菜单
Define and verify data governance as code. Use when data classes, retention, deletion, export, residency, subprocessors, sensitive metadata, privacy behavior, or data-handling evidence changes.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Decompose a feature or intent into small, context-bound backlog items in the SQL backlog, for a planning model (Opus or Sonnet). Use before a swarm of workers: turn one feature into tightly scoped, logged items, each with a write scope and a context profile, so cheaper sub-agents can each work one item in isolation and total token use drops.
Orchestrate a context-bound, backlog-logged multi-agent swarm to cut token use. Use to run a feature as a planner (Opus or Sonnet) that logs small backlog items, then cheaper workers (Sonnet or Haiku) that each implement one item under its bounded context packet, while the parent keeps integration, the SQL backlog, the audit log, and verification.
Select, record, and validate ADG evidence. Use when choosing targeted checks, recording failed commands, linking tests to requirements, writing audit events, registering advisory gaps, or preparing feature/release evidence.
Elicit generic ADG feature intent into a normalized requirements graph. Use when naming a feature, defining how it fits the platform, deriving RBAC-aligned stories and use cases, or creating success, anti-success, scenario, and gap evidence in config/agentic/elicitation.json.
Work a single backlog item under a bounded context packet, for a context-cheap sub-agent (Sonnet or Haiku). Use when an orchestrator hands you one item id to implement in isolation: claim it, load only its context:item packet, edit only its write scope, record evidence, and complete it. Keeps token use low and work traceable.
Use for small UI, copy, docs, styling, or visual polish fixes that should avoid full governance unless risk increases.
| name | adg-data-governance-as-code |
| description | Define and verify data governance as code. Use when data classes, retention, deletion, export, residency, subprocessors, sensitive metadata, privacy behavior, or data-handling evidence changes. |
Use this when data policy and runtime behavior must agree.
