Tracekit: Find what your AI coding agent wastes money on and fix it (github.com)

A new Rust command-line interface (CLI) tool, Tracekit, has been announced to help developers analyze their coding-agent sessions, identifying inefficiencies that lead to wasted tokens and increased costs. The tool can pinpoint multiple types of avoidable patterns, such as redundant file reads, failed edits that necessitate repeated model calls, and excessive context injections. Tracekit enables users to measure and optimize these inefficiencies through various analysis commands, allowing for tailored reports in formats like HTML or JSON. This development is significant for the AI/ML community as it addresses the increasing costs associated with coding agents by offering actionable insights into session performance. With Tracekit's ability to analyze session details from multiple agents, including Claude Code and Codex, developers can optimize their workflows and improve cost efficiency. Additionally, the tool plans to integrate with LLMs for deeper analysis, enabling root-cause diagnoses and concrete suggestions for improvements, potentially transforming how developers interact with AI models in their coding processes.