23 件 ・ 関連度順
概要と使いどころ
Guides compliance with Japan's Act on the Protection of Personal Information (APPI, 2022 amendments). Covers individual rights expansion, cross-border transfer restrictions including pre-transfer information requirements, PPC enforcement, and pseudonymised and anonymously processed information. Keywords: APPI, Japan data protection, PPC, cross-border transfer, pseudonymised information, individual rights.
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。
Claude Codeのファイル編集時に、Planktonで自動整形とコード検査を行う設定を支援するスキル。残った違反の自動修正や再検査、検査ルールの保護も扱います。
Analyze any OFAC or OFSI enforcement action — by URL, pasted text, or uploaded document — and produce a structured root cause analysis as a formatted Excel (.xlsx) spreadsheet. Use this skill whenever a user names, links to, pastes, or uploads an OFAC or OFSI enforcement action and asks for any of the following: root cause analysis, compliance gaps, what went wrong, lessons learned, organizational self-assessment, or remediation planning. Also trigger when a user asks "analyze this enforcement action", "what were the root causes", "turn this into a checklist", or "how do I make sure this doesn't happen to us". Outputs a single-sheet .xlsx table with six columns: Root Cause | What Went Wrong | How It Went Wrong | What Could Have Stopped It | Is my organization immune to this? (Yes/No/Partial) | Notes.
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。
Implements compliance with South Africa's Protection of Personal Information Act (POPIA), Act No. 4 of 2013. Covers conditions for lawful processing, data subject rights, cross-border transfer restrictions, Information Regulator enforcement, and responsible party obligations. Keywords: POPIA, South Africa, Information Regulator, responsible party, operator, prior authorisation.
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。
Guides compliance with Canada's Personal Information Protection and Electronic Documents Act (PIPEDA, S.C. 2000, c. 5). Covers the 10 fair information principles in Schedule 1, consent requirements, cross-border transfer obligations, breach notification under Division 1.1, and OPC enforcement. Keywords: PIPEDA, Canada privacy, fair information principles, OPC, breach notification, cross-border transfer, consent.
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 the free first-party `dotnet format` CLI for .NET formatting and analyzer fixes. Use when a .NET repo needs formatting commands, `--verify-no-changes` CI checks, or `.editorconfig`-driven code style enforcement.
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 the free first-party `dotnet format` CLI for .NET formatting and analyzer fixes. Use when a .NET repo needs formatting commands, `--verify-no-changes` CI checks, or `.editorconfig`-driven code style enforcement.
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。
Develops data classification policies with tiered handling (public, internal, confidential, restricted), labeling requirements, enforcement mechanisms, and procedures per tier. Covers policy governance, exception handling, and compliance monitoring. Keywords: classification policy, data tiers, handling procedures, labeling, enforcement, data governance, information security.
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。
Control LLM output with regex and grammars, guarantee valid JSON/XML/code generation, enforce structured formats, and build multi-step workflows with Guidance - Microsoft Research's constrained generation framework
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。
Control LLM output with regex and grammars, guarantee valid JSON/XML/code generation, enforce structured formats, and build multi-step workflows with Guidance - Microsoft Research's constrained generation framework
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。
Design serialization schemas using JSON Schema, Protocol Buffer definitions, or Apache Avro. Covers schema versioning, backwards compatibility, validation rules, and evolution strategies for long-lived data formats. Use when defining a new API contract or data interchange format, adding fields to an existing schema without breaking consumers, migrating between schema versions, choosing between schema systems, or documenting data validation rules for automated enforcement.
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。
Controle saída de LLM com regex e gramáticas, garanta geração válida de JSON/XML/código, aplique formatos estruturados e construa fluxos de trabalho multi-etapas com Guidance - framework de geração restrita da Microsoft Research
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。
Control LLM output with regex and grammars, guarantee valid JSON/XML/code generation, enforce structured formats, and build multi-step workflows with Guidance - Microsoft Research's constrained generation framework
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。
Control LLM output with regex and grammars, guarantee valid JSON/XML/code generation, enforce structured formats, and build multi-step workflows with Guidance - Microsoft Research's constrained generation framework
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。
Multi-agent swarm formation and coordinated execution with topology-aware agent deployment, consensus protocols, and anti-drift enforcement.
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。
California Consumer Privacy Act (CCPA) and California Privacy Rights Act (CPRA) compliance advisor — business threshold analysis, consumer rights fulfillment (access, delete, correct, opt-out of sale/sharing, limit SPI, ADMT opt-out), privacy notice drafting, service provider vs. contractor vs. third-party classification, sensitive personal information (SPI) handling, data minimization, opt-out mechanisms (including GPC), cybersecurity audits and risk assessments (live since Jan 1, 2026), ADMT obligations (effective 2026, deadline Jan 1, 2027), CPPA enforcement (Disney $2.75M, PlayOn $1.1M, Ford $375K), penalty exposure, GDPR comparison, and gap assessments for businesses operating in or targeting California residents.
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。
California Consumer Privacy Act (CCPA) and California Privacy Rights Act (CPRA) compliance advisor — business threshold analysis, consumer rights fulfillment (access, delete, correct, opt-out of sale/sharing, limit SPI, ADMT opt-out), privacy notice drafting, service provider vs. contractor vs. third-party classification, sensitive personal information (SPI) handling, data minimization, opt-out mechanisms (including GPC), cybersecurity audits and risk assessments (live since Jan 1, 2026), ADMT obligations (effective 2026, deadline Jan 1, 2027), CPPA enforcement (Disney $2.75M, PlayOn $1.1M, Ford $375K), penalty exposure, GDPR comparison, and gap assessments for businesses operating in or targeting California residents.
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。
Define deterministic guardrails for agent tool calls — protected paths, test-file locks during bug fixes, post-edit formatters, production approval gates, secret deny rules. Use when writing or reviewing a hook policy, or moving an always-do-X rule out of prose into enforcement.
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。
Guides compliance with South Korea's Personal Information Protection Act (PIPA, 개인정보 보호법). Covers pseudonymisation framework, notification requirements, PIPC enforcement, consent standards, and cross-border transfer rules under the 2023 amendments. Keywords: PIPA, Korea data protection, PIPC, pseudonymisation, consent, cross-border transfers.
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。
Write-time code quality enforcement using Plankton — auto-formatting, linting, and Claude-powered fixes on every file edit via hooks.
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。
Register shared claims transformation and hierarchical role policies in the API without breaking existing scope enforcement.
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。
Establish and enforce coding standards, best practices, and architectural patterns across the codebase using linters, formatters, and code review processes. Use when setting up ESLint/Prettier, configuring linting rules, creating code style guides, implementing pre-commit hooks, establishing naming conventions, enforcing TypeScript strict mode, maintaining consistency, conducting architecture reviews, or defining team coding standards.
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。
Write-time code quality enforcement using Plankton — auto-formatting, linting, and Claude-powered fixes on every file edit via hooks.
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。