「privacy」の検索結果

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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Draft or review a DPDPA-compliant consent notice under India's Digital Personal Data Protection Act, 2023 and DPDPA Rules, 2025. Provide basic details about your business and this skill handles the rest - building a notice tailored to your operations, with all required sections, granular consent boxes, and internal notes for your team. If you have an existing notice or privacy policy that needs to comply with DPDPA, this skill revises it too, flagging key gaps and changes made.

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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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Guide for drafting cookie policies compliant with GDPR and the ePrivacy Directive. Includes CNIL 2020 recommendations, a reference template, and best practices. Use when drafting or revising a cookie policy for a website or application.

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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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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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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.

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Best-practices reference for preparing and instrumenting applications on Temps. Covers the app runtime contract (`.temps.yaml` health, HOST/PORT, readiness, SIGTERM, replicas, migrations) and production observability (errors, traces, metrics, logs, analytics, privacy, sampling, cardinality, credential boundaries). Use whenever building or reviewing an app for Temps, configuring health checks, adding telemetry, diagnosing missing/noisy signals, or checking OTLP/Sentry/analytics ingestion. Triggers include "temps best practices", "prepare this app for Temps", ".temps.yaml health", "temps health check", "ignore health checks in otel", "temps observability", "wire up telemetry", and "instrument this app for temps". Prefer focused setup skills for a single SDK. Use temps-cli for executing deploy and resource-management commands.

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Generates App Store release documentation including submission guide, assets, privacy compliance, and marketing strategy. Creates RELEASE_SPEC.md for app launch. Use when preparing for App Store submission.

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Senior developer-level release review for macOS/iOS apps. Identifies security, privacy, UX, and distribution issues with actionable fixes. Use when preparing an app for release, want a critical review, or before App Store submission.

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Security category index for Apple platforms. Routes to the privacy-manifests skill. General secure-storage/biometrics/ATS guidance was retired in the 2026 blind-test audit — current models cover it natively.

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Legal document generation and compliance guidance for indie Apple developers. Covers privacy policies, terms of service, EULAs, GDPR/CCPA/DPDP compliance, and Apple App Store legal requirements. Use when user needs legal documents or compliance guidance.

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Privacy-preserving ad measurement with AdAttributionKit (SKAdNetwork's successor) — install and re-engagement attribution, conversion-value strategy under crowd anonymity, and end-to-end postback testing. Use when running paid acquisition beyond Apple Ads, measuring re-engagement campaigns, designing conversion values, or migrating from SKAdNetwork.

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Local user-profile maintenance skill for Codex, Claude Code, OpenClaw, OpenCode, and other agent harnesses. Use only when the user explicitly invokes $user-profile-keeper to create, initialize, update, query, correct, delete, export, or audit a local persistent user profile. It can extract durable collaboration preferences, requirement-expression habits, capability boundaries, recurring omissions, risk preferences, privacy boundaries, and typical events from the current session into auditable, confirmable, retractable local profile data. Do not auto-invoke, upload profile data, or replace task-clarifier's normal clarification flow.

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发布照片前的人脸隐私遮挡。用于用户提供一张或多张照片并指定保留人物后，用内置表情头像遮住其他人的正脸及仍可辨认人物的侧脸，处理后统一复查并补齐遗漏；支持合照打码、活动照片打码和批量头像遮挡。不用于识别人名、换脸、美颜、证件水印或直接发布照片。

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Agent Media OS, the single skill for every media need in a HyperFrames project. Resolve BGM, SFX, image, icon, brand logo, voice, color grade, or LUT into a frozen local file or paste-ready block + ledger record (one verb, `resolve`); generate via TTS / music / image models when the catalog misses; produce voiceover, transcription, captions, and background removal through one shared audio engine; operate on media (cut / reframe / transform); and reuse assets across projects. Also use for vague feedback that real footage looks dark, flat, boring, should feel retro/camcorder/print/ASCII, needs privacy, or needs a media reveal.

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Your legal, IP, and regulatory brain trust. 31 named personas across 7 cells covering patent strategy, tech licensing, regulatory litigation, AI governance, open-source compliance, privacy law, and antitrust.

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隐私标识移除工具。读取结构化文本数据，按用户选择的类别删除或替换邮箱、IPv4 地址、电话号码等文本中的隐私标识。 当用户提到移除邮箱、清洗 IP、替换电话、从文本里剔除隐私 token 等需求时使用此 skill。 它只处理文本中的 token 清理，不做字段级遮蔽，也不负责图片脱敏、音频脱敏、结构化字段加密或假数据生成。

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数据脱敏工具。对结构化数据中的敏感字段进行字符遮蔽脱敏，保留字段位置并用遮蔽字符替换手机号、身份证、姓名、邮箱、银行卡等内容。 当用户提到数据脱敏、隐私保护、敏感字段遮蔽、PII 处理等需求时使用此 skill。 与 privacy_token_remover 区分开：本 skill 负责字段级遮蔽，不负责删除文本中的隐私标识，也不负责生成假数据。

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SaaS analytics event taxonomy, metric formulas (MRR, churn, LTV), provider-agnostic tracking, funnel analysis, cohort setup, and privacy-respecting instrumentation.

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GDPR compliance - data subject rights, lawful basis, DPIA, privacy by design, breach notification, consent management, cross-border transfers, PII masking

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Use when reviewing, designing, or modifying Java enterprise systems that may support intermediary services, hosting services, online platforms, marketplaces, content moderation, recommender systems, advertising delivery, complaint workflows, transparency reporting, or systemic-risk evidence under the EU Digital Services Act. This should trigger for requests such as Review a Java online platform for DSA controls; Design notice-and-action or appeal workflows; Add recommender, ad transparency, moderation, audit, researcher access, or privacy-safe observability evidence; Assess online-platform transparency controls before production release. Part of Plinth Toolkit

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Use when you need to implement or improve distributed tracing with OpenTelemetry in Java — including trace/span modeling, context propagation, semantic conventions, span attributes/events/status, sampling strategy, baggage usage, privacy safeguards, and backend integration with OTLP collectors. This should trigger for requests such as Improve tracing; Apply OpenTelemetry tracing; Add distributed tracing; Refactor tracing instrumentation; Instrument Java services with OpenTelemetry spans. Part of Plinth Toolkit

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Guides fg-data-profiling data profiling, report generation, configuration, CLI, comparison, privacy, and optional Spark/notebook integration workflows.

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。