「compliance」の検索結果

Adjudicates whether a hit generated by sanctions, PEP, or adverse-media screening is a true positive, false positive, or requires human escalation. Use whenever a user presents a screening alert, a name match against a watchlist (OFAC SDN, EU consolidated list, UK OFSI, UN list, PEP list, adverse media hit, etc.), or asks to clear a screening hit / reduce false positives / determine whether a flagged name is actually the listed party. Use even when the user describes the task casually — "is this person actually on the sanctions list", "did we get a real match", "clear this alert", "I have a hit on X" — these are all screening-adjudication tasks. Produces a deterministic determination with full audit trail (structured JSON + human-readable narrative). Designed for use by compliance analysts and screening systems.

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First-pass framework for reading, interpreting, and structuring statutory analysis of US federal, state, and local law. Produces draft analysis for attorney review — not legal advice. Use this skill whenever the user references a specific US statute, regulation, ordinance, or rule by citation, asks "what does [statute X] require," asks for compliance scoping, applicability thresholds, requirement extraction, exemption analysis, definitional analysis, federal preemption analysis, or multi-state comparison — even if they don't explicitly ask for "statutory analysis." Halts and asks for missing inputs rather than guessing. Out of scope for non-US law.

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Swiss legal source and authority triage. Use when a user asks a Swiss legal, regulatory, compliance, contract, employment, corporate, litigation, IP, tax, privacy, public-law, fintech, register, or cantonal-law question; when Swiss law may apply; or when an AI legal answer needs source routing across federal, cantonal, communal, regulator, register, contractual, professional, soft-law, multilingual, or open-data layers.

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。

Adversarial verification of AI-generated legal content with systematic fact-checking, source validation, and quality control. Use when a user asks to verify, fact-check, red-team, validate sources, or quality-control a legal document, briefing, compliance summary, or regulatory analysis before it is distributed to clients, stakeholders, or published. Trigger phrases include "verify", "fact-check", "red team", "red-flag", "check accuracy", "validate sources", "quality control", "is this correct", and "review for errors". Produces a structured verification report with severity-categorized errors, verified sources, unsupported claim list, missing disclaimers, and an explicit distribution-readiness assessment.

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。

Prepare structured briefings for meetings with legal relevance and track resulting action items. Use when preparing for contract negotiations, board meetings, compliance reviews, or any meeting where legal context, background research, or action tracking is needed.

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。

Panel health assessment, firm exit management, coverage gap analysis, and panel refresh brief for in-house legal ops teams. Produce an annual Panel Health Report synthesising scorecard data, billing compliance, and step-out patterns into per-firm recommendations — Retain, Watch, Improvement Plan, or Exit Review. Produce a firm exit pack: formal exit notice with active matter transition plan, plus an internal exit record. Identify practice area, geographic, or tier gaps and produce a structured Coverage Gap Report with remediation options. Produce a Panel Refresh Brief as a scoped input to the RFP process. Trigger on: 'review our panel', 'annual panel review', 'is our panel working', 'which firms should we exit', 'write the exit notice', 'coverage gap', 'we don't have anyone for restructuring', 'refresh the panel', 'panel rationalisation', 'too many firms', 'step-out problem', 'do we have the right firms'.

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Wyszukiwanie, pobieranie i analiza aktów prawnych UE oraz polskich aktów i projektów wdrażających regulacje UE (np. PPWR, CBAM, EUDR, ESPR, CSRD, CSDDD, GPSR, AI Act, baterie, ekoprojekt). Używaj, gdy użytkownik potrzebuje statusu prawnego, dat stosowania, przepisów przejściowych, relacji aktów, obowiązków compliance i raportu z podstawami prawnymi oraz źródłami urzędowymi.

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NIL (Name, Image, and Likeness) contract analysis for NCAA student-athletes from the athlete's perspective. Use when user says 'review this NIL contract', 'analyze this NIL deal', 'check this athlete agreement', 'review my NIL agreement', or uploads a PDF NIL contract for review. Identifies red flags, missing protections, and compliance issues. Produces a structured review memorandum with negotiation positions. Do NOT use for general contract review, employment agreements, non-NIL endorsements, or brand-side deal analysis.

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.

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Use this skill when asked to analyze how Iceland has implemented an EU directive or regulation into national law, identify gaps between EU/EEA law and Icelandic implementation, or assess Iceland's compliance with EEA obligations. Triggers on questions about EEA transposition, ESA infringement, or EU-Iceland legal gaps.

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 when asked to review data protection or privacy compliance under Icelandic law and GDPR. Triggers on requests involving personal data processing, privacy policies, DPIA assessments, kennitala handling, Persónuvernd filings, or cross-border data transfers from Iceland.

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 whether Government of India approval is required for foreign investment in an Indian company under Foreign Exchange Management Act, 1999 and the Non-Debt Instruments Rules, 2019. The skill systematically gathers transaction details, evaluates sectoral entry routes and caps, assesses land border country restrictions under applicable laws, and delivers a preliminary compliance note. Produces clear guidance on whether the investment falls within Automatic Route or requires Government approval.

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 ISO 27701 Privacy Information Management System (PIMS) compliance advisor. Use this skill whenever a user asks about ISO/IEC 27701:2025, ISO/IEC 27701:2019, privacy information management, PIMS certification, PII controller or processor obligations, privacy risk assessment, Statement of Applicability for privacy, privacy by design, data subject rights, DPIA, records of processing activities, transitioning from ISO 27701:2019, GDPR alignment with ISO 27701, or any privacy management system topic. Also trigger for questions about Annex A.1 (controller controls), A.2 (processor controls), A.3 (shared security controls), or implementing a standalone PIMS without ISO 27001. When in doubt, use this skill — it covers the full ISO 27701 lifecycle from gap assessment through certification.

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 a lawyer's bounded expertise, workflow, review standard, or legal judgment pattern into a safe, inspectable legal AI skill. Use when a user provides legal memos, comments, checklists, negotiation notes, review habits, compliance playbooks, or professional feedback and wants a reusable Lawve-style skill. Do not impersonate the lawyer or claim to reproduce a person; distill only authorized, source-bounded capability.

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。

Use when a user needs a legal or legal-adjacent Mermaid diagram from a document, pasted text, matter description, process, timeline, party map, obligation map, corporate structure, funds flow, or compliance workflow. Trigger on: "diagram this contract", "visualise this deal/matter", "map the parties", "create a timeline of events", "make an org chart", "obligation checklist", "export as HTML diagram". Not for general-purpose non-legal diagrams, pure graphic design, image generation, or 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。

Builds a high-fidelity interactive legal assessment as a single self-contained HTML artifact. Output includes a live countdown timer, contract review tasks with hover-annotated problem clauses, candidate answer textareas, model answers hidden behind reveal blocks, scenario-based legal memo tasks, strategy and function-building questions, and a pre-submission checklist that encodes the marking criteria. Use when the user needs to (1) assess a legal candidate with a realistic timed exercise, (2) train or onboard junior lawyers using problem sets rather than doctrine, (3) help a candidate prepare for a real take-home assessment they are facing, (4) build educational materials for law students, in-house teams, or compliance training, or (5) produce scenario-based training modules on specific legal topics. Triggers on "legal test", "take-home", "mock exam", "contract redline exercise", "candidate assessment", "legal training exercise", "practice test", or similar phrasing even when informal.

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。

Audits the transition from legal AI output to reliance, recommendation, execution, or real-world commitment. Use it before an AI-generated analysis, memo, contract review, compliance finding, or workflow output is acted upon to check whether authority, evidence, mandate, uncertainty, procedure, and review conditions remain sufficient.

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 LGPD compliance advisor for Brazil's Lei Geral de Proteção de Dados (Law 13,709/2018). Use this skill whenever a user asks about LGPD, Brazilian data protection, ANPD, personal data processing in Brazil, data subject rights under Brazilian law, legal bases for processing, sensitive data handling, DPO appointment in Brazil, data breach notification to ANPD, LGPD penalties (fines up to 2% of revenue / R$50M), international data transfers from Brazil, Brazil-EU mutual adequacy (January 2026 — SCCs/BCRs no longer needed for Brazil-EU transfers), LGPD gap assessments, privacy policy drafting for Brazilian operations, DPIA under LGPD, consent management, or comparing LGPD with GDPR. Trigger for any Brazil privacy or data protection question even if LGPD is not named explicitly.

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。

GDPR Legitimate Interest Assessment (LIA) — Guided assessment for Art. 6(1)(f) GDPR using the EDPB three-step test. Based on EDPB Guidelines 1/2024, EDPB Opinion 28/2024 (AI models), the OSS Case Digest on Legitimate Interest (McIntyre 2026), CNIL AI guidance (June 2025), ICO guidance, and key CJEU case law. Use when: (1) user needs to assess whether legitimate interest is appropriate, (2) user asks about Art. 6(1)(f), "Interessenabwägung", "berechtigtes Interesse", "balancing test", or "LIA", (3) user wants to document a legitimate interest assessment, (4) user mentions the three-step test, (5) user evaluates necessity or proportionality under Art. 6(1)(f), (6) user discusses direct marketing, fraud prevention, IT security, employee monitoring, AI training, web scraping, or credit checks in context of legal basis, (7) user handles a right to object (Art. 21), (8) user asks about children's data, profiling, or cross-border data sharing under legitimate interest, (9) user compares legitimate interest against other legal bases. Do NOT use for: consent assessments (Art. 6(1)(a)), contract performance (Art. 6(1)(b)), DPIA workflows, or pure ePrivacy/cookie compliance questions — though the skill does address the ePrivacy/GDPR overlap where relevant.

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。

Performs structured compliance review, clause redlining, and drafting suggestions for legal documents (privacy policies, data processing agreements, vendor and SaaS contracts) against India's DPDPA 2023 and the EU GDPR. Flags clauses as compliant, at-risk, or non-compliant with reasoning, and proposes ready-to-use model replacement language.

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Analyze any OFAC or OFSI enforcement action — by URL, pasted text, or uploaded document — and produce a structured root cause analysis as a formatted Excel (.xlsx) spreadsheet. Use this skill whenever a user names, links to, pastes, or uploads an OFAC or OFSI enforcement action and asks for any of the following: root cause analysis, compliance gaps, what went wrong, lessons learned, organizational self-assessment, or remediation planning. Also trigger when a user asks "analyze this enforcement action", "what were the root causes", "turn this into a checklist", or "how do I make sure this doesn't happen to us". Outputs a single-sheet .xlsx table with six columns: Root Cause | What Went Wrong | How It Went Wrong | What Could Have Stopped It | Is my organization immune to this? (Yes/No/Partial) | Notes.

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 and operationalize implementation readiness for high-risk AI systems under the EU AI Act Annex III, including provider and deployer obligations, conformity assessment, post-market monitoring, and EU database registration. Use when users say things like “we classified this as high-risk, what now?”, “build an EU AI Act readiness plan”, “assess our Annex III compliance gaps”, “what do providers/deployers of high-risk AI need to implement?”, “prepare for conformity assessment”, or “create a high-risk AI implementation roadmap.”

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。