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Expertise complète en droit français des étrangers, de l'asile et de la nationalité — entrée et visas, séjour (CESEDA livre IV, AES, étranger malade, regroupement familial, métiers en tension), éloignement et contentieux (OQTF, IRTF, rétention, référés, TA/CAA/CE), asile (OFPRA, CNDA, Dublin, CMA/ADA), nationalité et droits sociaux des étrangers (AME, PUMa, RSA, AAH, ASPA). Interroge en priorité trois connecteurs MCP complémentaires — OpenLegi (textes, jurisprudence administrative), LibreJustice (recherche sémantique tous ordres) et Legal Data Hunter (rétention/JLD, graphe de citations, statut de validité) — puis les sources officielles (Légifrance, ANEF, OFPRA, CNDA) et la doctrine associative (GISTI, Cimade, ADDE, Comede, Anafé). Déclencher dès qu'une question porte sur un étranger en France, même sans vocabulaire juridique — « papier de la préfecture », « récépissé périmé », « la CAF refuse le RSA » — et pour toute consultation, recours, note ou vérification de références dans ces matières.

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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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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.

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EU Data Act (Regulation (EU) 2023/2854) skill for lawyers. Use when the user asks about Data Act classification, drafting, lookup, analysis, or audit. Triggers include "Data Act", "Regulation 2023/2854", "connected product", "related service", "data processing service", "DPS switching", "Article 3(2) pre-contract", "Article 25 contract", "trade-secret handbrake", "international government access", "Chapter VI cloud switching", "Article 50 timeline", "FAQ Q22a", "data holder", "exportable data", "functional equivalence", "Art. 4(10) competing product", and similar EU Data Act phrases. The skill produces lawyer-style Word output and cites verbatim from bundled regulation and FAQ source texts.

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Expert India Digital Personal Data Protection Act, 2023 (DPDPA) compliance advisor. Use this skill whenever a user asks about the DPDPA, DPDP Act, DPDP Rules 2025, India data privacy law, Data Fiduciary obligations, Data Principal rights, Significant Data Fiduciary, Data Protection Board of India, consent under DPDPA, notice requirements, breach notification India, children's data India, cross-border data transfer India, India privacy compliance, DPDPA gap analysis, DPDPA vs GDPR, or any obligation under India's personal data protection framework. Also trigger for: "Section 6 consent", "Section 7 legitimate uses", "Section 9 children's data", "Section 10 SDF", "Section 16 cross-border", "Rule 6 breach notification", "Rule 13 SDF obligations", "Data Protection Board complaint", "verifiable parental consent India", "DPDPA compliance roadmap", or "India privacy law global company".

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AFA design, scope-to-fee matching, negotiation preparation, health check, and scope dispute assessment for in-house legal ops teams managing outside counsel arrangements. Design fee structures (fixed, capped, collar, blended, phased, success). Assess whether scope supports a proposed AFA. Prepare commercial positions for fee negotiations. Review existing AFAs against delivery data. Assess OOS claims and build dispute response. Trigger on: 'structure the fee', 'move off hourly', 'design an AFA', 'does scope support a fixed fee?', 'negotiate the fee', 'renegotiate the arrangement', 'is our AFA holding?', 'fee health check', 'cap is being approached', 'firm is claiming OOS', 'is this in scope?', 'is this OOS?', 'AI should reduce the cost', 'blended rate vs fixed', 'collar arrangement', 'phased fees'.

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.

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Les LLM écrivent du juridique qui ressemble à du juridique sans en être. Formules creuses, attributions vagues, hedging systématique, latin décoratif : un praticien repère ces tics en trois lignes. Un juge aussi. LawyerScrib est un skill pour Claude Code et Cursor qui nettoie ces traces. Il scanne 17 patterns typiques de l'écriture IA appliquée au droit français (conclusions, consultations, notes, mails, actes) et réécrit chaque passage pour retrouver le ton d'un avocat qui argumente, pas d'un modèle qui rédige. Le résultat : un texte engagé, précis, avec des références sourcées et une position claire. Pas un texte neutre qui "reste à disposition pour tout complément".

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。

Review, draft, or redline a Data Processing Agreement (DPA / Auftragsverarbeitungsvertrag / AVV) under Art. 28 GDPR, or prepare a Joint Controller Arrangement under Art. 26 GDPR. Supports bilingual output (DE/EN), both controller- and processor-side perspectives, and two review depths — quick (Art. 28(3)(a)–(h) coverage) and negotiation-grade (clause-by-clause risk scoring).

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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.

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Collaboration platform configuration methodology for legal matter sites. Site architecture, workflow identification, dashboard design, data quality governance, and user adoption for SharePoint, Teams, and equivalent platforms. M365 is the reference implementation — outputs are platform-agnostic enough to brief IT or build simple automations without becoming a Power Automate manual. Use when setting up a matter site, identifying workflows to automate, designing reporting dashboards, managing platform data quality, or driving user adoption. Trigger on: 'set up the matter site', 'configure SharePoint', 'build a dashboard', 'what should we automate', 'brief IT on this workflow', 'nobody is using the platform', 'data quality is poor', 'set up Teams channel', 'matter site structure', 'alerts and notifications', 'user training', 'platform governance', 'status dashboard', 'what workflows can we automate', 'matter site template'.

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。

Generate templated responses for common legal inquiries and identify when situations require individualized attention. Use when responding to routine legal questions — data subject requests, vendor inquiries, NDA requests, discovery holds — or when managing response templates.

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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.

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 the user wants an AI governance, legal-risk, privacy, compliance, procurement, or vendor-risk review of an internal AI use case, an AI product feature, an LLM workflow, or a third-party AI vendor. The skill asks intake and clarifying questions first when facts or evidence are missing, identifies required documentation and missing evidence, maps the use case to AI governance frameworks and applicable legal domains, and produces a preliminary or final governance review with scorecards, findings, owners, remediation actions, and follow-up questions.

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 set up, improve, or audit analytics tracking and measurement. Also use when the user mentions "set up tracking," "GA4," "Google Analytics," "conversion tracking," "event tracking," "UTM parameters," "tag manager," "GTM," "analytics implementation," "tracking plan," "how do I measure this," "track conversions," "Mixpanel," "Segment," "are my events firing," or "analytics isn't working." Use this whenever someone asks how to know if something is working or wants to measure marketing results. For choosing attribution models, comparing multi-touch/MMM/incrementality, or reconciling conflicting numbers across tools, see attribution. For A/B test measurement, see ab-testing.

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When you or another skill needs to fetch the content of a social media post by URL — tweet, X thread, LinkedIn post, Instagram post, TikTok video, Bluesky post, Reddit thread, Mastodon status, Threads post, Hacker News thread. Returns normalized structured data (author, posted_at, text, engagement counts, media URLs, replies if requested) regardless of platform. Tries strategies in order: direct API (Bluesky, Mastodon, HN, Reddit), agent-browser with modal dismissal (LinkedIn, X preview), Wayback Machine (older posts), paid APIs (ScrapeCreators / Apify — only if env keys present). Triggers on "/social-fetch <url>," "fetch this tweet," "fetch this post," "what does this LinkedIn say," "read this thread," "pull this post." Used by deep-research (citing specific posts), jab-hook (inspiration account analysis), business-brainstorm (competitor / operator commentary).

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Monthly CFO workflow for a company or agency — pull raw data from bank + payment processor + payroll + expense management, categorize and reconcile, compute end-of-month cash via transaction-sum method, update a scenario projector for forward forecasting, write the monthly snapshot report, surface decisions to leadership. Modes — monthly (default; the standing report), weekly (thin cash pulse), scenario (ad-hoc modeling in the projector), pickup (resume where the prior run left off). Anonymized team-scope sibling to personal-cfo (which handles personal household finances). Composes with company-brain (report gets stored + wiki-indexed there), toolify (wire company-specific data sources), loopify (schedule the monthly + weekly runs). Triggers on "/company-cfo," "/cfo," "monthly cash report," "do the CFO snapshot," "CFO monthly," "let's run CFO," "cash projection," "runway forecast," "monthly financials," "cash pulse."

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When you want to clean and reformat content (usually from your terminal) for pasting into Slack, Notion, Twitter/X, LinkedIn, email, GitHub, or plain text. Strips ANSI codes, box-drawing chars, terminal prompt artifacts, and applies destination-specific formatting. Default input is the system clipboard; default output is both the clipboard and a chat preview. Triggers on "/paste", "/paste [destination]", "clean this for X," "format for slack/notion/twitter/linkedin/email/github," "render as markdown," "paste-ready," "strip formatting," "make this copy-pastable." Default destination is plain. Also scans for secrets (API keys, tokens, .env values) and warns before copying anything sensitive.

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When you want to capture into, compile, query, lint, or connect your personal Second Brain. Wraps the Karpathy LLM Wiki schema (Obsidian or any markdown vault) — raw/ (unprocessed sources), wiki/ (AI-compiled interlinked topic pages), outputs/ (generated artifacts). Tool-agnostic in design but defaults to a vault at ${SECOND_BRAIN_VAULT:-$HOME/Documents/SecondBrain}/. Six modes — capture (drop something into raw/), compile (process unprocessed raw files into wiki pages, update INDEX.md), query (answer a question from the wiki, save to outputs/), lint (orphans / contradictions / stale / unprocessed raw / topic gaps), connect (suggest new wikilinks between pages), search (quick lookup). Triggers on "/second-brain," "/sb," "capture this," "save this to my brain," "compile the wiki," "process raw notes," "query my wiki," "ask my brain," "lint the wiki," "find connections," "search my notes." Complements deep-research (external corpus) — this is the internal corpus.

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Expert blueprint for TileMapLayer and TileSet systems for efficient 2D level design. Covers terrain autotiling, physics layers, custom data, navigation integration, and runtime manipulation. Use when building grid-based levels OR implementing destructible tiles. Keywords TileMapLayer, TileSet, terrain, autotiling, atlas, physics layer, custom data.

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Expert blueprint for save/load systems using JSON/binary serialization, PERSIST group pattern, versioning, and migration. Covers player progress, settings, game state persistence, and error recovery. Use when implementing save systems OR data persistence. Keywords save, load, JSON, FileAccess, user://, serialization, version migration, PERSIST group.

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Expert blueprint for data-oriented design using Resource/RefCounted classes (item databases, character stats, reusable data structures). Covers typed arrays, serialization, nested resources, and resource caching. Use when implementing data systems OR inventory/stats/dialogue databases. Keywords Resource, RefCounted, ItemData, CharacterStats, database, serialization, @export, typed arrays.

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Expert blueprint for player mortality loops: progress-index checkpoints, soul graves, ghost/spirit layers, I-frame restitution, world-progress persistence, and death analytics. Use when implementing respawn, shrine checkpoints, corpse-run retrieval, or second-chance mechanics. Keywords revival, respawn, checkpoint, soul grave, ghost mode, I-frames, death analytics, progress index.

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Expert blueprint for fighting games including frame data (startup/active/recovery frames, advantage on hit/block), hitbox/hurtbox systems, input buffering (5-10 frames), motion input detection (QCF, DP), combo systems (damage scaling, cancel hierarchy), character states (idle/attacking/hitstun/blockstun), and rollback netcode. Based on FGC competitive design. Trigger keywords: fighting_game, frame_data, hitbox_hurtbox, input_buffer, motion_inputs, combo_system, rollback_netcode, cancel_system, advantage_frames.

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。