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Expert Section 508 compliance advisor for US federal ICT accessibility. Use this skill whenever a user asks about Section 508, WCAG 2.0/2.1 AA for federal systems, VPAT or Accessibility Conformance Reports (ACR), accessibility audits, remediation planning, PDF accessibility, web or software accessibility, mobile accessibility, federal procurement accessibility requirements, contractor obligations, undue burden exceptions, assistive technology compatibility, or Section 508 testing. Covers the Revised Section 508 Standards (2018), all WCAG 2.0 Level AA success criteria, the four POUR principles, testing methodologies, and agency compliance workflows. Trigger even if the user doesn't say "skill" — any Section 508 or ICT accessibility question for federal systems should use this skill.

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Reviews or drafts the agreement that pays an employee to settle their claims — and flags the statutory conditions that decide whether it actually binds them. Works under s.203 ERA 1996 for England & Wales. Flags apparent s.203 condition gaps for a solicitor to confirm (writing, specific complaints, independent adviser, identification, insurance, statement of conditions), drafts the substantive terms (sum, tax characterisation, confidentiality, references, restrictive covenants, indemnities), and surfaces enforceability risks. Does not rule on validity and is not legal advice. Use when the user says 'review this settlement agreement', 'draft a settlement agreement', 'compromise agreement' (old term), or asks whether an agreement is binding.

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This skill stress-tests a proposed settlement position before an offer goes out or comes back: the assumptions it depends on, your leverage and the opponent’s, the evidential weaknesses, the likely opponent response, and the timing and costs pressures around it. It structures settlement judgment for a better-informed decision; it does not advise whether to settle.

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No Inference / Source-Locked Verification. Forces Claude to answer ONLY from user-provided materials and/or online sources actually accessed — no inference, no assumptions, no gap-filling. Every factual, legal, numerical, or procedural claim must be anchored to a cited source. Use whenever Claude reviews documents, summarises evidence, checks accuracy, drafts submissions, creates timelines, extracts facts, checks citations, analyses rules, prepares legal arguments, compares documents, verifies claims, produces chronologies, works from uploaded materials, performs legal research, checks case status, or does anything where evidential fidelity matters. Also trigger on: 'source-locked', 'no inference', 'only from the materials', 'don't assume', 'stick to the evidence', 'verify this', 'check this is right', 'work from the documents'. Overrides Claude's default tendency to fill gaps. If evidential accuracy matters, use this skill.

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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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Expert TSA cybersecurity compliance advisor for critical infrastructure owners and operators. Use this skill whenever a user asks about TSA Security Directives for pipelines, freight railroads, passenger rail, public transit, or bus operators; the TSA Cyber Risk Management Program (CRMP); Cybersecurity Implementation Plan (CIP); Cybersecurity Operational Implementation Plan (COIP); Cybersecurity Assessment Plan (CAP); incident reporting to CISA; designation of a Cybersecurity Coordinator; Critical Cyber Systems (CCS); OT/IT network segmentation; the TSA November 2024 NPRM; or any directive in the SD Pipeline-2021 series, SD 1580-21-01 (freight rail), or SD 1582-21-01 (public transit/passenger rail). Also trigger for questions like "are we covered by TSA directives?", "what does the TSA require for pipeline cybersecurity?", "how do I build a CIP?", "what must I report to CISA?", or any request involving transportation critical infrastructure cybersecurity compliance.

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Verifies UK case-law citations, pinpoint references and quotations against the official public register — The National Archives' Find Case Law — and statutory references against legislation.gov.uk, before a document that cites them is relied on, served or filed. Every check returns a graded verdict: VERIFIED, MISMATCH (the citation resolves to a different case — the classic AI miscitation), NOT ON REGISTER, OUTSIDE COVERAGE (the register cannot answer — absence proves nothing), or UNCHECKABLE (a law-report citation). The grading exists because there are two ways to get this wrong: citing a case that does not exist, and accusing a real case of not existing. Use when asked to check citations, verify a case exists, confirm a quotation is verbatim, check a pinpoint paragraph, audit a draft's authorities, screen a document for hallucinated cases, or check a statutory provision is in force. Not a substitute for reading the judgment: existence is not authority.

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Screens a dismissal — proposed or already done — against the unfair dismissal framework for England & Wales, and shows where it is exposed. Structures the qualifying-service question, the automatically-unfair categories (no qualifying period), and a Burchell / Polkey / band-of-reasonable-responses analysis for a solicitor to verify — it does not determine fairness. Surfaces specific procedural risks. Use when the user says 'is this unfair', 'screen this dismissal', 'ordinary unfair dismissal', 'automatic unfair dismissal', or wants a structured fairness review before or after dismissal.

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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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Expert NIST Cybersecurity Framework (CSF) advisor covering CSF 2.0 and CSF 1.1. Use this skill whenever a user asks about NIST CSF, cybersecurity risk management, the six CSF functions (Govern, Identify, Protect, Detect, Respond, Recover), CSF profiles, implementation tiers, gap assessments, organizational profiles, community profiles, CSF core subcategories, informative references, or mapping to other frameworks (NIST SP 800-53, ISO 27001, CIS Controls, COBIT). Also trigger for questions like "how do I implement NIST CSF?", "what does CSF 2.0 change?", "help me build a CSF profile", "how do I assess my cybersecurity posture?", or any request involving organizational cybersecurity risk strategy or framework alignment.

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Use this skill whenever a lawyer or mediator needs help analyzing a dispute for mediation purposes. This includes: reviewing case materials (pleadings, contracts, correspondence, evidence) to identify issues in dispute, summarizing each party's position and interests, conducting legal analysis of the key issues, proposing mediation strategies or settlement directions, and preparing for mediation sessions. Trigger this skill when the user mentions 'mediation', 'dispute analysis', 'settlement', 'dispute resolution', 'identify issues in dispute', 'party positions', 'mediation brief', 'case analysis for mediation', 'ADR', 'mediation preparation', 'caucus strategy', 'settlement options', or any request to analyze a conflict between two or more parties with the goal of finding resolution. Also trigger when the user uploads case files and asks for a structured breakdown of who wants what, what the core disagreements are, or how the case might settle. Even if the user doesn't explicitly say 'mediation', trigger when the context involves analyzing opposing positions in a dispute with a resolution-oriented (rather than litigation-oriented) goal.

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Matter scoping across the full pre-execution arc — organise client data into a structured brief, capture the agreed baseline, or reconstruct scope mid-flight. Use when making sense of client information before a proposal, scoping a new matter, running a kickoff, defining scope, mapping stakeholders, or inheriting a matter mid-flight. Trigger on: 'make sense of this', 'structure this for the proposal', 'scope this matter', 'new matter', 'kickoff', 'what are we doing', 'who are the stakeholders', 'what does success look like', 'matter setup', 'intake', 'I've inherited this matter', 'organise this client data'.

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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.

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Apply the NIST AI Risk Management Framework (NIST AI 100-1 + the NIST AI 600-1 Generative AI Profile) to a specific AI system, governance question, or impact assessment. Three modes — consult, governance plan, full assessment — all cite Subcategories (`GOVERN 1.1`) and Profile Action IDs (`GV-1.2-001`) verbatim. Use when the user mentions the AI RMF, NIST RMF, NIST AI 100-1, NIST AI 600-1, GenAI Profile, the four functions (Govern / Map / Measure / Manage), the trustworthy AI characteristics, the 12 GAI risks (confabulation, harmful bias, information integrity, CBRN, data privacy, etc.), or asks "what does NIST say about X" for an AI system.

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Expert NIST AI Risk Management Framework (AI RMF 1.0) advisor covering all four functions: GOVERN, MAP, MEASURE, MANAGE. Use this skill whenever a user asks about NIST AI RMF, AI risk management, AI trustworthiness, GOVERN function, MAP function, MEASURE function, MANAGE function, AI RMF Playbook, AI risk profiles, responsible AI, AI bias management, AI transparency, AI explainability, AI reliability, AI safety, NIST AI 100-1, AI risk assessment, AI incident response, or alignment to EU AI Act, ISO 42001, or NIST CSF via AI RMF. Trigger even if the user doesn't say "skill" — any NIST AI RMF or AI governance risk question should use this skill.

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Panel structure design, firm selection criteria, right-sourcing analysis, and coverage gap assessment for in-house legal teams. Build panel frameworks from scratch or formalise existing informal arrangements. Define weighted selection criteria for firm evaluation. Run right-sourcing analysis (ABC tiering) to identify work sent to expensive providers that doesn't require that level of resource. Assess existing panels for practice area, geographic, and capability gaps. Trigger on: 'design our panel', 'how many firms do we need', 'panel structure', 'firm selection criteria', 'which firms should we use', 'right-sourcing', 'are we sending work to the right firms', 'panel gaps', 'too many firms', 'consolidate our panel', 'we need a firm for', 'preferred provider', 'panel tiers', 'do we need BigLaw for this', 'convergence', 'D&I panel targets', 'how do we choose firms'.

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Detects prompt injection hidden in documents from the other side (pleadings, skeletons, bundles, served evidence, opponents' emails and attachments) before an AI reads them, so the model is not turned against your client. Checks word by word that the text an extractor hands the model was visibly drawn on the page: white, near-white, covered, clipped, off-page, tiny, transparent and invisible-mode text in PDF (ink test plus OCR); Word formatting resolved as Word does (styles, shading, theme colours, scaling, off-page frames, fallbacks, unused headers); HTML/CSS, RTF, email with attachments and zips, xlsx/pptx and legacy formats. Flags Unicode smuggling, text addressed to an AI and authorities found only in hidden text. Fails closed. Optional Read-tool hook. Use BEFORE any AI summary or analysis of an opposing or third-party document. Triggers: 'scan for injection', 'is this document safe', 'check the other side's skeleton', 'injection guard'.

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Expert ISO 27001 compliance assistant for security and compliance teams. Use this skill whenever a user asks about ISO 27001 or ISO/IEC 27001, including any of the following: gap analysis, auditing, compliance assessments, control checklists, policy writing, document generation, Statement of Applicability (SoA), risk assessment, risk registers, risk treatment plans, Annex A controls, ISMS implementation, clause requirements, certification readiness, transitioning from 2013 to 2022, control implementation guidance, incident response policies, access control policies, supplier security, or any information security management system (ISMS) topic. Trigger even if the user doesn't say "skill" — any ISO 27001 or ISMS question should use this skill.

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Expert ISO 42001 AI Management System (AIMS) compliance advisor. Use this skill whenever a user asks about ISO/IEC 42001:2023, AI governance, AI management systems, AI risk assessment, AI system impact assessment, Annex A controls for AI, Statement of Applicability for AI systems, AI policy, responsible AI, AI lifecycle management, AI incident management, AI transparency, AI bias, AI certification readiness, or any topic related to implementing or auditing an AI Management System. Also trigger for questions like "how do I become ISO 42001 certified?", "what controls does ISO 42001 require?", "how do I assess AI risk under 42001?", "what is an AIMS?", or any request involving organisational governance of AI systems, responsible AI frameworks, or AI regulatory compliance aligned to an ISO standard.

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Turns a legal question, a set of draft questions, or source material such as a statute, jury instruction, rubric, contract checklist, or coding manual into a battery of narrow questions that TypeSafe's Jev, a fast classifier that returns probabilities rather than prose, can answer reliably across many documents. The skill breaks conclusions such as negligence, felony murder, or standing into element-level questions, writes the governing rule into each question, and delivers the questions alone, in Jev's request format or in plain English. Built for legal work that asks the same questions of many texts: coding statutes across jurisdictions, coding opinions or case files for empirical research, checking contracts against a review checklist, screening intake narratives, and grading student work against a rubric. Use when asked to write Jev questions, build a classifier for legal documents, or turn a legal test into yes-or-no questions. Running the questions requires Jev access; writing them does not.

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Assesses a legal argument, submission, or piece of structured reasoning from the perspective of a judge reading it cold under time pressure. Produces a structured seven-part assessment: what the case appears to be about, immediate points of confusion, what feels strong, what feels weak, what is assumed but unproved, a provisional confidence level (low/medium/high), and what would be needed to persuade. The skill does not rewrite, improve, or attack the argument — it tells you how it actually lands on a sceptical, experienced reader with no prior context. Works on skeleton arguments, witness statements, letters before action, position statements, academic articles, and non-legal structured reasoning.

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 a legal document against legal design principles. Scores the document on six pillars: language patterns (bureaucratese, archaisms, passive voice, nominalization), readability (Flesch Reading Ease and language-specific equivalents), structure and navigation, hidden conditions (material obligations buried away from their headings), statutory duplication (restating the law instead of citing it), and visual hierarchy where layout is available. Assessment-only; does not rewrite the document. Works on English, French, and German documents, inferring the applicable jurisdiction from the document's language and textual signals: governing-law clause, statute citations, party addresses. Use when a user shares a legal document (contract, NDA, T&C, privacy policy, internal policy) asking how good the drafting is from a legal design perspective, whether it is readable, whether it contains buried clauses or restates the law, or how it scores on Flesch / LIX / Amstad / Kandel-Moles readability metrics.

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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.

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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.

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。