whenever someone asks to brief a case, analyse or explain an opinion, summarise a decision for students, generate hypotheticals from a holding, critique a judgment, tabulate how justices voted, or convert case analysis to LaTeX. Triggers on "brief this case", "case brief", "explain the holding", "what did the court hold", "hypotheticals based on", "critique this opinion", "vote table", "Beamer presentation", "chapter brief", and on any reference to a judicial opinion or Supreme Court decision in a teaching context. Requires web search to verify quotations, votes and holdings.
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。
Expert blueprint for Battle Royale games including shrinking zone/storm mechanics (phase-based, damage scaling), large-scale networking (relevancy, tick rate optimization), deployment systems (plane, freefall, parachute), loot spawning (weighted tables, rarity), and performance optimization (LOD, occlusion culling, object pooling). Use for multiplayer survival games or last-one-standing formats. Trigger keywords: battle_royale, zone_shrink, storm_damage, deployment_system, loot_spawn, networking_optimization, relevancy_system, snapshot_interpolation.
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。
Clean and normalize A-share financial data for modeling. Adapts the original clean-data-xls skill for Chinese financial statements, CAS conventions, and A-share data formats. Triggers on "A股数据清洗", "财务数据清洗", "clean financial data China", "数据清洗", or "normalize financial statements".
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。
Image optimization analysis for SEO and performance. Checks alt text, file sizes, formats, responsive images, lazy loading, CLS prevention, image SERP rankings (via DataForSEO), and image file optimization (WebP/AVIF conversion, IPTC/XMP metadata injection). Use when user says "image optimization", "alt text", "image SEO", "image size", "image audit", "optimize images", "image metadata", "image SERP", "convert to webp", or "image file optimize".
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。
When the user wants to create competitor comparison or alternative pages for SEO and sales enablement. Also use when the user mentions 'alternative page,' 'vs page,' 'competitor comparison,' 'comparison page,' '[Product] vs [Product],' '[Product] alternative,' or 'competitive landing pages.' Covers four formats: singular alternative, plural alternatives, you vs competitor, and competitor vs competitor. Emphasizes deep research, modular content architecture, and varied section types beyond feature tables.
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Generates data export/import infrastructure for JSON, CSV, PDF formats with GDPR data portability, share sheet integration, and file import. Use when user wants data export functionality, CSV/JSON/PDF export, GDPR compliance data portability, import from files, or share sheet for 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。
mzR provides a unified API to the common file formats and parsers available for mass spectrometry data. It comes with a subset of the proteowizard library for mzXML, mzML and mzIdentML. The netCDF reading code has previously been used in XC
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Extensible framework for interacting with multiple genome browsers (currently UCSC built-in) and manipulating annotation tracks in various formats (currently GFF, BED, bedGraph, BED15, WIG, BigWig and 2bit built-in). The user may export/imp
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。
Universal LaTeX document skill: create, compile, and convert any document to professional PDF with PNG previews. Supports resumes, reports, cover letters, invoices, academic papers, theses/dissertations, academic CVs, presentations (Beamer), scientific posters, formal letters, exams/quizzes, books, cheat sheets, reference cards, exam formula sheets, fillable PDF forms (hyperref form fields), conditional content (etoolbox toggles), mail merge from CSV/JSON (Jinja2 templates), version diffing (latexdiff), charts (pgfplots + matplotlib), tables (booktabs + CSV import), images (TikZ), Mermaid diagrams, AI-generated images, watermarks, landscape pages, bibliography/citations (BibTeX/biblatex), multi-language/CJK (auto XeLaTeX), algorithms/pseudocode, colored boxes (tcolorbox), SI units (siunitx), Pandoc format conversion (Markdown/DOCX/HTML ↔ LaTeX), and PDF-to-LaTeX conversion of handwritten or printed documents (math, business, legal, general). Compile script supports pdflatex, xelatex, lualatex with auto-detection, latexmk backend, texfot log filtering, PDF/A output, and verbosity control (--verbose/--quiet). Empirically optimized scaling: single agent 1-10 pages, split 11-20, batch-7 pipeline 21+. Use when user asks to: (1) create a resume/CV/cover letter, (2) write a LaTeX document, (3) create PDF with tables/charts/images, (4) compile a .tex file, (5) make a report/invoice/presentation, (6) anything involving LaTeX or pdflatex, (7) convert/OCR a PDF to LaTeX, (8) convert handwritten notes, (9) create charts/graphs/diagrams, (10) create slides, (11) write a thesis or dissertation, (12) create an academic CV, (13) create a poster, (14) create an exam/quiz, (15) create a book, (16) convert between document formats (Markdown, DOCX, HTML to/from LaTeX), (17) generate Mermaid diagrams for LaTeX, (18) create a formal business letter, (19) create a cheat sheet or reference card, (20) create an exam formula sheet or crib sheet, (21) condense lecture notes/PDFs into a cheat sheet, (22) create a fillable PDF form with text fields/checkboxes/dropdowns, (23) create a document with conditional content/toggles (show/hide sections), (24) generate batch/mail-merge documents from CSV/JSON data, (25) create a version diff PDF (latexdiff) highlighting changes between documents, (26) create a homework or assignment submission with problems and solutions, (27) create a lab report with data tables, graphs, and error analysis, (28) encrypt or password-protect a PDF, (29) merge multiple PDFs into one, (30) optimize/compress a PDF for web or email, (31) lint or check a LaTeX document for common issues, (32) count words in a LaTeX document, (33) analyze document statistics (figures, tables, citations), (34) fetch BibTeX from a DOI, (35) convert a Graphviz .dot file to PDF/PNG, (36) convert a PlantUML .puml file to PDF/PNG, (37) create a one-pager/fact sheet/executive summary, (38) create a datasheet or product specification sheet, (39) extract pages from a PDF (page ranges, odd/even), (40) check LaTeX package availability before compiling, (41) analyze citations and cross-reference with .bib files, (42) debug LaTeX compilation errors, (43) make a document accessible (PDF/A, tagged PDF), (44) create lecture notes or course handouts, (45) fill an existing PDF form (fillable fields or non-fillable with annotations), (46) extract text or tables from a PDF (pdfplumber, pypdf), (47) OCR a scanned PDF to text (pytesseract), (48) create a PDF programmatically with reportlab (Canvas, Platypus), (49) rotate or crop PDF pages (pypdf), (50) add a watermark to an existing PDF, (51) extract metadata from a PDF (title, author, subject).
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。
Java logging best practices with SLF4J, structured logging (JSON), and MDC for request tracing. Includes AI-friendly log formats for Claude Code debugging. Use when user asks about logging, debugging application flow, or analyzing logs.
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。
Plan, build, and optimize Meta advertising campaigns on Facebook and Instagram — campaign structure, audience targeting (core, custom, lookalike), creative formats, pixel setup, retargeting strategy, budget scaling, and ROAS optimization. Use when the user says "Meta ads", "Facebook ads", "Instagram ads", "Facebook advertising", "Meta advertising", "Meta campaigns", "Facebook campaign", "Instagram campaign", "Meta ad strategy", "ROAS", "Meta pixel", "Facebook pixel", "lookalike audiences", "Meta retargeting", "scaling Meta ads", "Facebook ad account", "Meta ads manager", "Facebook ads not working", or wants to run or improve paid social advertising on Facebook or Instagram.
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 building, writing, refining, or structuring a Higgsfield AI prompt. Covers the MCSLA formula, prompt structure, narrative vs. timestamped formats, and how to write for both text-to-video and image-to-video workflows.
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 and publish social media posts for Reddit, Twitter/X, LinkedIn, Instagram, Facebook, and TikTok. Platform-specific formats, character limits, hashtag strategies, hooks, and content repurposing. Can post directly to Reddit and other platforms via API. Trigger phrases: "social media post", "tweet", "LinkedIn post", "Instagram caption", "TikTok script", "social content", "social media copy", "carousel", "thread", "social media strategy", "repurpose content", "hashtag strategy", "post to reddit", "publish on social", "post on reddit", "share on social media".
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。
Repurpose and atomize content across platforms and formats. Use when the user says "repurpose this", "turn this into", "convert blog to", "make a thread from", "content atomization", "repurpose content", "turn this article into social posts", or asks about adapting content from one format to another.
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。
Scan social platforms for top-performing content by engagement before you create anything. Use this skill when the user wants to see what content is winning in a niche, find viral content patterns, research what's working on YouTube/TikTok/X/Reddit, benchmark engagement, discover content gaps, or says "what content is working for [topic]", "show me top performing content about [keyword]", "what's trending in [niche]", "find viral content about [product]", "content research for [keyword]", "what gets views in [niche]", "engagement analysis for [topic]", "scout the competition", "what videos are getting the most views about [keyword]", "social listening for [topic]", "trending content in [niche]", "top content analysis", "what hooks work for [keyword]", "content intelligence", "find winning formats".
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。
Repurpose one piece of affiliate content into multiple formats. Triggers on: "repurpose my content", "turn my blog into tweets", "cross-post this", "content recycling", "convert to newsletter", "make a tweet thread from this", "adapt for TikTok", "omnichannel content", "scale my content", "turn this into a LinkedIn post", "repurpose for email", "content multiplication".
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。
Download YouTube videos with customizable quality and format options. Use this skill when the user asks to download, save, or grab YouTube videos. Supports various quality settings (best, 1080p, 720p, 480p, 360p), multiple formats (mp4, webm, mkv), and audio-only downloads as MP3.
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。
Pre-pipeline aggregator that scans AI agent cache directories (.claude, .cursor, .antigravity, .openclaw) or any user-specified directory for experimentation logs, extracts insights and numeric results, and formats them as PaperOrchestra-ready inputs (idea.md + experimental_log.md). TRIGGER when the user says "aggregate my agent logs for paper writing", "extract experiments from my coding agent history", "prepare PaperOrchestra inputs from my cache", "turn my agent logs into a paper", mentions a folder or directory they want to use as the basis for a paper, or wants to run PaperOrchestra but only has scattered agent experiment histories rather than structured inputs. Run this BEFORE paper-orchestra. Also called automatically by paper-orchestra when workspace/inputs/idea.md or workspace/inputs/experimental_log.md are missing.
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。
Cross-agent collaboration protocols, workflow handoff patterns, and commit message formats for TDD/Mikado/refactoring workflows
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。
Formats plain text or markdown files with frontmatter, titles, summaries, headings, bold, lists, and code blocks. Use when user asks to "format markdown", "beautify article", "add formatting", or improve article layout. Outputs to {filename}-formatted.md.
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 this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.
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。