5,158 件 ・ 関連度順
概要と使いどころ
Expert AWS solution architecture for startups focusing on serverless, scalable, and cost-effective cloud infrastructure with modern DevOps practices and infrastructure-as-code
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 deploying changes to staging across relay, relay-dashboard, and relay-cloud repos - coordinates multi-repo branch syncing using git worktrees, automatically triggers staging deployments via GitHub Actions
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。
Your operations manager. Works out how the business actually runs on day one: suppliers and what they cost, who works when, the step-by-step routines for opening, serving or shipping and closing, the tools to run it, the licences and permits to check, and a risk register with what to do when each thing goes wrong. Feeds real costs back to the CFO. Use when the user says "how do I run this", "operations", "suppliers", "staffing", "SOPs", "what do I need to open", "permits", or "day one".
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 floating particle cloud — soft round sprites drifting in 3D with a slow scene wobble. A marketing-grade hero backdrop. One per view; scrim behind text. Renders a static frame under prefers-reduced-motion.
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。
Adapt a historical primary source for classroom use — modifying complexity and length while preserving features for sourcing, close reading, and corroboration. Use when a primary source is too complex for the target age group.
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 figure out which marketing actually drives conversions and revenue, choose or interpret an attribution model, or reconcile conflicting numbers across tools. Also use when the user mentions "attribution," "attribution model," "first-touch vs last-touch," "multi-touch," "which channel drives revenue," "what's my real CAC," "my dashboards disagree," "Google/Meta says X but GA says Y," "media mix model," "MMM," "incrementality," "geo lift," "holdout test," "how did you hear about us," "self-reported attribution," "dark social," or wants to instrument attribution themselves — "stitch my bookings to their source," "SavvyCal/Calendly attribution," "close the identify gap," "track conversions on a third-party domain," "first-party / self-hosted attribution." For event tracking setup and UTMs, see analytics. For ad-platform pixels/CAPI, see ads. For pipeline and CRM revenue reporting, see revops. For the AI-search attribution blind spot, see ai-seo.
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 Vietnam Personal Data Protection Law (PDPL) compliance advisor for Law No. 91/2025/QH15 and implementing Decree 356/2025/ND-CP (effective January 1, 2026). Use this skill for gap analysis against the Vietnam PDPL, data subject rights fulfilment workflows, cross-border data transfer impact assessments, privacy notices and internal policies, breach notification procedures, sector-specific obligations (finance, AI, cloud, blockchain), and DPO qualification reviews. Trigger whenever a user mentions Vietnam data privacy, VN-PDPL, Nghị định 356, Vietnamese personal data, or cross-border transfers involving Vietnamese citizens' 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。
Writes a settlement letter on the right footing — and warns you when marking it 'without prejudice' won't actually keep it out of court. A genuine settlement letter is normally protected (the judge can't see it), but only if the substance is a real attempt to settle, and even then there are exceptions. The skill picks the correct footing — without prejudice (WP), without prejudice save as to costs (WPSATC / Calderbank), or open — drafts the finished letter, and surfaces the Unilever v Procter & Gamble exceptions that get WP material admitted despite the label, which a plain template won't flag. Built for juniors and in-house counsel drafting a settlement or Calderbank offer who need the footing right the first time. Use when the user asks to draft a WP letter, a Calderbank, a settlement letter, or wants to know whether material is likely protected from disclosure.
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。
Screen a client, counterparty, payer or corporate against the sanctions lists published by the designating authorities themselves — the UK Sanctions List (FCDO), OFSI, the UN Security Council, the EU consolidated list and OFAC's SDN and non-SDN lists. Use when onboarding, before taking a payment, before completing a transaction, or whenever a name must be checked against sanctions. Produces candidates and provenance, never a clearance: the record names every list searched with its publication date and count, states what was NOT searched, and ends at a blank decision block. Fails closed — a cache that is missing, damaged, truncated or stale is reported NOT SEARCHED and the process exits non-zero, so nothing can read an incomplete run as clean. Matches across transliteration, diacritics, homoglyphs and initials, because nobody spells a name the way the publisher does. Standard library only; screening opens no network connection.
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 dependency network and critical path from a matter plan. Produce an interactive Gantt, flag near-critical tasks, and run what-if cascade scenarios when delays occur — showing programme impact and drafting communications. Produces filtered workstream or jurisdiction views for local counsel. Trigger on: 'build a timeline', 'Gantt chart', 'critical path', 'what if X is delayed', 'what moves if', 'schedule impact', 'how does this affect the programme', 'when do we finish', 'can we still close on time', 'if we miss this deadline', 'run a what-if', 'visualise the plan', 'Germany timeline', 'what does the Employment workstream look like', 'timeline for local counsel', 'just show me the [workstream] 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。
Systematic contract negotiation strategies for technology services agreements with German/EU law specificity. Provides three-position framework (provider-favorable, balanced, client-favorable), deal-size calibration (€100K to €10M+), five-tier objection handling with regulatory leverage (GDPR, DORA, NIS2, BGB), concession packaging, and position matrices for liability, IP, payment, SLA, data protection, and termination. Use when: (1) Developing negotiation strategies for SaaS, cloud, or managed services agreements, (2) Preparing position papers and fallback positions, (3) Responding to counterparty objections, (4) Structuring concession packages that protect core economics, (5) Calibrating tactics to deal size and leverage, or (6) Applying German contract law constraints (BGB §§ 305-310 AGB, § 309 Nr. 7 liability limits, § 288 statutory interest).
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。
Critically assess and improve a legal scholarly thesis, article idea, student note, seminar-paper claim, or research agenda using Eugene Volokh's novelty, nonobviousness, utility, and soundness framework, connector-aware research, claim-specific tests, and a sustainable adversarial pass. Produces a self-contained green-, yellow-, or red-light report. Use when a law professor or law student asks whether a claim is viable, novel, publishable, preempted, useful, worth pursuing, or better than competing topics; or wants a thesis stress-tested, narrowed, repaired, or compared. No connector is required: use connected legal and scholarly research when available, public sources otherwise, and disclose any no-research fallback.
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。
Run an attorney-facing knockout/availability trademark search across the United States and Canada. Use whenever a user (founder, client, or attorney) asks whether a brand, mark, name, logo, slogan, or product name is "available," "free to use," "clearable," or "already taken" — or asks Claude to "search the trademark register," "check USPTO," "check CIPO," "do a knockout search," "clearance search," "availability search," or "see if [mark] is trademarked." Trigger even when the user phrases it casually ("can I call my company X?", "is this name taken?"). Covers federal USPTO (TESS/TSDR), federal Canada (CIPO), common-law/web/state, and WIPO Madrid international. Output is a knockout availability memo with green/yellow/red verdict for attorney review. Includes professional-responsibility gating (AI-use disclosure, conflict check, scope confirmation) before substantive analysis. Not legal advice — produces work product for attorney sign-off.
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 original, competition-ready commercial mediation problems and confidential packets with iterative validation. Use when a user provides a topic, industry, dispute sketch, or existing general-information packet and wants a public packet plus confidential packets for both sides—or one named side. Build a narrow but workable settlement corridor; verify factual and numerical consistency, information asymmetry, balance, originality, and commercial feasibility; and revise until deterministic and semantic exit criteria pass. Do not use merely to summarize an existing packet or to advise parties in a real dispute. Requires local file access; Python 3 is recommended for bundled deterministic checks, with disclosed manual fallbacks when unavailable.
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。
Edit mathematically, empirically, or technically dense papers for readers outside the author’s specialty, including empirical legal scholarship, law-and-economics models, and legal-technology research. Clarifies terminology, antecedents, study design, and claim–statistic relationships while checking equations, numbers, quotations, and citations against the source. Use to clarify exposition or de-jargonize a technical draft; not to rewrite briefs or doctrinal arguments. Produces an edited draft and audit memo. Full integrity checks and original-format rendering require suitable extraction, code execution, and document tools; otherwise provides proposed edits with verification limits 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。
Detects prompt injection hidden in documents from the other side (pleadings, skeletons, bundles, served evidence, opponents' emails and attachments) before an AI reads them, so the model is not turned against your client. Checks word by word that the text an extractor hands the model was visibly drawn on the page: white, near-white, covered, clipped, off-page, tiny, transparent and invisible-mode text in PDF (ink test plus OCR); Word formatting resolved as Word does (styles, shading, theme colours, scaling, off-page frames, fallbacks, unused headers); HTML/CSS, RTF, email with attachments and zips, xlsx/pptx and legacy formats. Flags Unicode smuggling, text addressed to an AI and authorities found only in hidden text. Fails closed. Optional Read-tool hook. Use BEFORE any AI summary or analysis of an opposing or third-party document. Triggers: 'scan for injection', 'is this document safe', 'check the other side's skeleton', 'injection guard'.
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。
EU NIS2 Directive (Directive (EU) 2022/2555) compliance advisor for essential and important entities: entity classification, Art. 21 risk management measures, Art. 23 incident reporting timelines (24h/72h/1 month), Art. 20 governance obligations, supply chain security (Art. 21(2)(d); coordinated risk assessments Art. 22), gap assessments, policy drafting, ISO 27001 alignment, and penalty exposure analysis. Also covers Commission Implementing Regulation (EU) 2024/2690, the technical/methodological sub-requirements for Art. 21(2) and the significant-incident thresholds binding on DNS/cloud/data-centre/MSP/MSSP/trust-service and other digital entities. Use for NIS2 readiness, transposition questions, ENISA technical implementation guidance, significant-incident thresholds, supervisory differences between essential and important entities, and cross-border coordination.
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 zero-hallucination privacy-policy generator that takes anyone — non-lawyer founder to lawyer — from a guided intake to a publishable, jurisdiction-aware privacy policy. Jurisdiction-first: it detects which laws apply from where your users are, then drafts only the required clauses — GDPR/EU + UK, US (CCPA/CPRA, ~20 state laws, COPPA, sector overlays), and global/MENA (LGPD, Quebec Law 25, India DPDP, China PIPL, UAE/DIFC, Saudi PDPL), plus app-store, cookies, and AI/EU AI Act disclosures. Its rule: state only what you confirm; never invent a statute, citation, fine, or date — every claim is source-cited and QA-gated. Not legal advice.
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。
Guide to review incoming one-way (unilateral) commercial NDAs in a jurisdiction-agnostic way, from either a Recipient or Discloser perspective (user-selected), producing a clause-by-clause issue log with preferred redlines, fallbacks, rationales, owners, and deadlines.
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。
Draft GDPR/DSGVO-compliant privacy notices as .docx for any EU/EEA jurisdiction and audience. Use when user asks to create a privacy policy/notice, mentions "Datenschutzerklärung", "politique de confidentialité", "privacy notice", needs Art. 13/14 disclosures, AI Act transparency, cookie policy, or notices for applicants ("Bewerber-Datenschutz"), employees ("Beschäftigten-Datenschutz"), B2B partners, or B2C customers. Covers DE (DSGVO+BDSG+TDDDG), FR (RGPD+LIL+LCEN), AT, IT, ES, NL, BE, IE, UK GDPR. Five notice types: Website/App, Applicant, Employee, Business Partner, B2C Customer.
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。
Evaluate completed mediation-competition problems consisting of general information and confidential packets for both sides. Use when asked to validate, audit, score, quality-control, or assess competition readiness; identify factual, numerical, chronological, authority, commercial-logic, or confidentiality defects; test mediation usefulness, BATNAs, settlement corridors, information asymmetry, and opportunities for firmness, cooperation, imagination, and clarification; or produce an author-only validation report. Perform a qualified partial review when packets are missing. Diagnose by default; do not generate a new problem or edit source packets unless repairs are expressly requested. Requires access to all supplied files and a host capable of reading their formats; otherwise disclose the unreviewed material and resulting limits.
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 ITAR compliance advisor for US defense contractors, exporters, and manufacturers. Use this skill for any question about 22 CFR Parts 120-130, the United States Munitions List (USML), DDTC registration, export license applications (DSP-5/73/94), Technical Assistance Agreements (TAA), Manufacturing License Agreements (MLA), brokering regulations (Part 129), deemed export rules for foreign nationals, technology control plans, voluntary disclosures, violation mitigation, jurisdiction determination (ITAR vs EAR), or US Munitions List category scoping. Trigger even if the user doesn't say "skill" — any ITAR or US defense export control question should use this skill.
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。
Takes a skill — a .skill or .zip archive, a bare SKILL.md, a folder, or just a raw idea — and produces a package ready for public distribution on lawve.ai, plus the exact entries for the submission form. Runs a gate first: skills with no plausible legal use, unsafe code, or licensing bars are declined with reasons, and general-purpose skills that could serve legal work are offered a legal adaptation instead. Then applies the standard compliance transforms — structure, metadata, attribution, dependency ladders, orphaned-file repair, limitations disclosure — validates the result, and delivers a zip. Raw ideas are gated first, built (via skill-creator where available), then adapted. Use for "make this Lawve-compliant," "prep this skill for Lawve," "package for lawve.ai," "is this suitable for Lawve," "get my skill ready to publish," or any request to ready a skill for the Lawve catalogue.
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。
Assesses which of the Art. 50(1)-(5) transparency obligations of the EU AI Act apply to a given AI system's provider or deployer, grounded in the final Code of Practice on Transparency of AI-Generated Content (June 2026) and the Commission's draft Art. 50 Guidelines. Covers AI-chatbot disclosure, deepfake and synthetic-content marking/watermarking, emotion-recognition and biometric-categorisation notices, the machine-readable marking duty, the obviousness exceptions, and the implementation timeline. Outputs a formal mini-report plus a per-obligation compliance checklist with gap flags. For breadth-first tier triage use the EU AI Act System Classifier; for raw Art. 50 text and Q&A use the EU AI Act Knowledge Base; for the full role x tier matrix use the EU AI Act Obligations Mapper.
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。