Pattern Proposal: Telemetry-Grounded Trace and Evaluation Loop

Summary

Instruments agent step execution with OpenTelemetry spans and persists evaluation reports to the runtime knowledge directory for post-hoc analysis.

Candidate Pattern

• ID: telemetry-grounded-evaluations
• Classification: intelligence
• Maturity: strategic_direction
• Type: emerging

Observed Signals

No specific signals listed.

Evidence

Supporting Evidence

• pyproject.toml (opentelemetry-api, opentelemetry-sdk) - Dependencies for distributed tracing of agent execution
• src/cas_runner/dashboard/health_model.py (HealthStatus, calculate_health) - Health model deriving operational status from recorded metrics
• cas-knowledge/runtime/traces/ - Persistence location for runtime execution traces

Scope Assessment

• Evidence Strength: high
• Confidence: high
• Applies to: ideas-to-life-cas

Rationale

• Intent: Maintain continuous visibility into agentic latency, failure rates, model drift, and cost across batch and CI runs.
• Context: FlowRunner execution, runtime traces directory (cas-knowledge/runtime/traces/), and health dashboard models.
• Force: Agent pipelines fail silently or non-deterministically without structured execution traces
• Force: Performance optimization is impossible without granular step-level duration and token metrics

Traceability

Artifact source: proposed-patterns