Update docs/platforms/javascript/common/tracing/span-metrics/examples.mdx

Co-authored-by: Alex Krawiec <[email protected]>

Author: codyde

docs/platforms/javascript/common/tracing/span-metrics/examples.mdx

@@ -805,7 +805,7 @@ async function synthesizeResponse(llmResponse: any, toolsUsed: string[]): Promis
 **How the trace works together:**
 - Frontend span (`gen_ai.invoke_agent`) captures the entire user interaction from message to response.
 - Backend agent span continues the trace with the same operation and agent name for correlation.
-- LLM spans (`gen_ai.chat`) track individual model calls with token usage and performance.
+- The LLM spans (`gen_ai.chat`) track individual model calls with token usage and performance.
 - The tool execution spans (`gen_ai.execute_tool`) monitor each tool call with input/output and timing.
 - Rich attributes enable monitoring of conversation quality, cost, and business outcomes.