#20 · Primary category: AI Usage & Cost Monitoring

agentacct

agent-observability ai-agents analytics claude-code cli codex coding-agent cost-tracking dashboard developer-tools devtools llm llmops local-first mcp observability opencode python token-usage

See what your coding agents did and what it cost. Breaks each task down into work steps — tools used, files changed, tests run, time and tokens spent. Local-first dashboard for Claude Code, Codex, OpenCode, and more. No login, no telemetry.

Project last updated:08/29/26

GitHub Stars

675

Forks

75

Contributors

4

License

MIT

Why we included this project

Coding agents like Claude Code, Codex, OpenCode, and Hermes leave session logs on disk, and agentacct turns those into a per-task work receipt: the commands run, files touched, tools used, time and tokens spent, and which parts of the work carry a passing machine check. The evidence model is the part worth calling out. An agent's own claim is kept separate from hook-observed exit codes and CI results, so a task only reads as verified when independent checks actually pass. Everything runs locally with a loopback-only JSON API, a terminal dashboard, and a macOS app, with no account and no telemetry, which suits teams that want agent observability without shipping logs to a hosted service. Developers and tech leads who need to audit agent work or track token spend per task will find it useful, and it's a decent way to catch agents that report done without real proof.

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