Claude Code plugins
5,175 plugins from public Claude Code marketplaces. Each one bundles skills, slash commands, agents, hooks or MCP servers that install together.
5,175 plugins from public Claude Code marketplaces. Each one bundles skills, slash commands, agents, hooks or MCP servers that install together.
Submit the repo with .claude-plugin/marketplace.json and we list every plugin.
Submit marketplaceAssesses 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.
Use when a lawyer, legal team, or client needs to assess AI agents that can act on someone's behalf: send messages, search, draft, file, pay, delete, connect to accounts, use tools, or rely on external data. Produces a practical delegation, oversight, accountability, and control audit for legal operations.
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.
Audits AI-assisted legal, compliance, governance, and institutional decisions before reliance to determine whether the responsible human or institution has enough access to the evidence, reasoning basis, uncertainty, authority, and review path to genuinely own the decision rather than merely approve, sign, or transmit it.
Audits legal AI outputs, prompts, skills, workflows and MCP/tool instructions for fluent but unsupported reasoning, missing evidence, overconfidence, hidden assumptions, weak causal links and absent human-review gates.
Audits legal AI outputs and workflows for honest compression: unnecessary complexity, false simplicity, excessive caveats, hidden uncertainty and poor cost per legally acceptable output.
Audits the transition from legal AI output to reliance, recommendation, execution, or real-world commitment. Use it before an AI-generated analysis, memo, contract review, compliance finding, or workflow output is acted upon to check whether authority, evidence, mandate, uncertainty, procedure, and review conditions remain sufficient.
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.
Post-hoc verification and trust audit of AI-generated factual and interpretive claims. Classifies claims by type and salience, routes them to domain-appropriate sources, scores trustworthiness on a tiered scale with an Interpolated verdict for plausible-but-unsupported detail, and assesses rhetorical fairness on interpretive claims. Designed with a focus on healthcare law in England and Wales, but with general applicability beyond.
Adversarial verification for AI-generated legal content with systematic fact-checking, source validation, and quality control. Use when verifying legal documents, fact-checking regulatory content, performing red team review, or quality assurance before distribution to clients or stakeholders.
Forces Claude to answer only from user-provided materials and online sources it has actually accessed. No inference, no assumptions, no gap-filling. Every factual, legal, numerical, or procedural claim must be anchored to a cited source, with statements categorised as expressly stated, verified online, supported, not found, or labelled inference. Built for legal and evidential work where fidelity to the record matters more than completeness.
Orientação completa sobre conformidade com regulamentações do Banco Central do Brasil: Resolução CMN nº 4.893/2021 (Política de Segurança Cibernética), Resolução BCB nº 85/2021 (GRSIC), Open Finance Brasil (Resoluções BCB nº 32/2020 e atualizações), e demais normas prudenciais do BACEN. Cobre elaboração e revisão de Política de Segurança Cibernética, Plano de Ação e Resposta a Incidentes (PARI), Gestão de Riscos de Serviços de Informação e Comunicação (GRSIC), consentimento e compartilhamento de dados no Open Finance, requisitos de API, gestão de terceiros (outsourcing) e sanções do BACEN. Triggers: Bacen, Banco Central, CMN 4.893, Resolução 4.893, segurança cibernética bancária, PARI, GRSIC, Open Finance, Open Banking, compartilhamento de dados financeiros, consentimento Open Finance, API financeira, outsourcing bancário, risco cibernético, incidente cibernético banco, LGPD financeira, fintech compliance, instituição financeira, DICT, Pix segurança.
Use when a calculator, financial model, investor memo, due diligence report, risk review, dashboard, or client-facing explanation needs clear distinctions between accounting and finance concepts such as cash flow vs profit, EBIT vs EBITDA, CapEx vs OpEx, debt vs equity, market value vs book value, ROI vs ROE, assets vs liabilities, and accounting vs finance.
An end-to-end method for drafting and finalising a complex, multi-pillar regulated fintech agreement — from intake to signature. Authored from a senior fintech lawyer's manual: a licensed payment-services provider engaging a counterparty across agent cash-in/cash-out, QR payments, wallet e-payments, and a marketplace, each with its own regulatory profile. Runs five phases and fourteen steps: regulatory mapping (activity-to-licence matrix, grey-zone classification gates), architecture (framework-plus-sub-agreement structure, ring-fenced marketplace), the regulatory–commercial balance (what flexes vs what cannot), core drafting (authority, float mechanics, hard-coded regulator caps, liability — all tracking control), execution-blocker triage, and a pre-signature check closing open blockers as conditions precedent. It refuses to invent licence-specific values or draft a representation as true without executed evidence. Use it to structure, draft, negotiate, or review any regulated payment
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.
Analyses contracts for risk across five critical clauses (Limitation of Liability, Indemnities, IP Ownership, Data Protection, Termination). Built for founders with no legal background. Flags red flags, explains risks in plain language, and provides negotiation guidance.
Use this skill when asked to review, analyze, or draft a contract governed by Icelandic law. Triggers on requests involving Icelandic commercial agreements, consumer contracts, sales agreements, service contracts, or any contract where Icelandic mandatory rules may apply.
Screen incoming NDAs and classify them as GREEN (standard), YELLOW (needs review), or RED (significant issues). Use when a new NDA comes in from sales or business development, when assessing NDA risk level, or when deciding whether an NDA needs full counsel review.
Reviews incoming one-way (unilateral) commercial NDAs in a jurisdiction-agnostic way, from either a Recipient or Discloser perspective (user-selected), producing a clause-by-clause issue log with preferred redlines, fallbacks, rationales, owners, and deadlines.
Review contracts against your organization's negotiation playbook, flagging deviations and generating redline suggestions. Use when reviewing vendor contracts, customer agreements, or any commercial agreement where you need clause-by-clause analysis against standard positions.