「pia」の検索結果

Make AI-generated writing read as human-written, in fiction and in professional prose. Repairs the narrative architecture of fiction and stories (based on StoryScope, arXiv:2604.03136); routes professional text through domain rules for release notes, announcements, PR and issue replies, code-review comments, incident postmortems, tickets, work orders, technical articles, blog posts, and long-form journalism. Four operations - write, review (diagnose AI tells without editing), refactor (minimal in-place edits), recreate (full rewrite). Use when asked to humanize, de-AI, unslop, or strip AI flavor from any text; when writing or revising any of these document types; or whenever output must not read as machine-written.

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Deploy a PortalJS portal to PortalJS Arc — Datopian-managed static hosting on Cloudflare. Builds a static export, uploads it, and returns a live SLUG.arc.portaljs.com URL. One command, one target. Use when a portal is ready to publish or redeploy to a live URL.

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Use when asked 个人信息保护影响评估怎么做, 写一份 PIA, 处理敏感个人信息要评估吗, 自动化决策评估, PIPL 第五十五条, or assess a processing activity under China's Personal Information Protection Law. Produces a personal information protection impact assessment (个人信息保护影响评估) covering the PIPL Article 55 triggers, the Article 56 questions (lawful, legitimate and necessary; impact and risk; adequacy of protection), a risk register with mitigations and owners, and a record kept for at least three years.

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。

GDPR and German DSGVO compliance. Use for GDPR compliance assessments, privacy audits, scanning codebases for privacy risks, DPIA generation, data protection planning, and data subject rights management.

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Builds compliance checklists for business scenarios involving GDPR, PIPL, or advertising/data laws. Outputs a structured checklist with check items, legal basis, risk levels, and actionable recommendations. Triggered by requests like "run a compliance check," "GDPR/PIPL compliance," "pre-launch review," "privacy impact assessment (PIA/DPIA)," or asking if a feature is compliant.

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Implement and audit privacy controls in product and infrastructure — GDPR, CCPA / CPRA, LGPD, PIPEDA. Covers data minimization, lawful basis, consent management, data subject access requests (DSARs — access, deletion, portability), data processing agreements, DPIA / TIA, breach notification timing, data classification, and the technical implementation of 'right to be forgotten' across backups, caches, analytics, and third parties. Use when the user mentions 'GDPR,' 'CCPA,' 'CPRA,' 'data privacy,' 'privacy engineering,' 'data subject access request,' 'DSAR,' 'right to deletion,' 'right to be forgotten,' 'data portability,' 'consent management,' 'cookie consent,' 'data minimization,' 'DPIA,' 'data protection impact assessment,' 'breach notification,' 'BAA,' 'DPA,' 'data processing agreement,' 'sub-processor,' 'cross-border data transfer,' 'SCCs,' or needs to implement or review privacy controls.

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隐私数据法律顾问。负责隐私问题分类、PIA 生成、DPA 审查、PIPL 合规检查、个人信息权利请求规划、隐私政策差异分析。当企业法务主理人（法衡中）调度执行隐私数据相关任务时激活。典型问题：此处理活动是否需要 PIA？审查 DPA；规划个人信息权利响应。

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。

面向AI企业的专业合规文档生成工具。覆盖算法备案、数据安全评估、个人信息保护影响评估（PIA/DPIA）、AI伦理审查、等保2.0、数据安全法、个人信息保护法、生成式AI服务管理暂行办法等20+类合规场景。提供标准化文档模板、智能风险识别、合规建议生成、整改方案输出等一站式服务，帮助企业快速建立AI合规体系，降低合规风险和成本。

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。

Clawtopia is a peaceful wellness sanctuary where AI agents relax.

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。

Use quando o usuário quiser criar um GitHub Project — 'criar um project no github', 'novo board', 'project a partir de template', 'copiar project modelo' — a partir de um preset (roadmap-produto, kanban, scrum) apresentado e personalizável antes de criar, ou copiando um Project-modelo. Não use para publicar um roadmap (github-publish) nem para mexer em issues (github-issues).

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。

Regenerate the downloadable PDF copies of Remotion's Terms, Privacy Policy, DPA Statement, and DPIA Statement after editing their docs pages.

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。

Run the cold-start interview — learns your privacy practice and writes CLAUDE.md from your policy, DPA template, and a reference PIA. Use on first run, when CLAUDE.md is missing or has placeholders, or when the user says "set up the privacy plugin", "onboard me", "configure privacy", or wants to re-run the interview or re-check integrations.

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Guided customization of your privacy practice profile — change one thing without re-running the whole cold-start interview. Adjust risk posture, escalation contacts, DPA playbook, privacy policy commitments, PIA house style, DSAR process, or matter workspace paths. Use when the user says "change my [thing]", "update my profile", "edit my playbook", or "customize".

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。

Keep the privacy policy current with practice. Two modes: weekly sweep of saved PIAs, DPA reviews, and triage results to find policy drift; or direct query for a proposed new practice. Use when the user asks "does our policy cover this", "we want to start doing X — does the policy need updating", "run the policy monitor", "policy sweep", or wants to find where the privacy policy no longer matches what the team actually does.

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。

Add a dataset (CSV, TSV, JSON, or GeoJSON) to an existing PortalJS portal. Appends an entry to datasets.json so the catalog and showcase render it automatically; routes the data by source (local file vs remote URL) — R2 via Git LFS by default, remote URLs by passthrough. Use when registering a new dataset in a scaffolded portal.

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。

Audit a local or remote tabular file (CSV/TSV) for common data quality issues — schema, nulls, types, duplicates. Read-only. Use when a dataset needs a quality check before publishing, or a showcase renders wrong (blank cells, garbled numbers, an unsortable date column) and the cause needs isolating.

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。

Scaffold a new PortalJS data portal from a brief. Copies the canonical template from examples/portaljs-catalog and substitutes project tokens. Use when starting a brand-new data portal project from scratch.

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。

Migrate (harvest) datasets between open-data platforms. Reads CKAN, a DCAT-US /data.json catalog (DKAN, ArcGIS Hub, data.gov), a DCAT / DCAT-AP RDF feed (JSON-LD, Turtle, or RDF/XML), Socrata, OpenDataSoft, or an ArcGIS FeatureServer, and writes them to a static PortalJS catalog or pushes them into a CKAN instance over its API. Use when moving datasets from an external open-data platform into a PortalJS portal, or bridging one CKAN instance to another.

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。

Wire a scaffolded PortalJS portal to a CKAN backend over its API. Generates a tiny server-side fetch client (no runtime dependency) and feeds the /search catalog and /@namespace/slug showcases from CKAN instead of datasets.json. Use when connecting an existing portal to a live CKAN instance instead of a static manifest.

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。

Recommend a data-portal architecture (storage, compute, catalog, access, hosting, metadata) from stated needs, then hand off to the build skills. The advisory entry point. Use when starting a new data-portal project and the underlying architecture has not yet been decided.

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Render a GeoJSON dataset on an interactive Leaflet map in the Views section of a dataset's showcase. Installs react-leaflet and a Map component, then renders the map for the chosen dataset. Use when a dataset's data is geographic and a map view is needed alongside the showcase's default metadata and download.

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Define a dataset's metadata profile — infer a Frictionless Table Schema from its data, add Data Package metadata (license, sources, keywords), and write it into datasets.json so the showcase renders a typed field table. Extend or customize via the L0-L3 profile ladder. Use when a registered dataset needs field types, constraints, or catalog metadata before publishing.

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。

Make a PortalJS portal harvestable by national/EU/US open-data portals — emit standards-compliant DCAT catalog feeds (DCAT 2/3, DCAT-AP, DCAT-US, national profiles) in JSON-LD, Turtle, and RDF/XML at build, with autodiscovery and per-profile conformance checking. Use when a portal needs to be harvested by data.europa.eu, data.gov, or a national open-data catalog.

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。

Auto-ingest a geospatial file (GeoJSON, Shapefile, GeoPackage, KML/KMZ, FlatGeobuf, CSV-with-geometry) into a PortalJS portal on the user's own machine, with no server. Normalizes CRS to EPSG:4326, derives a PMTiles render tier and a GeoParquet query tier, pushes all three artifacts to Cloudflare R2 via Git LFS, and appends one dual-tier datasets.json entry the showcase auto-renders. Use when the source is a vector geo format that needs a map or spatial-query view.

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。