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概要と使いどころ
Publish Markdown articles to X (Twitter) Articles editor with proper formatting. Use when user wants to publish a Markdown file/URL to X Articles, or mentions "publish to X", "post article to Twitter", "X article", or wants help with X Premium article publishing. Handles cover image upload and converts Markdown to rich text automatically.
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。
Controlla coerenza e plausibilità delle citazioni normative italiane ed europee in un testo prodotto da un'altra skill legal-tech (o passato dall'avvocato). Verifica formato, esistenza apparente, coerenza interna, segnala citazioni sospette o non risolvibili. Usa quando una skill IT/EU ha appena prodotto un output con riferimenti normativi, o quando l'avvocato chiede esplicitamente "verifica le fonti", "controlla le citazioni", "queste citazioni reggono?".
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。
a skill that determines whether a given subject matter qualifies for copyright protection under EU law by applying the Cofemel two-step test (concept of work + originality), grounded in fifteen CJEU judgments (including the most recent Mio/Konektra and Calinescu) and the four EU directive provisions on originality. It argues from one of two positions: pro-rightsholder (establishing that the work is original) or pro-alleged-infringer (contesting work status or originality via the four exclusion grounds — technical function, rule-dictated outcome, sweat of the brow, idea/functionality). It includes sector-specific modules for photography, software/GUI, sporting events, databases, applied art, functional texts, derivative works/critical editions, and multimedia works.
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 and cite French case law and statutes with the LibreJustice MCP tools. Use whenever the user asks about French or European court decisions (Cour de cassation, Conseil d'État, cours d'appel, TJ/TA, CNDA, Conseil constitutionnel, CNIL, CEDH, CJUE), needs authorities for a brief, requête, référé or consultation, wants to check how courts rule on an issue, needs counts of decisions on a point, or asks what a code article says at a given date, even if they never mention LibreJustice.
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。
Searches the domestic courts of 122 jurisdictions — 153 databases, 49 automated — for extradition and arrest-warrant surrender decisions, each in its own language and vocabulary. Answers the question no commercial database does: how are OTHER executing states treating this requesting state, or this ground? Searching by requesting state localises its name per jurisdiction (AE becomes 'Emiratele Arabe Unite' in Romania, 'Emirati Arabi Uniti' in Italy), so the sweep finds what those courts actually wrote. Every hit passes a relevance gate; every search leaves a dated report, so the research is reconstructable months later. Use when asked what foreign courts have said about surrender to a given state, whether any European court has refused extradition on prison conditions, assurances or Article 3, for comparative extradition research, or to build a foreign-authority section of an extradition argument. Not for domestic case law of the user's own jurisdiction, and never a substitute for reading the judgment.
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。
Toolkit for comprehensive Spreadsheet reading, creation, editing, and analysis with visual quality control. Use to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing tabular data, (3) Modifying existing spreadsheets while preserving formulas, (4) Building financial models with proper formatting, (5) Data visualization with in-sheet charts, or any other spreadsheet tasks.
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。
Assess obligations under Regulation (EU) 2023/2854 for connected products, related services, statutory B2B data sharing, unfair data-contract terms, exceptional-need B2G requests, data-processing-service switching, international governmental access, interoperability, smart contracts, enforcement, and non-EU representatives. Use for Data Act scope analysis, gap assessments, product and service design, request handling, contract review, cloud exit planning, or cross-regulation mapping.
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。
Practitioner skill for advising on EU Regulation 2023/2854 (Data Act). Covers Chapters II-VII (IoT data access, mandatory B2B sharing, unfair contract terms, public-sector exceptional need, cloud switching, third-country governmental access) and Chapter VIII (interoperability and smart contracts, gate-only). Use when the user asks about Data Act rights or obligations, drafts a Data Act notice or letter, reviews a data-sharing or cloud-switching contract under the Data Act, runs a Data Act gap analysis, or asks how the Data Act interacts with GDPR, the DMA, the Trade Secrets Directive, or sectoral law. Triggers include "Data Act", "Datengesetz", "Regulation (EU) 2023/2854", "Art. 4(1) request", "Art. 5(1) third-party request", "trade-secret handbrake", "cloud switching obligations", "Chapter VI", "Ch V exceptional need", and references to specific Data Act articles or recitals.
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 US employment law topic across federal, state, and city jurisdictions and produce structured research notes with proper source attribution. Use this skill any time the user asks about US employment laws, regulations, or pending legislation - from a single jurisdiction question to a 50-state survey. Triggers include phrases like "research [employment law topic]", "what are the laws on [employment topic]", "state-by-state [employment topic]", "help me understand [topic] across the US", or any prompt that asks for a legal landscape overview before another deliverable. Always run this BEFORE the employment-law-dashboard skill if a dashboard is the eventual output. Output is a structured research note that distinguishes primary sources (statutes, regs, agency guidance) from secondary sources (law firm alerts, tracker orgs).
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。
Works out which documents you have to hand over to the other side in a civil case in England & Wales, and builds the formal list. The part it gets right that trips people up is which disclosure regime applies — Practice Direction 57AD (the Disclosure Pilot, now permanent in the Business and Property Courts, with its Models A–E) or standard disclosure under CPR Part 31 everywhere else. It picks the regime, chooses a Model per issue, structures the Disclosure Review Document, and drafts the disclosure certificate for the party to sign personally. Built for litigation juniors, in-house counsel, and small teams without a precedent bank. Use when the user says 'disclosure list', 'PD 57AD', 'Model C', 'extended disclosure', 'List of Documents', 'N265', or needs to work out what must be disclosed.
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 up translation-ese and AI-writing tics in Korean prose so it reads like a person wrote it — content (facts, numbers, proper nouns, quotes) stays 100% unchanged, only style and rhythm are touched. Single-pass, done in this session. Triggers — AI 티 없애줘, 번역투 고쳐줘, 한글 자연스럽게 윤문해줘, sounds like a machine translation, remove AI tells from this Korean text, make this Korean read naturally. Not for: marketing copy generation (write it clean the first time — see rules/korean-writing-quality.md), English text, plain spell-check (see korean-spell-check), or book-length manuscripts.
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。
Configure and author rgthree-comfy nodes — Fast Groups Bypasser/Muter (group toggles), Power Lora Loader, Context/Context Big, Seed, Any Switch. Use when a workflow contains rgthree nodes, when asked to add stage/section toggles or an A/B switch, when stacking LoRAs, or when an rgthree node needs configuring. Covers the frontend-only nodes that are absent from /object_info and the properties-not-widgets configuration model.
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 implementing tweens — property animation, method tweening, chaining, parallel sequences, easing, and common UI/gameplay motion recipes
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 new Claude Code Skills with proper YAML frontmatter, progressive disclosure structure, and complete directory organization. Use when you need to build custom skills for specific workflows, generate skill templates, or understand the Claude Skills specification.
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。
Guides you through creating well-structured Claude Code skills with proper modularization, templates, and best practices. Use when creating new skills or improving existing ones.
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。
Generates structured logging infrastructure using os.log/Logger to replace print() statements. Use when user wants to add proper logging, replace print statements, or set up app logging.
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。
NanoTube includes functions for the processing, quality control, analysis, and visualization of NanoString nCounter data. Analysis functions include differential analysis and gene set analysis methods, as well as postprocessing steps to help understand the results. Additional functions are included to enable interoperability with other Bioconductor NanoString data analysis packages.
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。
An implementation, which takes input data and makes it available for proper batch effect removal by ComBat or Limma. The implementation appropriately handles missing values by dissecting the input matrix into smaller matrices with sufficient data to feed the ComBat or limma algorithm. The adjusted data is returned to the user as a rebuild matrix. The implementation is meant to make as much data available as possible with minimal data loss.
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。
Multivariate methods are well suited to large omics data sets where the number of variables (e.g. genes, proteins, metabolites) is much larger than the number of samples (patients, cells, mice). They have the appealing properties of reducin
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。
cogeqc aims to facilitate systematic quality checks on standard comparative genomics analyses to help researchers detect issues and select the most suitable parameters for each data set. cogeqc can be used to asses: i. genome assembly and annotation quality with BUSCOs and comparisons of statistics with publicly available genomes on the NCBI; ii. orthogroup inference using a protein domain-based approach and; iii. synteny detection using synteny network properties. There are also data visualizat
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。
Provides guidance for writing and benchmarking optimized Triton kernels for AMD GPUs (MI355X, R9700) on ROCm, targeting HuggingFace diffusers (LTX-Video, SD3, FLUX) and transformers. Core kernels: RMSNorm, RoPE 3D, GEGLU, AdaLN. Includes XCD swizzle, autotune, diffusers integration patterns, and LTX-Video pipeline injection.
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。
Force unrelated concepts together to discover emergent properties - "What if we treated X like Y?"
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 Bilt Rewards travel portal for cash and Bilt Points pricing on hotels and flights. Public REST API, no auth required. Includes Home Away From Home (HaFH) properties with $300+ benefits.
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。