DEDUPED Hot AI repos, turned into use cases Get 5 a day

How to see what your coding agents did and what it cost with Agentacct

Install Agentacct once and review recent agent tasks, tool calls, tokens, and estimated cost on your machine.

Who it is forA developer who runs several coding agents across projects and wants to know what they worked on last week and roughly what it cost.

The problemAgent sessions are spread across client log files, so it is hard to tell which task changed which files, what ran, and how many tokens it used.

The outcomeA local dashboard and terminal app listing recent tasks with their receipts, steps, checks, tokens, and cost estimates, with nothing sent off the machine.

What you need first

  • Python 3.11 or newer on macOS or Linux, or Windows through WSL, with pipx available (or the signed macOS app from the latest release on macOS 14+)
  • At least one supported coding agent with local session logs on this machine, such as Claude Code or Codex
  • Permission to open a new agent session after setup, because hooks and MCP servers bind at session start

Steps

  1. Run pipx install agentacct
  2. Run agentacct onboard once on this machine so it finds your agents and starts the recorder
  3. Open a new agent session so hooks and MCP servers bind
  4. Run agentacct tui and open Sessions to see the most recently active tasks

Prompt for your agent

Install agentacct from https://github.com/mikehasa/agentacct on this machine using pipx, then run agentacct onboard. Report the most recent task names and their estimated costs in <project path>, and confirm that costs are marked as estimates. Verify that the Sessions view opens in agentacct tui.

Caveat. Costs are pricing-table estimates rather than invoices, and Windows is supported only through WSL.

Share: X LinkedIn Hacker News Email Copy link

Disclaimer

Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked "Seen in the wild", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email [email protected] and we will look at it promptly. Full disclaimer page