data360-schema-get

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data360-schema-get Skill

data360-schema-get 技能

Overview

概述

This skill retrieves Data Lake Object (DLO) and Data Model Object (DMO) schema information from Salesforce Data Cloud using the SSOT REST API. It can list all DLOs or DMOs in an org, or retrieve detailed schema for a specific DLO or DMO.

此技能使用SSOT REST API从Salesforce Data Cloud中检索数据湖对象（DLO）和数据模型对象（DMO）的架构信息。它可以列出组织中的所有DLO或DMO，或者检索特定DLO或DMO的详细架构。

When to Use

使用场景

User wants to see all DLOs or DMOs in a Data Cloud org
User needs field schema for a specific DLO or DMO
User is exploring Data Cloud data structures
User needs to understand DLO or DMO field types and metadata

用户希望查看Data Cloud组织中的所有DLO或DMO
用户需要特定DLO或DMO的字段架构
用户正在探索Data Cloud的数据结构
用户需要了解DLO或DMO的字段类型和元数据

Prerequisites

前提条件

SF CLI installed and authenticated to target org
Org has Data Cloud enabled
User has appropriate Data Cloud permissions

已安装SF CLI并完成目标组织的身份验证
组织已启用Data Cloud
用户拥有相应的Data Cloud权限

Skill Execution

技能执行

Parameters

参数

org_alias (required): The SF CLI org alias (e.g., 'afvibe', 'myorg')
dlo_name (optional): Specific DLO developer name (e.g., 'Employee__dll')
dmo_name (optional): Specific DMO developer name (e.g., 'Individual__dlm')

org_alias（必填）：SF CLI组织别名（例如：'afvibe'、'myorg'）
dlo_name（可选）：特定DLO的开发者名称（例如：'Employee__dll'）
dmo_name（可选）：特定DMO的开发者名称（例如：'Individual__dlm'）

Step 1: Discover Connected Org

步骤1：发现已连接的组织

First, run

sf org list

to find out which org is connected and extract the alias to use for all subsequent calls:

bash

sf org list

Example output:

text

┌────┬───────┬──────────────────────────┬────────────────────┬───────────┐
│    │ Alias │ Username                 │ Org Id             │ Status    │
├────┼───────┼──────────────────────────┼────────────────────┼───────────┤
│ 🍁 │ myorg │ chandresh@afvidedemo.org │ 00DKZ00000b80NT2AY │ Connected │
└────┴───────┴──────────────────────────┴────────────────────┴───────────┘

Extract the Alias value (e.g.,

myorg

) from the output and use it as the

<org_alias>

for all subsequent calls. Use

--all

to see expired and deleted scratch orgs as well.

首先，运行

sf org list

查看已连接的组织，并提取别名用于后续所有调用：

bash

sf org list

示例输出：

text

┌────┬───────┬──────────────────────────┬────────────────────┬───────────┐
│    │ Alias │ Username                 │ Org Id             │ Status    │
├────┼───────┼──────────────────────────┼────────────────────┼───────────┤
│ 🍁 │ myorg │ chandresh@afvidedemo.org │ 00DKZ00000b80NT2AY │ Connected │
└────┴───────┴──────────────────────────┴────────────────────┴───────────┘

从输出中提取 Alias 值（例如：

myorg

），将其作为后续调用中的

<org_alias>

。使用

--all

参数可以查看过期和已删除的临时组织。

Step 2: Validate SF CLI Authentication

步骤2：验证SF CLI身份验证

Before making API calls, verify the org is connected:

bash

sf org display --target-org <org_alias> --json

If not connected, inform user to run:

bash

sf org login web --alias <org_alias>

在调用API之前，验证组织是否已连接：

bash

sf org display --target-org <org_alias> --json

如果未连接，请告知用户运行以下命令：

bash

sf org login web --alias <org_alias>

Step 3a: Execute DLO Schema Script

步骤3a：执行DLO架构脚本

The Python scripts are bundled with this skill in the

scripts/

subdirectory.

To list all DLOs:

bash

python3 ./scripts/get_dlo_schema.py <org_alias>

To get specific DLO schema:

bash

python3 ./scripts/get_dlo_schema.py <org_alias> <dlo_name>

Python脚本已捆绑在此技能的

scripts/

子目录中。

列出所有DLO：

bash

python3 ./scripts/get_dlo_schema.py <org_alias>

获取特定DLO的架构：

bash

python3 ./scripts/get_dlo_schema.py <org_alias> <dlo_name>

Step 3b: Execute DMO Schema Script

步骤3b：执行DMO架构脚本

To list all DMOs:

bash

python3 ./scripts/get_dmo_schema.py <org_alias>

To get specific DMO schema:

bash

python3 ./scripts/get_dmo_schema.py <org_alias> <dmo_name>

列出所有DMO：

bash

python3 ./scripts/get_dmo_schema.py <org_alias>

获取特定DMO的架构：

bash

python3 ./scripts/get_dmo_schema.py <org_alias> <dmo_name>

Step 4: Present Results

步骤4：展示结果

Parse and present the results in a user-friendly format:

For DLO List:

Show DLO name, label, category, and ID
Indicate total count
Highlight DLOs with data (totalRecords > 0)

For DLO Schema:

Show basic info (name, label, category, status)
List all fields with:
- Field name
- Data type
- Primary key indicator
- Nullable status
Highlight custom fields (exclude system fields like DataSource__c, cdp_sys_*)
Show record count if available

For DMO List:

Show DMO name, label, category, and ID
Indicate total count

For DMO Schema:

Show basic info (name, label, category, description)
List all fields with:
- Field name
- Data type
- Primary key indicator
- Nullable status
Show dataspace information if available

解析结果并以用户友好的格式展示：

DLO列表：

显示DLO名称、标签、类别和ID
标注总数
高亮显示包含数据的DLO（totalRecords > 0）

DLO架构：

显示基本信息（名称、标签、类别、状态）
列出所有字段，包括：
- 字段名称
- 数据类型
- 主键标识
- 可空状态
高亮显示自定义字段（排除DataSource__c、cdp_sys_*等系统字段）
若有可用数据则显示记录数

DMO列表：

显示DMO名称、标签、类别和ID
标注总数

DMO架构：

显示基本信息（名称、标签、类别、描述）
列出所有字段，包括：
- 字段名称
- 数据类型
- 主键标识
- 可空状态
若有可用数据则显示数据空间信息

Step 5: Offer Next Steps

步骤5：提供后续操作建议

After displaying results, suggest relevant follow-up actions:

Query data from the DLO
Create calculated insights
Build segments
Set up data streams
Create DMO mappings

展示结果后，建议相关的后续操作：

查询DLO中的数据
创建计算洞察
构建细分群体
设置数据流
创建DMO映射

API Endpoints Used

使用的API端点

List All DLOs

列出所有DLO

text

GET /services/data/v64.0/ssot/data-lake-objects

Response structure:

json

{
  "dataLakeObjects": [
    {
      "name": "Employee__dll",
      "label": "Employee",
      "category": "Profile",
      "id": "1dlXXXXXXXXXXXXXXX",
      "status": "ACTIVE",
      "totalRecords": 12,
      "fields": [...]
    }
  ],
  "totalSize": 5
}

text

GET /services/data/v64.0/ssot/data-lake-objects

响应结构：

json

{
  "dataLakeObjects": [
    {
      "name": "Employee__dll",
      "label": "Employee",
      "category": "Profile",
      "id": "1dlXXXXXXXXXXXXXXX",
      "status": "ACTIVE",
      "totalRecords": 12,
      "fields": [...]
    }
  ],
  "totalSize": 5
}

Get DLO Schema

获取DLO架构

text

GET /services/data/v64.0/ssot/data-lake-objects/{dlo_name}

Response structure (same as individual object in list response, but wrapped in paginated format).

text

GET /services/data/v64.0/ssot/data-lake-objects/{dlo_name}

响应结构（与列表响应中的单个对象相同，但包裹在分页格式中）。

List All DMOs

列出所有DMO

text

GET /services/data/v64.0/ssot/data-model-objects

Response structure:

json

{
  "dataModelObjects": [
    {
      "name": "Individual__dlm",
      "label": "Individual",
      "category": "Profile",
      "id": "0dmXXXXXXXXXXXXXXX",
      "fields": [...]
    }
  ],
  "totalSize": 10
}

text

GET /services/data/v64.0/ssot/data-model-objects

响应结构：

json

{
  "dataModelObjects": [
    {
      "name": "Individual__dlm",
      "label": "Individual",
      "category": "Profile",
      "id": "0dmXXXXXXXXXXXXXXX",
      "fields": [...]
    }
  ],
  "totalSize": 10
}

Get DMO Schema

获取DMO架构

text

GET /services/data/v64.0/ssot/data-model-objects/{dmo_name}

Response structure (same as individual object in list response, but wrapped in paginated format).

text

GET /services/data/v64.0/ssot/data-model-objects/{dmo_name}

响应结构（与列表响应中的单个对象相同，但包裹在分页格式中）。

Error Handling

错误处理

Common Issues:

Org not connected
- Message: "Org not connected"
- Solution: Ask user to authenticate via SF CLI
DLO not found
- Message: "DLO 'XYZ__dll' not found"
- Solution: List all DLOs first to verify name
DMO not found
- Message: "DMO 'XYZ__dlm' not found"
- Solution: List all DMOs first to verify name
Permission issues
- Message: HTTP 403 errors
- Solution: Verify user has Data Cloud permissions
API version mismatch
- Current: v64.0
- Solution: Script can be updated for newer API versions

常见问题：

组织未连接
- 提示信息："Org not connected"
- 解决方案：请用户通过SF CLI完成身份验证
DLO未找到
- 提示信息："DLO 'XYZ__dll' not found"
- 解决方案：先列出所有DLO以验证名称
DMO未找到
- 提示信息："DMO 'XYZ__dlm' not found"
- 解决方案：先列出所有DMO以验证名称
权限问题
- 提示信息：HTTP 403错误
- 解决方案：验证用户是否拥有Data Cloud权限
API版本不匹配
- 当前版本：v64.0
- 解决方案：可更新脚本以适配更高版本的API

Example Usage

示例用法

Example 1: List all DLOs

text

User: "Show me all DLOs in afvibe org"

Response:
1. Run sf org list to discover connected org alias
2. Authenticate to afvibe
3. Run: python3 ./scripts/get_dlo_schema.py afvibe
4. Display formatted list of DLOs

Example 2: Get specific DLO schema

text

User: "Get the schema for Employee__dll in afvibe"

Response:
1. Run sf org list to discover connected org alias
2. Authenticate to afvibe
3. Run: python3 ./scripts/get_dlo_schema.py afvibe Employee__dll
4. Display field schema with types and metadata

Example 3: Explore DLOs then get schema

text

User: "What DLOs exist in myorg and show me the schema for the Employee one"

Response:
1. Run sf org list to discover connected org alias
2. List all DLOs in myorg
3. Identify Employee__dll
4. Get detailed schema for Employee__dll
5. Present both results

Example 4: List all DMOs

text

User: "Show me all DMOs in afvibe org"

Response:
1. Run sf org list to discover connected org alias
2. Authenticate to afvibe
3. Run: python3 ./scripts/get_dmo_schema.py afvibe
4. Display formatted list of DMOs

Example 5: Get specific DMO schema

text

User: "Get the schema for Individual__dlm in afvibe"

Response:
1. Run sf org list to discover connected org alias
2. Authenticate to afvibe
3. Run: python3 ./scripts/get_dmo_schema.py afvibe Individual__dlm
4. Display field schema with types and metadata

Example 6: Explore DMOs then get schema

text

User: "What DMOs exist in myorg and show me the schema for the Individual one"

Response:
1. Run sf org list to discover connected org alias
2. List all DMOs in myorg
3. Identify Individual__dlm
4. Get detailed schema for Individual__dlm
5. Present both results

示例1：列出所有DLO

text

用户："显示afvibe组织中的所有DLO"

响应：
1. 运行sf org list发现已连接的组织别名
2. 完成afvibe组织的身份验证
3. 运行：python3 ./scripts/get_dlo_schema.py afvibe
4. 展示格式化的DLO列表

示例2：获取特定DLO的架构

text

用户："获取afvibe组织中Employee__dll的架构"

响应：
1. 运行sf org list发现已连接的组织别名
2. 完成afvibe组织的身份验证
3. 运行：python3 ./scripts/get_dlo_schema.py afvibe Employee__dll
4. 展示包含类型和元数据的字段架构

示例3：先探索DLO再获取架构

text

用户："myorg组织中有哪些DLO？请展示Employee相关的架构"

响应：
1. 运行sf org list发现已连接的组织别名
2. 列出myorg组织中的所有DLO
3. 定位到Employee__dll
4. 获取Employee__dll的详细架构
5. 展示上述两项结果

示例4：列出所有DMO

text

用户："显示afvibe组织中的所有DMO"

响应：
1. 运行sf org list发现已连接的组织别名
2. 完成afvibe组织的身份验证
3. 运行：python3 ./scripts/get_dmo_schema.py afvibe
4. 展示格式化的DMO列表

示例5：获取特定DMO的架构

text

用户："获取afvibe组织中Individual__dlm的架构"

响应：
1. 运行sf org list发现已连接的组织别名
2. 完成afvibe组织的身份验证
3. 运行：python3 ./scripts/get_dmo_schema.py afvibe Individual__dlm
4. 展示包含类型和元数据的字段架构

示例6：先探索DMO再获取架构

text

用户："myorg组织中有哪些DMO？请展示Individual相关的架构"

响应：
1. 运行sf org list发现已连接的组织别名
2. 列出myorg组织中的所有DMO
3. 定位到Individual__dlm
4. 获取Individual__dlm的详细架构
5. 展示上述两项结果

Output Format

输出格式

DLO List Output

DLO列表输出

text

Found 5 DLOs in org 'afvibe':

1. DataCustomCodeLogs__dll
   Label: DataCustomCodeLogs
   Category: Engagement
   Records: 233

2. Employee__dll
   Label: Employee
   Category: Profile
   Records: 12

[...]

text

在组织'afvibe'中找到5个DLO：

1. DataCustomCodeLogs__dll
   标签：DataCustomCodeLogs
   类别：Engagement
   记录数：233

2. Employee__dll
   标签：Employee
   类别：Profile
   记录数：12

[...]

DLO Schema Output

DLO架构输出

yaml

DLO: Employee__dll
Label: Employee
Category: Profile
Status: ACTIVE
Records: 12

Custom Fields:
  • id__c (Text) - Primary Key
  • name__c (Text)
  • position__c (Text)
  • manager_id__c (Number)

System Fields:
  • DataSource__c (Text)
  • InternalOrganization__c (Text)
  • cdp_sys_SourceVersion__c (Text)

Next steps:
- Query data: SELECT * FROM Employee__dll LIMIT 10
- Create segment based on position field
- Set up data stream for real-time updates

yaml

DLO: Employee__dll
标签: Employee
类别: Profile
状态: ACTIVE
记录数: 12

自定义字段:
  • id__c (文本) - 主键
  • name__c (文本)
  • position__c (文本)
  • manager_id__c (数字)

系统字段:
  • DataSource__c (文本)
  • InternalOrganization__c (文本)
  • cdp_sys_SourceVersion__c (文本)

后续操作建议:
- 查询数据: SELECT * FROM Employee__dll LIMIT 10
- 基于position字段创建细分群体
- 设置数据流以实现实时更新

DMO List Output

DMO列表输出

text

Found 10 DMOs in org 'afvibe':

1. Individual__dlm
   Label: Individual
   Category: Profile

2. ContactPointEmail__dlm
   Label: Contact Point Email
   Category: Profile

[...]

text

在组织'afvibe'中找到10个DMO：

1. Individual__dlm
   标签：Individual
   类别：Profile

2. ContactPointEmail__dlm
   标签：Contact Point Email
   类别：Profile

[...]

DMO Schema Output

DMO架构输出

yaml

DMO: Individual__dlm
Label: Individual
Category: Profile
Description: Represents an individual person

Fields:
  • Id__c (Text) - Primary Key
  • FirstName__c (Text)
  • LastName__c (Text)
  • BirthDate__c (DateTime)

Next steps:
- Query data: SELECT * FROM Individual__dlm LIMIT 10
- View DLO mappings to this DMO
- Create calculated insights

yaml

DMO: Individual__dlm
标签: Individual
类别: Profile
描述: 代表独立个人

字段:
  • Id__c (文本) - 主键
  • FirstName__c (文本)
  • LastName__c (文本)
  • BirthDate__c (日期时间)

后续操作建议:
- 查询数据: SELECT * FROM Individual__dlm LIMIT 10
- 查看与此DMO关联的DLO映射
- 创建计算洞察

Notes

注意事项

DLO names always end with
```
__dll
```
suffix
DMO names always end with
```
__dlm
```
suffix
Field names always end with
```
__c
```
suffix
System fields (DataSource__c, KQ_, cdp_sys_) are automatically added
Primary key fields are required for DLO and DMO queries
API supports pagination (limit/offset) for large result sets

DLO名称始终以
```
__dll
```
后缀结尾
DMO名称始终以
```
__dlm
```
后缀结尾
字段名称始终以
```
__c
```
后缀结尾
系统字段（DataSource__c、KQ_、cdp_sys_）会自动添加
主键字段是DLO和DMO查询的必填项
API支持对大型结果集进行分页（limit/offset参数）

data360-schema-get

Original

Translation

data360-schema-get Skill

data360-schema-get 技能

Overview

概述

When to Use

使用场景

Prerequisites

前提条件

Skill Execution

技能执行

Parameters

参数

Step 1: Discover Connected Org

步骤1：发现已连接的组织

Step 2: Validate SF CLI Authentication

步骤2：验证SF CLI身份验证

Step 3a: Execute DLO Schema Script

步骤3a：执行DLO架构脚本

Step 3b: Execute DMO Schema Script

步骤3b：执行DMO架构脚本

Step 4: Present Results

步骤4：展示结果

Step 5: Offer Next Steps

步骤5：提供后续操作建议

API Endpoints Used

使用的API端点

List All DLOs

列出所有DLO

Get DLO Schema

获取DLO架构

List All DMOs

列出所有DMO

Get DMO Schema

获取DMO架构

Error Handling

错误处理

Example Usage

示例用法

Output Format

输出格式

DLO List Output

DLO列表输出

DLO Schema Output

DLO架构输出

DMO List Output

DMO列表输出

DMO Schema Output

DMO架构输出

Notes

注意事项

Related Skills

相关技能