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Build Python workflows that constrain language model output using text patterns and grammar rules. Generate structured JSON, restrict classifications to allowed labels, extract information, and combine reusable generation steps with loops and tool selection.
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Build Python workflows that constrain language model output using text patterns and grammar rules. Generate structured JSON, restrict classifications to allowed labels, extract information, and combine reusable generation steps with loops and tool selection.
中文简介正在准备中。当前显示英语简介。
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.
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协助在Claude Code中配置Plankton，在每次编辑文件后自动格式化并检查代码。还涵盖剩余违规的自动修复、复查，以及防止检查规则被放宽的保护措施。
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.
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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.
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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.
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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.
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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.
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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.
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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.
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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
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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
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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
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Check names, aliases, and existing pages before saving content to a gbrain knowledge store. The skill reads likely matches to identify duplicates, links to existing information, and routes new material to the appropriate ingestion skills.
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Multi-agent swarm formation and coordinated execution with topology-aware agent deployment, consensus protocols, and anti-drift enforcement.
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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.
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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.
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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.
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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.
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Expert guide for agent-native structured outputs, JSON Schema strict mode enforcement (OpenAI response_format, Gemini schema mode, Claude tool_use), MCP resource schemas, and zero-hallucination type contracts / Panduan ahli kontrak output terstruktur native agen dan penegakan JSON schema ketat.
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Write-time code quality enforcement using Plankton — auto-formatting, linting, and Claude-powered fixes on every file edit via hooks.
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Register shared claims transformation and hierarchical role policies in the API without breaking existing scope enforcement.
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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.
中文简介正在准备中。当前显示原文说明。