> For the complete documentation index, see [llms.txt](https://cortex-docs.paloaltonetworks.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://cortex-docs.paloaltonetworks.com/cortex-xsiam/configure-cortex-xsiam/automations/lists/use-cases-json-lists/extract-data-from-a-json-object.md).

# Extract data from a JSON object

Create a JSON list and use the **Set** automation to create a context key from its data.

1. Create a List:
   1. In the Name field, type `Test1`.
   2. Select **Settings** → **Configurations** → **Object Setup** → **Lists** → **Add a List**.
   3. In the **Content Type** field, select **JSON** and add the following content:

      ```programlisting
      {    
          "domain": {
              "name": "mwidomain",
              "prod_mode": "prod",
              "user": "weblogic",
              "admin": {
                  "servername": "AdminServer",
                  "listenport": "8001"
              },
              "machines": [
                  {
                      "refname": "Machine1",
                      "name": "MWINODE01"
                  },
                  {
                      "refname": "Machine2",
                      "name": "MWINODE02"
                  }
              ],
              "clusters": [
                  {
                      "refname": "Cluster1",
                      "name": "App1Cluster",
                      "machine": "Box1"
                  },
                  {
                      "refname": "Cluster1",
                      "name": "App2Cluster",
                      "machine": "Box2"
                  }
              ],
              "servers": [
                  {
                      "name": "ms1",
                      "port": 9001,
                      "machine": "Box1",
                      "clusterrefname": "Cluster1"
                  },
                  {
                      "name": "ms2",
                      "port": 9002,
                      "machine": "Box2",
                      "clusterrefname": "Cluster2"
                  }
              ]
          }
      }
      ```
   4. **Save** the list.
2. Create a playbook task with the **Set** automation:
   1. Select **Investigation & Response** → **Automation** → **Playbooks** → **New Playbook**.
   2. Name the playbook, and click Save.
   3. Click Create Task and provide a task name.
   4. In the **Choose Script** field, select **Set** .

      The **Set** script sets a value in context under the key entered.
   5. In the **key** field, define a context key name for the data. For example, JSONData.

      ![](/files/LEkBXAPnxEWoT8SbAEe2)
   6. In the **value** field, set the list you want to extract by clicking the curly brackets.
   7. Click **Filters And Transformers**.
   8. In the **Get** field, click the curly brackets, and in the **Select source for value** section, select the list you created in step 1: **Test1**.
   9. In the **Fetch data** field, select an issue to test the data.
   10. Click **Test**.

       In this example, the test results have found the list data.

       ![](/files/jvP8qddvh1KO4ZbPo8q6)
   11. When the test completes, click **Save**.
   12. Save the task and playbook.
3. Check all the data is stored in the context key you defined by testing the playbook using the debugger:
   1. Click **Run**.
   2. Open the **Debugger Panel**.

      The key you defined, JSONData, holds the data in context from the JSON object.

      ![](/files/E5yYoeMHe6B2at4C7U06)


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://cortex-docs.paloaltonetworks.com/cortex-xsiam/configure-cortex-xsiam/automations/lists/use-cases-json-lists/extract-data-from-a-json-object.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.