Data 36028 tasks
Analyze Agentforce Observability Data
A user gets answers about how their Agentforce agents are used and how they perform. MeshMesh queries the session, trace and LLM request data stored in Data 360. It turns that data into insights or reports, and fixes the pipeline when the data is missing.
Method
How MeshMesh does it
- Checks whether the Agentforce observability data model objects hold any data. When reports come up blank, it traces the cause back to the pipeline.
- Creates missing DLO-to-DMO mappings so queries can join session data to objects such as User.
- Builds Calculated Insights on the data, such as token and credit consumption measures.
- When real data is not available, loads synthetic observability data. It then checks DMO field names and platform requirements to find out why analytics fields stay empty.
- Where asked, builds, publishes and activates a simple Agent Script agent that answers usage questions.
- Writes up the workflow as a reusable recipe or HTML artifact for later sessions.
Products
Products and features it works with
Bars show how many of this capability's tasks touched each product.