OTel: parallel task dispatch emits successful chat spans without response identity or usage

Describe the bug

With metadata-only OpenTelemetry file export enabled, a prompt-mode run that dispatches two named subagents emits two chat spans that have successful status and a stop finish reason but omit all of:

• gen_ai.response.id
• gen_ai.response.model
• gen_ai.usage.input_tokens
• gen_ai.usage.output_tokens

This also occurs when the parent model is explicitly pinned, so it is not limited to --model auto.

The remaining parent and subagent chat spans in the same trace contain complete request/response model and usage fields.

Affected version

GitHub Copilot CLI 1.0.83 on macOS.

Steps to reproduce

1. Enable the file exporter and force content capture off.
2. Run prompt mode with streaming enabled and an explicitly pinned parent model.
3. In one synthetic prompt, use the task tool twice with two named agent types and explicit models.
4. Parse the resulting JSONL.

A representative trace contained one root invoke_agent, two execute_tool task spans, two nested named invoke_agent spans, and seven chat spans. Every completed-response chat had the expected provider, request model, response model, response ID, and usage. Two root-level chats had request model, streaming=true, status code 0, and finish reason stop, but no response identity or usage.

Expected behavior

Each logical completed inference should contain independently reported response identity and usage when available. An abandoned, cancelled, routing, or retry attempt should not look like a successful completed chat: it should carry an explicit attempt/outcome classification or a non-success terminal status. Consumers must not have to synthesize gen_ai.response.model from the requested model.

Privacy

The reproduction used synthetic prompts with OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=false. No prompt, response, repository, or credential content is included here.

Inizia riproducendo il trace di prompt-mode con esportazione OpenTelemetry di soli metadati, streaming, un modello padre esplicitamente fissato e due agenti di task denominati. Analizza il JSONL risultante e confronta i due span di chat incompleti a livello root con gli span di chat completi. Il lavoro è completato quando ogni inferenza completata riporta l'identità della response e l'utilizzo quando disponibili, mentre i tentativi abbandonati o non completati non vengono contrassegnati come riusciti.