
Mehdi Nemlaghi developed the AgentCore Session Investigation skill for the awslabs/mcp repository, focusing on enhancing observability and traceability in CloudWatch MCP server workflows. Leveraging AWS, CloudWatch, and OpenTelemetry, Mehdi implemented session-to-trace resolution through span correlation, enabling operators to efficiently map sessions to traces. He created reusable CloudWatch Logs Insights templates in both structured and glob-style formats, and introduced noise-filtering heuristics to improve log analysis quality. The work included Bash and JSON for scripting and configuration, as well as Markdown for documentation, resulting in improved investigation speed, maintainability, and onboarding through targeted code cleanups and comprehensive setup guides.
March 2026: Delivered the AgentCore Session Investigation skill for the CloudWatch MCP server, enabling session-to-trace resolution via OpenTelemetry span correlation, along with ready-to-use CloudWatch Logs Insights templates (structured + glob-style) and noise-filtering heuristics to improve analysis quality. Also shipped MCP setup docs with a Kiro CLI onboarding example to accelerate adoption. Included targeted code/docs cleanups for maintainability. This work enhances observability, speeds up investigations, and improves operator efficiency across AgentCore workflows.
March 2026: Delivered the AgentCore Session Investigation skill for the CloudWatch MCP server, enabling session-to-trace resolution via OpenTelemetry span correlation, along with ready-to-use CloudWatch Logs Insights templates (structured + glob-style) and noise-filtering heuristics to improve analysis quality. Also shipped MCP setup docs with a Kiro CLI onboarding example to accelerate adoption. Included targeted code/docs cleanups for maintainability. This work enhances observability, speeds up investigations, and improves operator efficiency across AgentCore workflows.

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