# A 5-column CSV that stops your AI agents from silently burning money

> Source: <https://dev.to/renev3408/a-5-column-csv-that-stops-your-ai-agents-from-silently-burning-money-3o98>
> Published: 2026-10-15 22:39:03+00:00

Most agent cost problems are not model-pricing problems. They are *untracked-run* problems: nobody can say which run spent what, for which task, and whether the output was used.

Here is the minimal tracking schema I use for every autonomous agent run. You can start with just a CSV.

| column | why it matters | 
|---|---|
| `run_id` | lets you join logs, costs and outcomes | 
| `agent_role` | which agent spent the money | 
| `tokens_in / tokens_out` | the raw driver of cost | 
| `cost_usd` | computed at write time, not at month end | 
| `outcome` | `shipped` ,`no_action` ,`failed` ,`retried` | 

`cost_usd` divided by the count of `outcome = shipped`. If it is rising, your agents are getting less efficient.` outcome = no_action`. This is pure waste, and it is often 20-40% of spend in loops that re-read state without acting.

``` python
import csv, time, pathlib

PATH = pathlib.Path('agent_runs.csv')

def log_run(run_id, role, tin, tout, cost, outcome):
    new = not PATH.exists()
    with PATH.open('a', newline='') as f:
        w = csv.writer(f)
        if new:
            w.writerow(['ts','run_id','role','tokens_in','tokens_out','cost_usd','outcome'])
        w.writerow([time.strftime('%Y-%m-%dT%H:%M:%S'), run_id, role, tin, tout, round(cost, 4), outcome])
```

Call it in a `finally` block so failed runs are recorded too. Failed runs are where the money hides.

I packaged this schema as a Notion database template plus a CSV starter and the three views above, so you do not have to wire it up yourself: **Agent Ops Tracker (Notion + CSV)** - [https://renevibe76.gumroad.com/l/ptfvli](https://renevibe76.gumroad.com/l/ptfvli) (pay what you want, minimum $1).

The CSV approach above is fully enough to get started, though. The habit matters more than the tool.

What do you track per agent run? I am curious whether anyone measures cost per *useful* outcome rather than cost per call.