SKILL.md
sf-ai-agentforce-observability: Agentforce Session Tracing Extraction & Analysis
Use this skill when the user needs trace-based observability, not just testing: extract Session Tracing Data Model (STDM) records, work with Parquet datasets, reconstruct session timelines, analyze topic/action latency, or debug agent behavior from Data 360 telemetry.
When This Skill Owns the Task
Use sf-ai-agentforce-observability when the work involves:
- Data 360 / Session Tracing extraction
.parquetfiles from Agentforce telemetry- session timeline reconstruction
- trace-driven debugging of topic routing, action failures, or latency
- Polars / PyArrow-based analysis of large telemetry datasets
Delegate elsewhere when the user is:
- formally testing agents → sf-ai-agentforce-testing
- debugging Apex logs → sf-debug
- authoring or reconfiguring the agent itself → sf-ai-agentforce or sf-ai-agentscript
sf-ai-agentforce-observability: Agentforce Session Tracing Extraction & Analysis
Use this skill when the user needs trace-based observability, not just testing: extract Session Tracing Data Model (STDM) records, work with Parquet datasets, reconstruct session timelines, analyze topic/action latency, or debug agent behavior from Data 360 telemetry.
When This Skill Owns the Task
Use sf-ai-agentforce-observability when the work involves:
- Data 360 / Session Tracing extraction
.parquetfiles from Agentforce telemetry- session timeline reconstruction
- trace-driven debugging of topic routing, action failures, or latency
- Polars / PyArrow-based analysis of large telemetry datasets
Delegate elsewhere when the user is:
- formally testing agents → sf-ai-agentforce-testing
- debugging Apex logs → sf-debug
- authoring or reconfiguring the agent itself → sf-ai-agentforce or sf-ai-agentscript