OTel: propagate GenAI semantic attrs to gh-aw.agent.conclusion spans (#33245)

Author: Copilot

.github/workflows/smoke-otel-backends.lock.yml

@@ -1747,6 +1747,15 @@ async function sendJobConclusionSpan(spanName, options = {}) {
   if (typeof runtimeMetrics.estimatedCostUsd === "number") {
     attributes.push(buildAttr("gh-aw.estimated_cost_usd", runtimeMetrics.estimatedCostUsd));
   }
+  if (jobName === "agent") {
+    // Emit OTel GenAI semantic attributes on agent conclusion spans even when the
+    // dedicated agent sub-span is missing, so LLM activity remains discoverable.
+    attributes.push(buildAttr("gen_ai.operation.name", "chat"));
+    if (workflowName) attributes.push(buildAttr("gen_ai.workflow.name", workflowName));
+    if (runtimeMetrics.stopReason) {
+      attributes.push(buildArrayAttr("gen_ai.response.finish_reasons", [runtimeMetrics.stopReason]));
+    }
+  }
 
   if (agentConclusion) {
     attributes.push(buildAttr("gh-aw.agent.conclusion", agentConclusion));
@@ -1939,20 +1948,8 @@ async function sendJobConclusionSpan(spanName, options = {}) {
     // Token-usage attributes are included here (and only here) to prevent
     // double-counting with the conclusion span.
     const agentAttributes = [...attributes, ...usageAttrs];
-    // gen_ai.operation.name is Required by the OTel GenAI spec for inference spans.
-    // All gh-aw agent executions are chat-style LLM completions.
-    agentAttributes.push(buildAttr("gen_ai.operation.name", "chat"));
-    // gen_ai.request.model is already present in agentAttributes via the spread above
-    // (added to attributes at the top of this function); do not push again.
-    // gen_ai.workflow.name identifies the agentic workflow, matching the OTel spec example
-    // use-cases (e.g. "multi_agent_rag", "customer_support_pipeline").
-    if (workflowName) agentAttributes.push(buildAttr("gen_ai.workflow.name", workflowName));
-    // gen_ai.response.finish_reasons is a standard OTel GenAI response attribute (array of strings).
-    // It exposes the stop_reason from the agent's result line so operators can detect truncated
-    // runs (e.g. "max_tokens") that would otherwise silently appear as STATUS_OK.
-    if (runtimeMetrics.stopReason) {
-      agentAttributes.push(buildArrayAttr("gen_ai.response.finish_reasons", [runtimeMetrics.stopReason]));
-    }
+    // gen_ai.operation.name / gen_ai.workflow.name / gen_ai.response.finish_reasons
+    // are already included via the shared attributes list above.
 
     const agentPayload = buildOTLPPayload({
       traceId,

actions/setup/js/send_otlp_span.cjs

@@ -2820,6 +2820,12 @@ describe("sendJobConclusionSpan", () => {
     expect(attrs["gh-aw.engine.id"]).toBe("claude");
     expect(attrs["gh-aw.engine"]).toBeUndefined();
     expect(attrs["gen_ai.workflow.name"]).toBe("otel-advisor");
+
+    const conclusionBody = JSON.parse(mockFetch.mock.calls[1][1].body);
+    const conclusionSpan = conclusionBody.resourceSpans[0].scopeSpans[0].spans[0];
+    const conclusionAttrs = Object.fromEntries(conclusionSpan.attributes.map(a => [a.key, a.value.stringValue ?? a.value.intValue]));
+    expect(conclusionAttrs["gen_ai.operation.name"]).toBe("chat");
+    expect(conclusionAttrs["gen_ai.workflow.name"]).toBe("otel-advisor");
   });
 
   it("does not duplicate gen_ai.request.model on the agent span", async () => {
@@ -2970,6 +2976,12 @@ describe("sendJobConclusionSpan", () => {
     const finishAttr = agentSpan.attributes.find(a => a.key === "gen_ai.response.finish_reasons");
     expect(finishAttr).toBeDefined();
     expect(finishAttr.value.arrayValue.values).toEqual([{ stringValue: "end_turn" }]);
+
+    const conclusionBody = JSON.parse(mockFetch.mock.calls[1][1].body);
+    const conclusionSpan = conclusionBody.resourceSpans[0].scopeSpans[0].spans[0];
+    const conclusionFinishAttr = conclusionSpan.attributes.find(a => a.key === "gen_ai.response.finish_reasons");
+    expect(conclusionFinishAttr).toBeDefined();
+    expect(conclusionFinishAttr.value.arrayValue.values).toEqual([{ stringValue: "end_turn" }]);
   });
 
   it("omits gen_ai.response.finish_reasons from the agent span when stop_reason is absent in agent-stdio.log", async () => {
@@ -2999,6 +3011,11 @@ describe("sendJobConclusionSpan", () => {
     expect(agentSpan.name).toBe("gh-aw.agent.agent");
     const keys = agentSpan.attributes.map(a => a.key);
     expect(keys).not.toContain("gen_ai.response.finish_reasons");
+
+    const conclusionBody = JSON.parse(mockFetch.mock.calls[1][1].body);
+    const conclusionSpan = conclusionBody.resourceSpans[0].scopeSpans[0].spans[0];
+    const conclusionKeys = conclusionSpan.attributes.map(a => a.key);
+    expect(conclusionKeys).not.toContain("gen_ai.response.finish_reasons");
   });
 
   it("includes gen_ai.response.finish_reasons with max_tokens on the agent span when truncated", async () => {