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Merge branch 'develop' into npz/createAgent

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Steve Hetzel 2026-05-07 09:36:20 -06:00 committed by GitHub
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2
skills/developing-datacloud-code-extension/SKILL.md
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@ -83,8 +83,8 @@ sf data-code-extension function init --package-dir <directory>
my-transform/ # Project root
├── payload/ # CRITICAL: This is what --package-dir must point to for deploy
│ ├── entrypoint.py # Main transformation code
│ ├── requirements.txt # Python dependencies
│ └── config.json # Code extension configuration
├── requirements.txt # Python dependencies
└── README.md
```

4
skills/developing-datacloud-code-extension/references/README.md
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@ -139,8 +139,8 @@ After `init`, you'll have:
my-transform/
├── payload/
│ ├── entrypoint.py # Your transformation code
│ ├── config.json # Permissions and configuration
│ └── requirements.txt # Python dependencies
│ └── config.json # Permissions and configuration
├── requirements.txt # Python dependencies
└── README.md
```

4
skills/developing-datacloud-code-extension/references/quick-reference.md
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@ -219,8 +219,8 @@ sf data-code-extension script scan --entrypoint ./payload/entrypoint.py
my-project/
├── payload/
│ ├── entrypoint.py # Main code
│ ├── config.json # Auto-generated permissions
│ └── requirements.txt # Auto-generated dependencies
│ └── config.json # Auto-generated permissions
├── requirements.txt # Auto-generated dependencies
└── README.md
```

20
skills/getting-datacloud-schema/SKILL.md
View File

@ -67,30 +67,28 @@ sf org login web --alias <org_alias>
### Step 3a: Execute DLO Schema Script
Use the Python script to retrieve DLO information:
The Python scripts are bundled with this skill. They live in the `scripts/` subdirectory of the same directory that contains this SKILL.md file. Use the absolute path to that directory — do NOT use `./scripts/` as that resolves relative to the current working directory, not the skill directory.
**To list all DLOs:**
```bash
python3 ./scripts/get_dlo_schema.py <org_alias>
python3 <skill_dir>/scripts/get_dlo_schema.py <org_alias>
```
**To get specific DLO schema:**
```bash
python3 ./scripts/get_dlo_schema.py <org_alias> <dlo_name>
python3 <skill_dir>/scripts/get_dlo_schema.py <org_alias> <dlo_name>
```
### Step 3b: Execute DMO Schema Script
Use the Python script to retrieve DMO information:
**To list all DMOs:**
```bash
python3 ./scripts/get_dmo_schema.py <org_alias>
python3 <skill_dir>/scripts/get_dmo_schema.py <org_alias>
```
**To get specific DMO schema:**
```bash
python3 ./scripts/get_dmo_schema.py <org_alias> <dmo_name>
python3 <skill_dir>/scripts/get_dmo_schema.py <org_alias> <dmo_name>
```
### Step 4: Present Results
@ -227,7 +225,7 @@ 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
3. Run: python3 <skill_dir>/scripts/get_dlo_schema.py afvibe
4. Display formatted list of DLOs
```
@ -238,7 +236,7 @@ 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
3. Run: python3 <skill_dir>/scripts/get_dlo_schema.py afvibe Employee__dll
4. Display field schema with types and metadata
```
@ -261,7 +259,7 @@ 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
3. Run: python3 <skill_dir>/scripts/get_dmo_schema.py afvibe
4. Display formatted list of DMOs
```
@ -272,7 +270,7 @@ 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
3. Run: python3 <skill_dir>/scripts/get_dmo_schema.py afvibe Individual__dlm
4. Display field schema with types and metadata
```