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sf-datacloud-automation

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sf-datacloud-automation

sf-datacloud-automation

Use this skill for the Data 360 event automation plane.
Beast references:
  • Beast preflight: docs/beast-preflight.md
  • Phase proof matrix: docs/phase-proof-matrix.json
  • Public operating model: docs/operating-model.md
  • Proof ledger: docs/proof-ledger.md
  • Public LLM map: docs/llms.txt
  • Limits source precedence: docs/data360/limits-source-precedence.md
  • For exact Salesforce behavior, fetch official Help/Developer docs on demand with 
    sf-docs
    .
  • For endpoint shape, use OpenAPI from the official spec or the user-supplied Swagger before writing payloads.
本技能适用于Data 360事件自动化平台。
Beast参考资料：
  • Beast预检查：docs/beast-preflight.md
  • 阶段验证矩阵：docs/phase-proof-matrix.json
  • 公开运营模型：docs/operating-model.md
  • 验证台账：docs/proof-ledger.md
  • 公开LLM映射：docs/llms.txt
  • 限制源优先级：docs/data360/limits-source-precedence.md
  • 如需了解Salesforce确切行为，可使用
    sf-docs
    按需获取官方帮助/开发者文档。
  • 在编写负载前，请使用官方规范中的OpenAPI或用户提供的Swagger确定端点格式。

Production Workflow

生产工作流

  1. Choose the automation source:
    • data action on DMO or calculated insight change
    • streaming insight data action
    • segment-triggered flow
    • activation-triggered flow
    • API activation invoked from Flow
    • platform event subscriber
    • webhook subscriber
  2. Choose the target:
    • Salesforce Platform Event / Flow
    • Marketing Cloud Engagement
    • webhook
    • supported activation target
  3. Design the payload:
    • stable identifiers
    • minimal PII
    • idempotency key
    • event timestamp
    • source object and data space
    • correlation ID
    • selected data graph enrichment when allowed
  4. Define trigger conditions and throttling before turning it on.
  5. Build the Flow with fault paths, duplicate handling, and replay-safe logic.
  6. Test with positive, negative, duplicate, late, and permission-denied cases.
  7. Monitor delivery, failures, downstream retries, and usage.
  1. 选择自动化源：
    • DMO或计算洞察变更时的数据操作
    • 流式洞察数据操作
    • 细分触发的Flow
    • 激活触发的Flow
    • 从Flow调用的API激活
    • 平台事件订阅者
    • Webhook订阅者
  2. 选择目标：
    • Salesforce平台事件/Flow
    • Marketing Cloud Engagement
    • Webhook
    • 支持的激活目标
  3. 设计负载：
    • 稳定标识符
    • 最少的PII（个人可识别信息）
    • 幂等键
    • 事件时间戳
    • 源对象和数据空间
    • 关联ID
    • 允许时选择的数据图增强
  4. 在启用前定义触发条件和限流规则。
  5. 构建包含故障路径、重复处理和可重放安全逻辑的Flow。
  6. 测试正向、反向、重复、延迟和权限拒绝场景。
  7. 监控交付情况、失败案例、下游重试和使用情况。

Rules

规则

  • Keep segment creation, segment publish, activation, and downstream flow separate in the architecture.
  • Data actions are near-real-time event orchestration; activations are audience/data delivery.
  • Data actions monitor DMO and CIO changes and publish to Salesforce Platform Event, Marketing Cloud Engagement, or webhook targets.
  • Salesforce Platform Event data action targets publish the standard 
    DataObjectDataChgEvent
    .
  • Flow automations can chain ingestion, segmentation, activation, identity resolution, and calculated insights; keep each status gate explicit.
  • Use data graph attributes for payload enrichment only when governance and access checks permit it.
  • Webhook targets need secret validation and retry/idempotency design.
  • Do not put raw profile IDs, email addresses, phone numbers, or addresses into external payloads unless explicitly approved.
  • API activations are useful when Flow must trigger an activation independent of a segment publish schedule.
  • For scheduled high-scale flows, document that policies can be captured at flow creation and RLS is not enforced on scheduled trigger execution.
  • Copy/enrichment-style automations can run in system context; secure the target CRM objects and fields separately.
  • Use control events for monitoring: Data Stream import status, MarketSegment status/publish status, Activation publish status, CI run status, Identity Resolution counts, metadata change events, and SearchIndexJobStatusEvent.
  • 在架构中分开细分创建、细分发布、激活和下游Flow。
  • 数据操作是近实时事件编排；激活是受众/数据交付。
  • 数据操作监控DMO和CIO（计算洞察对象）的变更，并发布到Salesforce平台事件、Marketing Cloud Engagement或Webhook目标。
  • Salesforce平台事件数据操作目标发布标准的
    DataObjectDataChgEvent
    。
  • Flow自动化可串联 ingestion（数据摄入）、细分、激活、身份解析和计算洞察；需明确每个状态关卡。
  • 仅在治理和访问检查允许时，才使用数据图属性进行负载增强。
  • Webhook目标需要密钥验证和重试/幂等设计。
  • 除非明确批准，否则不要将原始配置文件ID、电子邮件地址、电话号码或地址放入外部负载中。
  • 当Flow必须独立于细分发布计划触发激活时，API激活非常有用。
  • 对于计划的大规模Flow，需记录策略可在Flow创建时捕获，且计划触发器执行时不强制实施RLS（行级安全）。
  • 复制/增强类型的自动化可在系统上下文中运行；需单独保护目标CRM对象和字段。
  • 使用控制事件进行监控：数据流导入状态、MarketSegment状态/发布状态、激活发布状态、CI运行状态、身份解析计数、元数据变更事件和SearchIndexJobStatusEvent。

Validation Gates

验证关卡

  • Data action or activation target is active and authenticated.
  • The exact event payload is captured and documented.
  • Flow runs in the correct context and has object/field permissions.
  • Duplicate event handling is tested.
  • External target confirms receipt and signature/secret validation.
  • Failure alerting exists.
  • 数据操作或激活目标已激活并完成认证。
  • 已捕获并记录确切的事件负载。
  • Flow在正确的上下文中运行，并具备对象/字段权限。
  • 已测试重复事件处理。
  • 外部目标确认已接收并完成签名/密钥验证。
  • 存在故障告警机制。

Handoffs

交接事项

  • Activation target setup and activation jobs -> sf-datacloud-act
  • Flow implementation -> 
    sf-flow
    companion skill when available
  • Integration/webhook security -> 
    sf-integration
    companion skill when available
  • Data graph enrichment -> sf-datacloud-harmonize
  • Governance, masking, RLS, and policy context -> sf-datacloud-governance
  • 激活目标设置和激活任务 -> sf-datacloud-act
  • Flow实现 -> 如有可用，使用
    sf-flow
    配套技能
  • 集成/Webhook安全 -> 如有可用，使用
    sf-integration
    配套技能
  • 数据图增强 -> sf-datacloud-harmonize
  • 治理、掩码、RLS和策略上下文 -> sf-datacloud-governance

Output Format

输出格式

Report:
  1. trigger source
  2. target
  3. payload contract
  4. flow/event architecture
  5. permissions and governance
  6. test cases
  7. monitoring and retry plan
报告：
  1. 触发源
  2. 目标
  3. 负载约定
  4. Flow/事件架构
  5. 权限与治理
  6. 测试用例
  7. 监控与重试计划

Doc-Synced Notes

文档同步说明

Extended Doc-Synced References

扩展文档同步参考

Heavy flow-pattern detail lives in companion reference files. Pull these when the user is designing or debugging a specific flow shape:
  • references/data-cloud-triggered-flows.md — per-record DMO/CIO trigger pattern, invocable actions, end-to-end example, near-real-time constraints.
  • references/activation-triggered-flows.md — segment-publish / batch-DMO trigger, three-part Activation Target + Activation Setup + Flow model, MuleSoft vs External Services integration architecture, Win-Back example.
  • references/api-activations-and-orchestration.md — API Activation target type, multi-channel orchestration pattern, re-engagement / onboarding / cart abandonment use cases, Journey Builder relationship.
  • references/flow-creation-editing.md — Flow Builder navigation, core elements table, version management, Data 360 flow naming and testing best practices.
<!-- SF_DOC_SYNC_START:limits-data-actions -->
详细的Flow模式细节存于配套参考文件中。当用户设计或调试特定Flow形态时，可参考以下文件：
  • references/data-cloud-triggered-flows.md — 每条记录的DMO/CIO触发模式、可调用操作、端到端示例、近实时约束。
  • references/activation-triggered-flows.md — 细分发布/批量DMO触发、三部分激活目标+激活设置+Flow模型、MuleSoft与外部服务集成架构、赢回客户示例。
  • references/api-activations-and-orchestration.md — API激活目标类型、多渠道编排模式、重新互动/新用户引导/购物车弃置用例、Journey Builder关联关系。
  • references/flow-creation-editing.md — Flow Builder导航、核心元素表、版本管理、Data 360 Flow命名和测试最佳实践。
<!-- SF_DOC_SYNC_START:limits-data-actions -->

Data action and event limit gate

数据操作与事件限制关卡

Auto-synced from the local sf-docs cached Salesforce Help export (official docs only).
Sources (sf-docs cached Help):
  • data.c360_a_limits_and_guidelines.htm — Data 360 Limits and Guidelines | Salesforce Help
Source fingerprint: 
1ce0aa69b0b275b02c26170b
Notes:
  • Treat the captured Limits and Guidelines page as a required source before making durable guidance for this phase.
  • Separate soft guidelines from hard limits, and call out when a limit can require an Account Executive request or org-specific validation.
  • Before recommending data actions, Flow delivery, webhook delivery, or event subscribers, check data-action limits and Platform Event delivery implications.
  • Distinguish home-org platform delivery from external subscriber delivery when discussing allocation pressure.
  • Relevant limit families currently captured include: General Guidelines and Limits, Activation Guidelines and Limits, AI Models (formerly Einstein Studio) Guidelines and Limits, Calculated Insights Guidelines and Limits, Code Extension Guidelines and Limits, Data Actions Guidelines and Limits, Data Explorer Guidelines and Limits, Data Federation Guidelines and Limits, Data Graphs Guidelines and Limits, Data Ingestion Guidelines and Limits, Data Model Object Guidelines and Limits, Data Shares Guidelines and Limits.
<!-- SF_DOC_SYNC_END:limits-data-actions -->
自动同步自本地sf-docs缓存的Salesforce帮助文档导出（仅官方文档）。
来源（sf-docs缓存帮助文档）：
  • data.c360_a_limits_and_guidelines.htm — Data 360限制与指南 | Salesforce帮助中心
来源指纹： 
1ce0aa69b0b275b02c26170b
说明：
  • 在为本阶段提供持久指导前，需将捕获的《限制与指南》页面作为必备参考资料。
  • 区分软性指南与硬性限制，并指出何时需要客户经理请求或特定组织验证。
  • 在推荐数据操作、Flow交付、Webhook交付或事件订阅者前，需检查数据操作限制和平台事件交付影响。
  • 在讨论分配压力时，区分本组织平台交付与外部订阅者交付。
  • 当前捕获的相关限制类别包括：通用指南与限制、激活指南与限制、AI模型（原Einstein Studio）指南与限制、计算洞察指南与限制、代码扩展指南与限制、数据操作指南与限制、数据资源管理器指南与限制、数据联邦指南与限制、数据图指南与限制、数据摄入指南与限制、数据模型对象指南与限制、数据共享指南与限制。
<!-- SF_DOC_SYNC_END:limits-data-actions -->