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

@@ -806,7 +806,7 @@ async function synthesizeResponse(llmResponse: any, toolsUsed: string[]): Promis
 - 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.
-- Tool execution spans (`gen_ai.execute_tool`) monitor each tool call with input/output and timing.
+- 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.
 
 **What to monitor with span metrics:**