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Adversarial premortem for England & Wales civil litigation - builds the strongest version of a case, then attacks it from four angles to find where it loses before opposing counsel does. Runs an adversarial premortem on a UK litigation matter. Builds the strongest version of the case, then attacks it from four angles — procedural, substantive, evidentiary, strategic — to find where it actually loses. Returns a ranked stress-test brief: failure scenarios, evidence inconsistencies, blind spots, mitigations, and one brutal one-sentence verdict. Use before issue, before settlement negotiations, before a litigation-funder pitch, or before deciding whether to take a case.

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Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

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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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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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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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Toolkit for comprehensive Spreadsheet reading, creation, editing, and analysis with visual quality control. Use to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing tabular data, (3) Modifying existing spreadsheets while preserving formulas, (4) Building financial models with proper formatting, (5) Data visualization with in-sheet charts, or any other spreadsheet tasks.

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Elite incident response and legal compliance guidance for data breaches under GDPR Articles 33 & 34. Use when: (1) User reports a data breach or security incident — including "is this even a personal data breach?" triage, (2) User asks about breach notification obligations or deadlines, (3) User mentions "72 hours", Art. 33, Art. 34, or notification requirements, (4) Discussion involves security incidents affecting personal data, (5) User needs breach risk assessment using ENISA methodology, (6) User mentions "Data Breach" or "Incident" or "Data Leakage" or "Ransomware" or "Exfiltration", (7) User needs to determine Controller vs Processor obligations, (8) Cross-border breach scenarios requiring Lead SA determination, (9) User needs a mitigation playbook or immediate response recommendations, (10) User needs audit-ready breach documentation (.docx) or an EDPB-template-aligned breach notification / evidence file — including follow-up and withdrawal notifications, (11) Breach involves an AI system requiring AI Act Art. 73 serious incident screening.

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Export Administration Regulations (EAR, 15 CFR Parts 730-774) compliance advisor — ECCN classification across all 10 CCL categories and 5 product groups (A-E), EAR99 determination, jurisdiction analysis (EAR vs ITAR order of review), license requirement analysis via Country Chart, all license exceptions (LVS, GBS, CIV, TMP, RPL, GOV, TSU, ENC, TSR, APP, BAG, AVS, ACE), end-user/end-use controls (Entity List, Denied Persons List, Unverified List, MEU List), deemed export rules, Foreign Direct Product Rule (FDPR), de minimis thresholds, 10 General Prohibitions, SNAP-R license applications, voluntary self-disclosure, civil/criminal penalties, Export Compliance Program (ECP) design, and EAR vs ITAR jurisdiction determination. Use for any dual-use export control, CCL classification, or BIS compliance question.

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EU AI Act (Regulation (EU) 2024/1689) compliance advisor — risk classification across all four tiers, all 9 prohibited practices (Art. 5, including the nudification/CSAM prohibition from Dec 2, 2026), all 8 Annex III high-risk use case areas, provider and deployer obligations (Arts. 9–17, 26), GPAI model obligations including the July 2025 Code of Practice (Arts. 51–55), conformity assessment and CE marking (Arts. 43–48), EU AI database registration, Art. 50 transparency (chatbots, synthetic media, AI-generated content), governance (AI Office, AI Board), penalties (Art. 99), confirmed phase-in timeline (Digital Omnibus adopted June 29, 2026: Annex III deferred to Dec 2, 2027; Annex I to Aug 2, 2028), and cross-framework mapping to ISO 42001, NIST AI RMF, and GDPR. Use for any EU AI regulation, AI system classification, or AI compliance question. Current as of July 2026. GPAI enforcement powers activate August 2, 2026.

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GDPR Data Protection Impact Assessment (DPIA) guidance under Article 35 GDPR, EDPB Guidelines WP 248 rev.01, EDPB Opinion 28/2024 (AI), and national SA blacklists/whitelists. Triggers: "DPIA", "DSFA", "Datenschutz-Folgenabschätzung", "impact assessment", "Art. 35", "do I need a DPIA", descriptions of new high-risk processing (profiling, AI, biometrics, large-scale monitoring, special category data), Art. 36 prior consultation questions, national blacklist/whitelist queries.

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AI co-counsel for divorce and family-law attorneys — a jurisdiction-portable scaffold spanning the full matter lifecycle. Eight operating modes mirror how a matter actually moves: intake and onboarding, financial disclosure, children and support, property division and QDRO, discovery and document review, drafting, negotiation and mediation prep, and court prep — plus post-judgment modification and enforcement. The methodology is jurisdiction-agnostic: it forces real, verifiable research for every local form, formula, or rule rather than inventing one, handling common-law, community-property, civil-law, and MENA personal-status regimes as variables. Built around one non-negotiable: privilege. It drafts, analyzes, organizes, and pressure-tests. It is not the lawyer.

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When your bar comes asking "show me how you billed AI-assisted work" — and ABA 512, Florida 24-1, California, New York, and DC all have opinions out — you need an artifact that survives review. billable-time produces it. From your Claude Code session logs, it drafts reviewable time entries plus a printable HTML audit packet with: SHA-256 chain of evidence (source files + matter.yml + active disclosure pack + verifiable artifact self-hash), attorney identity and signature block, a bar-opinion disclosure pack with starter language for five jurisdictions, and content-aware deterministic narratives derived from filename and tool shape — never from prompt text by default. The tool refuses to bill on its own. --strict mode refuses to ship the artifact if any audit invariant fails (broad routes, missing attorney, missing/unverified disclosure). Comes as a Node CLI and a self-contained browser version (no backend; JSONL never leaves the page). 15 invariant tests verify the contract. AGPL-3.0.

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Contract intelligence and contract operations workflow skill for Claude and Codex. Guides the full contract lifecycle review process from intake and playbook normalization through clause review, deviation scoring, negotiation planning, approval routing, QA, and action recommendations. Reviews legal, business, operational, compliance, privacy, security, technology, and AI-related risks across contracts and legal documents. Supports NDAs, SaaS agreements, DPAs, procurement contracts, commercial agreements, contract comparisons, redlines, approval packages, clause research, and drafting. Warning-Comprehensive reviews can consume significant Claude/OpenAI tokens, especially for large agreements, playbooks, exhibits, schedules, and multi-document reviews.

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Adversarially stress-tests a legal text — a contract, statute, regulation, or judicial opinion — for interpretive ambiguity: it finds the seams where the people governed by it will later disagree about what it means and turns each into a concrete dispute scenario with both sides' arguments, the likely outcome, and a fix. Use it whenever someone wants to pressure-test, red-team, audit, or find weak spots, loopholes, gaps, ambiguities, or drafting problems in a legal document; whenever a drafter wants to tighten a contract, statute, regulation, or opinion before it issues; whenever a litigator wants to mine an opinion or contract for arguments; or whenever someone hands over a legal text and asks where it will be fought over or for issue-spotting. Trigger it for contract review, statutory-ambiguity analysis, judicial-opinion scope analysis, and drafting QA — even if the user never says "stress-test" or "ambiguity."

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Perform language and framework specific security best-practice reviews and suggest improvements. Trigger only when the user explicitly requests security best practices guidance, a security review/report, or secure-by-default coding help. Trigger only for supported languages (python, javascript/typescript, go). Do not trigger for general code review, debugging, or non-security tasks.

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California Consumer Privacy Act (CCPA) and California Privacy Rights Act (CPRA) compliance advisor — business threshold analysis, consumer rights fulfillment (access, delete, correct, opt-out of sale/sharing, limit SPI, ADMT opt-out), privacy notice drafting, service provider vs. contractor vs. third-party classification, sensitive personal information (SPI) handling, data minimization, opt-out mechanisms (including GPC), cybersecurity audits and risk assessments (live since Jan 1, 2026), ADMT obligations (effective 2026, deadline Jan 1, 2027), CPPA enforcement (Disney $2.75M, PlayOn $1.1M, Ford $375K), penalty exposure, GDPR comparison, and gap assessments for businesses operating in or targeting California residents.

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When the user wants to design, construct, or improve an offer — the thing they actually sell — including value framing, bonus stacking, guarantee design, scarcity/urgency, naming, and payment structure. Also use when the user mentions 'offer,' 'offer design,' 'build an offer,' 'grand slam offer,' 'irresistible offer,' 'value stack,' 'bonus stack,' 'guarantee,' 'risk reversal,' 'money-back guarantee,' 'scarcity,' 'urgency,' 'high-ticket offer,' 'productize a service,' 'naming an offer,' 'payment plan,' 'down-sell,' 'upsell offer,' or 'why isn't my offer converting.' Best for services, agencies, courses, coaching, info products, high-ticket B2B, and direct-response. If you run pure self-serve SaaS, read pricing first — tiers and packaging do more work there. For price level itself (tiers, freemium, value metric), see pricing. For the page that presents the offer, see copywriting. For the launch moment, see launch. For sales collateral, see sales-enablement.

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When the user wants to research, profile, or analyze competitors from their URLs. Also use when the user mentions 'competitor profile,' 'competitor research,' 'competitor analysis,' 'profile this competitor,' 'analyze competitor,' 'competitive intelligence,' 'competitor deep dive,' 'who are my competitors,' 'competitor landscape,' 'competitor dossier,' 'competitive audit,' or 'research these competitors.' Input is a list of competitor URLs. Output is structured competitor profile markdown files. For creating comparison/alternative pages from profiles, see competitors. For sales-specific battle cards, see sales-enablement.

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When you want to integrate an external tool, API, MCP server, or service into a project — the wizard walks you through auth, config, env vars, client wrapper code, example usage, and an optional smoke test. Scoped to Next.js and Rails projects. Interactive Q&A — starts with the tool name, asks structured questions until the integration is specified, then scaffolds files. Examples — Stripe, Kit, Sanity, Notion, Neon, Supabase, Resend, Postmark, Twilio, Anthropic, OpenAI, Vercel Blob, custom internal APIs. For MCP servers, also handles the .mcp.json wiring. Triggers on "/toolify," "integrate X," "add X to this project," "wire up X," "set up the X integration," "hook up X," "connect X," "add MCP for X." Part of the -ify trifecta (skillify / toolify / loopify). NOT for adding new SKILL.md files — that's skillify. NOT for cron/agent loops — that's loopify.

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ONVIF device security scanner for testing authentication and brute-forcing credentials. Use when you need to assess security of IP cameras or ONVIF-enabled devices.

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WS-Discovery protocol scanner for discovering and enumerating ONVIF cameras and IoT devices on the network. Use when you need to discover ONVIF devices, cameras, or WS-Discovery enabled equipment on a network.

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Expert blueprint for Godot 4 project organization (feature-based folders, naming conventions, version control). Enforces snake_case files, PascalCase nodes, %SceneUniqueNames, and .gitignore best practices. Use when starting new projects or refactoring structure. Keywords project organization, naming conventions, snake_case, PascalCase, feature-based, .gitignore, .gdignore.

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Expert patterns for managing combat waves, difficulty scaling, and automated enemy spawning in Godot 4. Use when building wave-based shooters, tower defense, or arena games.

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Expert blueprint for MOBA games including lane logic (minion wave spawning every 30s), tower aggro priority (hero attacking ally over minion over hero), click-to-move controls (RTS-style raycasting), hero ability systems (QWER cooldowns, mana cost), fog of war (SubViewport projections), and authoritative networking (server validates damage). Use for competitive 5v5 or arena games. Trigger keywords: MOBA, lane_manager, minion_waves, tower_aggro, click_to_move, ability_cooldowns, fog_of_war, comeback_mechanics.

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