Multi-Agent Orchestration Observability and Telemetry Specification
Specify distributed tracing, token accounting, causal state tracking, and SLO telemetry for complex multi-agent execution graphs.
Use this template when deploying production-grade multi-agent debugging or engineering workflows that require fine-grained observability. It defines a unified telemetry standard covering distributed trace propagation, latency budgets, and cost governance.
Role: Staff Site Reliability Engineer specializing in distributed agent runtime observability and telemetry pipelines.
Context
- Orchestration Framework: {{orchestration_engine}}
- Workflow DAG Structure: {{workflow_dag_topology}}
- Telemetry Backend: {{telemetry_backend}}
- Target Latency SLOs: {{slo_latency_targets}}
- Trace Export Standard: {{telemetry_export_standard}}
- Total Cost & Token Budget: {{cost_budget_ceiling}}
Task
Produce an Observability and Telemetry Specification Report that establishes distributed tracing standards, metric instrumentation, and anomaly detection rules across the multi-agent execution graph.
Method
- Define trace context propagation mechanisms across asynchronous node boundaries in {{orchestration_engine}} using {{telemetry_export_standard}}.
- Design span models for LLM calls, tool executions, vector retrievals, and deterministic evaluation gates within {{workflow_dag_topology}}.
- Establish structured log attributes capture (causal session IDs, node parentage, model version, prompt/completion token splits, temperature).
- Specify latency metrics and warning thresholds aligned with {{slo_latency_targets}} for each critical execution path.
- Formulate real-time token tracking and cost-attribution algorithms to enforce constraints against {{cost_budget_ceiling}}.
- Architect anomaly detection alerts in {{telemetry_backend}} for infinite reasoning loops, context window saturation, and tool error spikes.
- Detail sampling strategies that balance diagnostic depth against telemetry ingestion overhead for high-throughput workflows.
Constraints
- MUST specify W3C Trace Context or native OpenTelemetry propagation headers for all inter-agent messages.
- MUST NOT log raw credentials, PII, or unsanitized proprietary source code within telemetry span attributes.
- Span attributes and metric schemas MUST integrate natively with {{telemetry_backend}}.
- Token attribution mechanisms MUST calculate real-time cumulative spend relative to {{cost_budget_ceiling}}.
Output format
Deliver an engineering specification report divided into four sections:
- Telemetry Architecture & Context Propagation (tracing standard, headers, and span lifecycle)
- Instrumentation Schema (exact key-value semantic conventions for nodes, LLM invocations, and tool executions)
- SLO Monitoring & Alerting Matrix (thresholds, latency baselines matching {{slo_latency_targets}}, and alert rules)
- Cost Governance & Token Accounting Model (budget tracking, burn-rate metrics, and circuit-breaker conditions) Length must be between 900 and 1400 words.
Self-review
- Verify every branch in {{workflow_dag_topology}} has explicit parent-child trace context inheritance.
- Ensure metric definitions align precisely with the capabilities of {{telemetry_backend}}.
- Confirm alert conditions cover both performance degradation (SLOs) and financial overrun ({{cost_budget_ceiling}}).
Explicit role, a named task, and discrete steps the model can follow.
Background, inputs and variables the model needs before it starts.
Hard boundaries — what the model must and must not do.
A named, field-level shape for the response.
Ordered work items that force analysis before an answer.
Length and structure that travel across frontier models.
Signal density — instruction weight without padding.
Documented variables so the scaffold adapts to new inputs.
Quality bar, assumptions and behaviour when inputs are thin.
How much real usage the template has behind it.