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Search, retrieval, and analysis of EU legal acts, as well as Polish legislation and draft laws implementing EU regulations (e.g. PPWR, CBAM, EUDR, ESPR, CSRD, CSDDD, GPSR, the AI Act, batteries, and ecodesign). Use when the user needs information on legal status, application dates, transitional provisions, relationships between legal acts, compliance obligations, and a report supported by legal bases and official sources.

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.

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.

This skill builds a structured audit trail of an AI-assisted task: what the tool was asked to do, what materials it was given, what it produced, how the output was verified, and what was ultimately relied upon. It documents the workflow for supervision and later review without ruling on privilege or disclosure, so the record stays accurate rather than self-serving.

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.

Authoritative regulatory Q&A grounded in 70 official EU source documents, including the 2026 Commission draft guidelines on Art. 6 high-risk classification. Answers any EU AI Act question with article-level citations from the full regulation text, Commission guidelines, EDPB/EDPS opinions, codes of practice, harmonised standards, FRIA guides, and sector-specific guidance — covering penalties, timelines, GPAI obligations, high-risk and prohibited practices, and the AI Act / GDPR interplay.

Depth assessment of whether an AI system is high-risk under Art. 6 of the EU AI Act, grounded in the Commission's draft Art. 6(5) classification guidelines (general principles + Annex I + Annex III). Covers the Annex I product-safety route, all eight Annex III areas with worked examples, the Art. 6(3) exception and its profiling re-exception, and the Art. 25 quasi-provider trap. Outputs a structured decision block, a practitioner memo, and a JSON interchange artefact.

Real-time individual screening across 30+ official lists (UN, EU, OFAC, OFSI, French DGT...), sectoral analysis, dual-use goods (EU Reg. 2021/821), US/China extraterritorial regimes (EAR, ITAR, FDPR, ECL), USD/SWIFT risk and jurisdictional mapping across 30+ countries.

Comprehensive guidance on compliance with Central Bank of Brazil regulations: CMN Resolution No. 4,893/2021 (Cybersecurity Policy), BCB Resolution No. 85/2021 (GRSIC), Open Finance Brazil (BCB Resolutions No. 32/2020 and updates), and other BACEN prudential rules. Covers drafting and reviewing Cybersecurity Policies, Incident Action and Response Plans (PARI), Information and Communication Services Risk Management (GRSIC), consent and data sharing in Open Finance, API requirements, third-party management (outsourcing), and BACEN sanctions. Triggers: Bacen, Central Bank, CMN 4,893, Resolution 4,893, banking cybersecurity, PARI, GRSIC, Open Finance, Open Banking, financial data sharing, Open Finance consent, financial API, banking outsourcing, cyber risk, bank cyber incident, financial LGPD, fintech compliance, financial institution, DICT, Pix security.

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.

This skill helps you apply the NIST AI Risk Management Framework and can quote AI RMF subcategories and GenAI profile action IDs verbatim from NIST AI 100-1 and 600-1. The skill routes you to the correct category as needed and has three modes, picked automatically from your question: 1. Consult: “What should I do per the AI RMF for this system?” 2. Governance Plan: “What should our AI governance program include?” 3. Assessment: “Run a full AI RMF aligned impact assessment for this system.” It knows the difference between the Core and the GenAI overlay, and won’t dump profile actions on a classifier or recommender.

PageRank-based jurisprudential authority analysis for Argentine case law (CSJN, federal courts). Peer-reviewed methodology published in JCLLT (DOI: 10.47852/bonviewJCLLT62027951). Ranks precedents by citation network influence with temporal decay.

A working tool for lawyers advising on the EU Data Act (Regulation (EU) 2023/2854). Hand it the facts of a matter and it returns a classification memo, a drafting starter, a verbatim regulation lookup, an applied legal analysis, or a gap audit. Every output quotes verbatim from the bundled regulation and the European Commission's FAQ rather than paraphrasing from memory. Sixteen drafting templates cover what lawyers actually draft against: Art. 3(2) and 3(3) pre-contract notices, Art. 25 data-processing-service clauses, Art. 26, 28, and 29 public pages, the three-part trade-secret refusal pack, a safety and security restriction clause, and a third-party data-sharing request. Output goes to chat by default. A one-click Word export styled for client work is available after the chat answer, with a verified-as-of stamp and live EUR-Lex and FAQ links so currency is always visible on the page.

Pre-flight privilege and work-product check for legal AI prompts. Use when the user is about to send legal content to a third-party AI surface and wants to know whether the prompt risks blowing attorney-client privilege or work-product protection. Returns a SAFE/CAUTION/STOP band with cited factors, a discovery-impact line, and a redacted-safe rewrite.

Generate a spreadsheet of test entries — newly designated names from OFAC, OFSI, and EU sanctions lists plus deliberate variations of those names — to validate that a sanctions screening system catches fresh designations and is tuned to the right fuzziness threshold. Use this whenever the user asks for sanctions list update test data, screening regression test data, screening QA, fuzzy match calibration, or wants to verify their screening lists are current. Trigger even if the user doesn't say 'screening' explicitly — phrases like 'test my sanctions list', 'check our SDN coverage', 'is my list up to date', or 'build me a regression set from the latest designations' should also invoke this skill.

Generates standalone interactive HTML "deal cards" that translate complex regulations into negotiation-ready reference tools, systematically distinguishing mandatory obligations from negotiable implementation choices. Use when the user needs an interactive regulatory guide for (1) contract negotiation support, (2) client education or internal training, (3) regulatory briefings for commercial stakeholders, or (4) structured comparison between required and flexible compliance paths. Primary focus on EU digital regulation (Data Act, AI Act, CRA, DORA, NIS2, GDPR) but the structural pattern transfers to any regulation where separating hard obligations from implementation choice is the point. Supports bilingual output where the jurisdiction calls for it.

Analyzes how multiple regulations interact for a specific product, service, or business model. Identifies where obligations overlap, reinforce, complement, duplicate, or conflict; builds a priority matrix; produces an integrated compliance timeline; and estimates the total compliance burden. Use when (1) scoping a new product or service against the full regulatory landscape before launch, (2) conducting M&A due diligence on a target's multi-regulation exposure, (3) building a strategic compliance roadmap where single-regulation analyses miss the interactions, (4) advising on complex situations where regulations touch the same conduct from different angles, or (5) estimating budget and resourcing for multi-regulation compliance. Primary coverage of EU digital regulation (GDPR, Data Act, AI Act, CRA, NIS2, DORA, DMA, DSA, ePrivacy) and national implementations; the framework extends to any jurisdiction where overlapping regulatory regimes apply to the same activity.

Outil d'analyse des sanctions économiques internationales et du contrôle des exportations pour Claude Desktop. Screening individuel en temps réel sur 30+ listes officielles (ONU, UE, OFAC, OFSI, DGT France...), analyse sectorielle, biens à double usage (Reg. UE 2021/821), régimes extraterritoriaux US/Chine (EAR, ITAR, FDPR, ECL), risque USD/SWIFT et cartographie de 30+ juridictions. Résultats sourcés et vérifiés en temps réel — aucune réponse de mémoire. Répond en français, anglais, allemand, espagnol, russe et chinois. Mis à jour au 19 mai 2026 (20ème paquet UE, SEUC UK, EO Cuba). Outil indicatif — ne se substitue pas à un avis juridique.

Assess compliance obligations under the EU Data Act (Regulation (EU) 2023/2854) for connected products, IoT devices, data sharing, cloud switching, B2B fairness, B2G data access, dispute resolution, and international data transfers. Covers scope assessment (manufacturer, data holder, data recipient roles), user data access rights, pre-sale transparency, unfair contract terms, public authority data requests, cloud portability, dispute settlement mechanisms, international transfer restrictions, access-by-design obligations, trade secret protection, and cross-regulation mapping with GDPR, AI Act, and CRA. Use when assessing Data Act obligations, designing connected products, drafting data sharing contracts, responding to B2G requests, planning cloud switching capabilities, or evaluating dispute resolution options.

Serious Incident Reporting (SIR) for high-risk AI systems under Article 73 EU AI Act (Regulation (EU) 2024/1689). Assess, qualify, draft, and submit Art. 73 SIR notifications across the four Art. 3(49) harm categories (death or serious health damage, critical infrastructure disruption, breach of fundamental rights, property or environmental damage). Covers Art. 73 immediate, 2/10/15-day reporting windows, market surveillance authority notification, deployer duties under Art. 26(5), and cross-regulation mapping with GDPR Art. 33/34 breach notification, NIS2 Art. 23 incident reporting, DORA Art. 19 ICT incident, and MDR vigilance. Built for in-house counsel and AI risk teams handling AI incidents, building AI incident response playbooks, or managing AI failure, AI bias, or automated decision incidents. DACH routing through German market surveillance (BNetzA, BaFin, BSI, BfArM, KBA). Pairs with the EU AI Act System Classifier, High-Risk Readiness, FRIA, and GPAI Code of Practice skills.

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.”

Assess whether a Fundamental Rights Impact Assessment (FRIA) is required under Article 27 EU AI Act, and structure or draft that assessment for a specific high-risk AI deployment. Covers deployer scope gating (public bodies and private entities providing public services), affected group mapping, Charter rights analysis, proportionality, safeguards evaluation, residual risk, DPIA/FRIA interaction, notification under Article 27(3), and DACH-specific considerations. Use when asked about FRIA obligations, Article 27 scope, fundamental rights and AI, or deployer assessment duties.

Structured NIS2 compliance assessment covering scope classification (Annex I/II, size thresholds, DORA/CIR checks), gap analysis across all 10 Art. 21 risk management measures with 0–4 maturity scoring and ISO 27001 references, and a prioritized compliance roadmap. Deep German BSIG-neu coverage (BSI registration, § 30/32/38, incident reporting, Nachweispflicht) plus high-level jurisdiction profiles for Italy, France, Netherlands, Austria, and Spain. Built on ENISA guidance and BSI #nis2know packages.

Assess compliance with the EU General-Purpose AI (GPAI) Code of Practice under the AI Act (Regulation (EU) 2024/1689), Articles 51-56. Covers GPAI model identification (Art. 3(63)), systemic risk model designation (Art. 3(65), Art. 51, 10^25 FLOP training compute threshold), upstream provider obligations under Art. 53 (transparency, technical documentation, copyright policy, training data summary), additional systemic risk obligations under Art. 55 (model evaluation, adversarial testing, AI Office incident notification, cybersecurity), systemic-risk notification and Commission designation under Art. 52, downstream Art. 25 quasi-provider duties, and Art. 53(2) open-source exemption. Built for in-house counsel and AI governance teams reviewing LLM or foundation model deployments, drafting GPAI compliance plans, or assessing systemic risk thresholds. DACH: BaFin, BSI, BNetzA. Pairs with the EU AI Act System Classifier, High-Risk Readiness, FRIA, and Serious Incident Reporting skills.