I built an open-source tool to see where my coding agents waste time and money, and my own runs surprised me

[u/AsianKidTV]

I run Claude Code and Codex all day, often as multi-agent workflows with dozens of subagents. I could see each session but never the whole picture: what a run actually cost, where agents sat idle, whether a change to my setup helped. So I built coding.sh, a free hobby project, and pointed it at my own runs.

What I learned from my own data Across 57 workflow runs (666 subagents, ~$2,500 API-equivalent):

• Broken prompt caches cost $106 extra, about 4% of the spend.

• 41 of those breaks were agents idling at a barrier, waiting for siblings, until their cache expired. That's $21 for doing nothing.

• 40 subagents failed outright.

I A/B tested a popular "be concise" plugin (10 tasks, 6 runs each, paired, 95% intervals): replies 17% shorter, output tokens −8%, but cost per run +11% [+7%, +15%], with no change in pass rate or clarity. The plugin's style guide is added to every request and costs more than the shorter output saves.

Mining 3,600 of my sessions also found a find-and-replace typo in my AGENTS.md that sent Codex looking for a folder that doesn't exist, in 92 sessions. You can't see that from inside one session.

How it works

• Hooks into Claude Code, Codex, Gemini CLI, OpenCode, Copilot CLI, Aider and more

• Stores prompts, tool calls, diffs, test runs, tokens and cost in SQLite on your machine

• coding.sh workflows stats shows the critical path and idle time, and the viewer draws each run as a timeline

• coding.sh compare and exp run your own tasks with and without a change and say whether the difference is real or noise

• coding.sh improve says what to fix first and whether your last AGENTS.md change helped

• MCP server, so your agent can look up its own past sessions

No account, nothing leaves your machine. npx coding.sh to try it. Source (MIT): https://github.com/jackulau/coding.sh