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Create an Estuary derivation that flattens a nested array into one output document per array element. Use for normalising nested JSON, exploding line items, unpacking tags, or producing one-row-per-item tables from arrays. Derivations add complexity and cost — confirm the user wants a derivation before reaching for this (some destinations can `UNNEST` server-side without one). Use when user says "flatten-array derivation", "derivation to explode an array", "transformation to unnest", "derive one row per item", or "flatten nested data with a derivation".

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Foundation for writing Estuary derivations — what they are, language choice (SQL/TypeScript/Python), project layout, flowctl workflow, stateless vs stateful shuffling, and universal gotchas. Read this before any other derivation-* skill. Use when user says "write a derivation", "how do derivations work", "create a derivation", "derivation setup", or before starting any transformation work.

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Review whether every page provides an accessible privacy policy link, especially in the footer. Check that the policy explains data collection, use, sharing, retention periods, contact details, and user rights, and identify missing information.

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• Checking privacy policy links across all pages
• Adding a privacy policy link to a shared footer
• Reviewing data retention and sharing disclosures

Compare new or changed privacy regulations with current policies and practices. Identify whether the rules apply, list missing requirements, and produce a prioritized remediation plan with owners and due dates, documenting compliant areas as well.

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• Assess whether a new privacy law applies to the company
• Identify gaps between regulatory guidance and current practices
• Plan corrective actions with owners and deadlines

Prepare an internal Privacy Impact Assessment, a review of how a feature uses personal data. Check whether assessment is needed, examine legal grounds and policy commitments, and document specific risks, required actions, and owners in the team’s format.

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• Reviewing personal data use in a new feature
• Checking whether a privacy assessment is needed
• Comparing processing plans with privacy policy commitments

Compile and improve existing English or Chinese academic papers written in Typst. Check references, formatting, prose, argument flow, abstracts, tables, and pseudocode, with source-level review comments and support for adapting papers to another publication venue.

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• Diagnosing Typst compilation and export errors
• Validating BibTeX or Hayagriva references
• Reviewing abstracts and the logic of paper sections

Expert ISO 27701 Privacy Information Management System (PIMS) compliance advisor. Use this skill whenever a user asks about ISO/IEC 27701:2025, ISO/IEC 27701:2019, privacy information management, PIMS certification, PII controller or processor obligations, privacy risk assessment, Statement of Applicability for privacy, privacy by design, data subject rights, DPIA, records of processing activities, transitioning from ISO 27701:2019, GDPR alignment with ISO 27701, or any privacy management system topic. Also trigger for questions about Annex A.1 (controller controls), A.2 (processor controls), A.3 (shared security controls), or implementing a standalone PIMS without ISO 27001. When in doubt, use this skill — it covers the full ISO 27701 lifecycle from gap assessment through certification.

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A zero-hallucination privacy-policy generator that takes anyone — non-lawyer founder to lawyer — from a guided intake to a publishable, jurisdiction-aware privacy policy. Jurisdiction-first: it detects which laws apply from where your users are, then drafts only the required clauses — GDPR/EU + UK, US (CCPA/CPRA, ~20 state laws, COPPA, sector overlays), and global/MENA (LGPD, Quebec Law 25, India DPDP, China PIPL, UAE/DIFC, Saudi PDPL), plus app-store, cookies, and AI/EU AI Act disclosures. Its rule: state only what you confirm; never invent a statute, citation, fine, or date — every claim is source-cited and QA-gated. Not legal advice.

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Expert ISO 27701 Privacy Information Management System (PIMS) compliance advisor. Use this skill whenever a user asks about ISO/IEC 27701:2025, ISO/IEC 27701:2019, privacy information management, PIMS certification, PII controller or processor obligations, privacy risk assessment, Statement of Applicability for privacy, privacy by design, data subject rights, DPIA, records of processing activities, transitioning from ISO 27701:2019, GDPR alignment with ISO 27701, or any privacy management system topic. Also trigger for questions about Annex A.1 (controller controls), A.2 (processor controls), A.3 (shared security controls), or implementing a standalone PIMS without ISO 27001. When in doubt, use this skill — it covers the full ISO 27701 lifecycle from gap assessment through certification.

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Audits a website for compliance with Azerbaijan's Law on Personal Data No. 998-IIIQ and, where applicable, EU GDPR plus ePrivacy/cookie consent rules. Inventories the privacy documents present (privacy policy, cookie policy, cookie banner, consent flow, controller and DPO contact, data subject rights channel, cross-border transfer disclosures, AZ operator-registration references) and scores each against the applicable statutory requirements. Produces a dual-layer report: a plain-language traffic-light summary for business owners plus a clause-by-clause findings table with article-level citations for lawyers. Assessment-only — no drafting. Use whenever the user shares a URL or privacy/cookie policy text for an AZ-based or AZ-targeted site; also when the user mentions an .az domain, Law 998, the AZ State Register, ePrivacy, an Art. 27 EU representative, or asks "is my site GDPR compliant", "do I need to register as an operator in Azerbaijan", or "is our cookie banner lawful" — even without the word "audit".

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처리방침·이용약관 자동 생성 스킬 패키지 (v4.0). 호출 시 privacy-kr·privacy-eu·privacy-us·privacy-global 4개 하위 스킬을 번호 메뉴로 제시하고 번호 입력 즉시 해당 스킬 인터뷰로 직행. 한국 PIPA + EU GDPR + US CCPA/CPRA 대응.

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Tracks and monitors US state privacy legislation across all 50 states, DC, and territories. Covers enacted comprehensive privacy laws (California CCPA/CPRA, Virginia VCDPA, Colorado CPA, Connecticut CTDPA, Utah UCPA, and subsequent enactments), pending bills, effective dates, and key requirement differences. Keywords: state privacy law, CCPA, CPRA, VCDPA, CPA, CTDPA, UCPA, multi-state.

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Guides SOC 2 Type II Privacy Trust Services Criteria preparation and audit execution. Covers AICPA TSP Section 100 Privacy criteria P1-P8 including notice, choice/consent, collection, use/retention/disposal, access, disclosure, security, and quality. Includes evidence collection, control testing, and report review. Keywords: SOC 2, privacy criteria, TSP, AICPA, Type II, trust services.

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Build privacy KPI dashboards tracking DSAR volume and response time, breach count and severity, DPIA completion rate, training coverage, and consent rates. Includes metric definitions, data collection patterns, visualization designs, and executive reporting templates for privacy program measurement.

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Implement the NIST Privacy Framework GOVERN function covering GV.AT awareness and training, GV.MT monitoring and review, GV.PO policy development, and GV.RR roles and responsibilities. Provides governance structure templates, training programs, and accountability frameworks for privacy governance.

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Implement the NIST Privacy Framework COMMUNICATE function covering CM.AW awareness raising and CM.PO communication policies. Provides transparency mechanisms, stakeholder engagement frameworks, privacy notice templates, and communication workflow guidance.

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Implements HITECH Act privacy and security requirements including breach notification expansion, four-tier penalty structure, state attorney general enforcement authority, EHR meaningful use privacy conditions, and business associate direct liability. Keywords: HITECH Act, breach notification, penalty tiers, state AG enforcement, meaningful use, EHR privacy.

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Implementation guide for Global Privacy Control (GPC) automated opt-out signal per CPRA Section 1798.135(e). Covers Sec-GPC HTTP header detection, JavaScript navigator.globalPrivacyControl API, and state-specific requirements for CA, CO, CT, MT, TX, and OR. Includes server-side detection code and compliance mapping.

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Systematic application of the eight privacy design patterns per Hoepman: minimize, hide, separate, abstract, inform, control, enforce, and demonstrate. Covers pattern selection methodology per processing activity, mapping to GDPR principles, and practical implementation guidance for privacy-by-design system architecture.

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Expert in on-chain privacy technologies - ZK-SNARKs, ZK-STARKs, mixers, stealth addresses, ring signatures, and confidential transactions for building privacy-preserving blockchain applicationsUse when "privacy, zero knowledge, zk-snark, zk-stark, mixer, stealth address, ring signature, confidential transaction, tornado, private transaction, anonymous, unlinkability, privacy, zero-knowledge, zk-snarks, zk-starks, mixers, stealth-addresses, tornado-cash, zcash, confidential" mentioned.

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Family-G proof & derivation integrity forensics: does a THIRD PARTY's written proof/derivation actually establish its theorem, or does it skip an obligation, assume its own conclusion, take an invalid step, drift a symbol's meaning, or smuggle an unstated assumption? Decides from the WRITTEN proof/derivation — verdict-bearing at L1 (the LaTeX source; PDF-extracted math is unreliable, so an L0 PDF-only run surfaces info only) — never asserts 'fabricated', only that the step shown does not hold. A fresh cross-model reviewer reads the theorem/proof + an extraction-only obligation scaffold and proposes per-obligation findings, each span-anchored to the evidence ledger (claims.json); reviewer≠adjudicator. Emits proof-derivation-forensics.findings.json; NEVER computes the verdict. dimension=proof, can be critical. Triggers: "proof forensics", "check this proof", "derivation integrity", "audit the math", "证明审计", "推导有没有漏洞".

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Rates a project with Jevaluate and keeps the rating private, with the same rubric and checks, a private library that export refuses, and nothing pushed or published. Use when a rating must stay private, such as "/jevaluate-private" followed by a link or folder, "rate this privately", "evaluate my own project", a client's or employer's code, a design doc or a local folder that isn't public, or any rating that must not reach the public ratings or the repo.

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Research private companies through six perspectives, including business, finances, competition, and technology. Cross-check evidence, separate facts from inferences, and produce a valuation range, possible exit routes, and a map of missing information.

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• Assess a private company's business and valuation range
• Compare conflicting revenue or funding reports
• Check company claims against hiring and patent signals

Review code for privacy risks, prepare data protection impact assessments, and track personal data requests and deadlines. The skill supports GDPR and German privacy compliance work, with final compliance decisions referred to a data protection officer or legal counsel.

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• Checking a service's code for privacy risks
• Preparing a data protection impact assessment
• Tracking deadlines for access and erasure requests