「2026」の検索結果

Pick the right LLM for LEGAL RESEARCH & ANALYSIS — issue-spotting, rule application, case/statute analysis, memos, and multi-step agentic research. Vendor-neutral routing grounded in mid-2026 benchmarks (Vals AI LegalBench across 124 models; Harvey Legal Agent Benchmark for agentic work). Asks up to 4 quick questions (cost, speed, accuracy/stakes, privacy/jurisdiction/language), then recommends a primary model + fallback + what to avoid + what a human must verify. Use when someone asks "which model for legal research / case analysis / a memo", "best AI for legal reasoning", "route this research task", or is starting legal analysis without a fixed model.

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Pick the right LLM for LEGAL TRANSLATION — translating contracts, statutes, case law, and legal correspondence across languages, including Arabic/MENA. Vendor-neutral routing triangulated from mid-2026 evidence (WMT25 human eval, SwiLTra-Bench legal-MT, multilingual-reasoning proxies, ArabLegalEval). There is NO clean legal-translation leaderboard, so this vertical is directional and treats human legal-linguist review as mandatory. Asks up to 4 quick questions (language pair, cost, speed, privacy/certification), then recommends a primary model + fallback + what to avoid + what a human must verify. Use when someone asks "which model to translate this contract/statute", "best AI for legal translation", "translate this legal doc to/from Arabic", or is about to machine-translate legal text without a fixed model.

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Pick the right LLM for CONTRACT REVIEW — reviewing an existing agreement for risk, deviations from standard, missing protections, and internal contradictions, and proposing redlines. Vendor-neutral routing grounded in mid-2026 legal benchmarks. Contract review is a COMPOSITE skill (extraction + reasoning + redlining + conflict-detection), so this routes by the dominant sub-task. Asks up to 4 quick questions (cost, speed, accuracy/stakes, privacy/jurisdiction/ language), then recommends a primary model + fallback + what to avoid + what a human must verify. Use when someone asks "which model to review this contract / NDA / MSA", "best AI to redline", "route this contract review", or is about to review an agreement without a fixed model.

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Pick the right LLM for LEGAL INFO EXTRACTION — pulling facts, clauses, dates, parties, obligations, and structured fields out of contracts and legal documents. Vendor-neutral routing grounded in mid-2026 benchmarks (legalbenchmarks.ai Info Extraction; CUAD/MAUD/ACORD). Asks up to 4 quick questions (cost, speed, accuracy/stakes, privacy/jurisdiction/language), then recommends a primary model + fallback + what to avoid + what a human must verify. Use when someone asks "which model should I use to extract clauses/data from these documents", "best AI for contract data extraction", "route this extraction task", or is about to pull structured fields from legal docs without a fixed model.

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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.

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Pick the right LLM for CONTRACT DRAFTING — generating, redlining, or rewriting contract language from instructions. Vendor-neutral routing grounded in mid-2026 legal benchmarks (legalbenchmarks.ai Contract Drafting). Asks up to 4 quick questions (cost, speed, accuracy/ stakes, privacy/jurisdiction/language), then recommends a primary model + fallback + what to avoid + what a human must verify. Use when someone asks "which model should I use to draft this clause/agreement", "best AI for drafting contracts", "route this drafting task", or is about to generate/redline contract text and hasn't fixed a model.

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Sanctions and export control analysis tool for Claude Desktop. 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. All results sourced and verified in real time — no memory-based answers. Responds in French, English, German, Spanish, Russian and Chinese. Updated 19 May 2026 (EU 20th package, UK SEUC, Cuba EO). Indicative guidance only — not legal advice.

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Routes any legal task to the right LLM, like OpenRouter but for legal work and grounded in benchmarks instead of brand loyalty. Built from mid-2026 legal evals (legalbenchmarks.ai, Vals AI × Stanford LegalBench across 124 models, Harvey's Legal Agent Benchmark, the Atticus Project's CUAD/MAUD/ACORD) plus translation evidence (WMT25, SwiLTra-Bench, ArabLegalEval). Covers five verticals: contract drafting, info extraction, legal research, contract review, and legal translation (including Arabic/MENA). Each asks up to four questions (cost, speed, accuracy/stakes, privacy/jurisdiction/language), then returns a primary model, a fallback, what to avoid, and what a human must verify. Core principle: capability is not controllability, so every route ends with a verification step. Not legal advice; a lawyer owns the output.

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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.

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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.

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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.

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EU AI Act Knowledge Engine — authoritative regulatory Q&A grounded in 70 official EU source documents (including the 2026 Commission draft guidelines on Art. 6 high-risk classification — general principles, Annex I, Annex III). Answers any question about the AI Act with article-level citations from the full regulation text, Commission guidelines, EDPB/EDPS opinions, codes of practice, harmonised standards, FRIA guides, incident templates, and sector-specific guidance. This skill should be used when the user asks about the "EU AI Act", "AI Act regulation", "Regulation 2024/1689", "KI-Verordnung", asks to "explain an AI Act article", "what does Article X say", "AI Act requirements", "AI Act penalties", "AI Act timeline", "GPAI obligations", "high-risk AI", "prohibited AI practices", "AI Act and GDPR", "fundamental rights impact assessment", "AI Act standards", "AI Act national implementation", "AI literacy", "serious incident reporting", "Digital Omnibus", "AI regulatory sandbox", or any question about EU artificial intelligence regulation. Also triggers on German terms: "KI-Gesetz", "KI-Verordnung", "Hochrisiko-KI", "KI-Kompetenz", "Grundrechte-Folgenabschaetzung", "GPAI-Verhaltenskodex". For assessment workflows that produce a classification decision rather than a knowledge answer, offer to run a structured risk-tier classification in-session.

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Claude skill that turns Claude into a Connecticut-specific divorce planner — nine operating modes from pre-flight intake to post-judgment modification, modeled on Untangle.us's feature surface and grounded in C.G.S. Title 46b, Practice Book Chapter 25, and the 2026-08-01 CCSG schedule. Covers eligibility triage (nonadversarial under § 46b-44a vs standard), financial affidavit (JD-FM-6), child support (JD-FM-220 / CCSG-1 / 1A), alimony (§ 46b-82 fourteen factors), parenting plan (with GAL/AMC escalation under JD-FM-224), settlement agreement (JD-FM-172, TCJA-aware), filing packet (marshal 12-day rule, $360 + $50 fees, JD-FM-75 waiver), and post-judgment motion practice. Hard UPL gate: refuses non-CT, domestic violence (refers CTCADV 1-888-774-2900), hidden assets, courtroom advocacy. Heppner-aware: AI prompts are not privileged. First family-law skill in the Lawvable registry.

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Upscale and restore video in ComfyUI. Both the quick local path (per-frame ESRGAN like 4x_foolhardy_Remacri via ImageUpscaleWithModel + 4x→2x supersample, with its temporal-flicker tradeoff) and temporal-aware super-resolution (SeedVR2, the newer FlashVSR) with the downscale-first restore pipeline; RIFE/FILM frame interpolation via the BUILT-IN ComfyUI 0.26 FrameInterpolate (rife_v4.26 in models/frame_interpolation/) or the ComfyUI-Frame-Interpolation pack; 2x/4x scaling, VRAM tiers, VHS encode. Captures the classic downscale→SeedVR2→RIFE recipe and the current 2026 recommendation.

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Security category index for Apple platforms. Routes to the privacy-manifests skill. General secure-storage/biometrics/ATS guidance was retired in the 2026 blind-test audit — current models cover it natively.

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Interface copy that works — voice/tone, the PACE framework, alert anatomy, naming features, empty states, error messages, and the small-word edits that measurably improve UX. Distilled from Apple's writing sessions (2017–2026). Use when writing or reviewing any user-facing text — labels, alerts, onboarding, notifications, empty states, paywalls — or naming a feature.

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Build a near-complete company list for any ICP by learning how your real customers label themselves, pulling every industry and keyword they use, judging every single row with a cheap AI model (Jev or gpt-5-nano), and running a Claygent lookalike loop until it runs dry. The method from the SCULPT 2026 talk "Build the perfect company list". Use when a database filter feels too narrow or too noisy, when someone says "find every company like our customers", "our TAM looks too small", or "why is this list full of junk".

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Orchestrate the full PaperOrchestra (Song et al., 2026, arXiv:2604.05018) five-agent pipeline to turn unstructured research materials (idea, experimental log, LaTeX template, conference guidelines, optional figures) into a submission-ready LaTeX manuscript and compiled PDF. TRIGGER when the user asks to "write a paper from my experiments", "turn this idea and these results into a paper", "generate a conference submission", "run paper-orchestra on X", or otherwise wants the end-to-end paper-writing pipeline. Coordinates the outline-agent, plotting-agent, literature-review-agent, section-writing-agent, and content-refinement-agent skills.

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Dung khi da co MOT master design va can ra du kich thuoc cho tat ca kenh — bang kich thuoc chuan 2025-2026 cho feed, story, reel, cover, placement ads; 3 cach xu ly scale-crop, re-compose, rebuild; quy tac safe zone va cach dat ten file. Kich hoat khi user nhac 'resize asset', 'du kich thuoc', 'adapt kich thuoc', 'bang kich thuoc chuan', 'safe zone', 'anh bi cat mat chu tren story', 'mot anh dang duoc may cho'. Khong dung cho — thiet ke moi tu concept thi dung skill 42-brief-hinh-anh; asset gap khi campaign dang chay thi dung skill 48-quick-visual-brief; liet ke toan bo asset cua campaign thi dung skill 41-campaign-asset-list.

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한국 서비스용 처리방침·이용약관·회원가입 동의 모달·쿠키 배너 자동 생성. 개인정보보호법 §30, 2025.4.21 작성지침, 2026.3 개정법, 공정위 전자상거래 표준약관 10023호 반영. Next.js 13~16 프로젝트 대상.

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미국 CCPA/CPRA + 주요 주법(VCDPA·CPA·CTDPA·UCPA·ICDPA·KCDPA·RIDPA) 기반 Privacy Policy 자동 생성. 2026.1.1 CPPA 갱신 규정, Sensitive Personal Information, Do Not Sell/Share, ADMT 공개, GPC 브라우저 신호 대응. 캘리포니아 거주자 서비스·100K records 초과 서비스 대상.

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Make .NET projects compatible with Native AOT and trimming by systematically resolving IL trim/AOT analyzer warnings. USE FOR: making projects AOT-compatible, fixing trimming warnings, resolving IL warnings (IL2026, IL2070, IL2067, IL2072, IL3050), adding DynamicallyAccessedMembers annotations, enabling IsAotCompatible. DO NOT USE FOR: publishing native AOT binaries, optimizing binary size, replacing reflection-heavy libraries with alternatives. INVOKES: no tools — pure knowledge skill.

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Query 2021-2025 CUMCM school awards and 2026 forecasts, or assess a student's preparation distance from provincial and national awards using school history and prior modeling experience.

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根据用户的视频需求(场景、时长、音频、语言、平台限制、预算、是否需要本地部署/角色一致性等),从 16 个主流 AI 视频模型(12 商业 + 4 开源)中推荐最匹配的 1-3 个,并解释为什么。覆盖商业:Seedance 2.0、HappyHorse 1.0、Kling 3.0、Sora 2、Veo 3.1、**Gemini Omni**(2026-05 新)、Runway Gen-4.5/Aleph、Pika 2.5、Hailuo 02、Hunyuan Video 1.5、Wan 2.7、即梦 AI;开源:LTX-Video 0.9.7、Mochi 1、CogVideoX 5B、Higgsfield Soul。用于"用哪个 AI 视频模型好"、"Sora 还是 Kling"、"国内有什么模型"、"哪个免费"、"哪个支持中文"、"哪个能编辑已有视频"、"哪个能本地部署"、"哪个角色一致性最强"等触发场景。

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