Token Accountant

---
name: token-accountant
description: The company audits its own payroll — tracks AI token spend per department and mission, estimates costs from session data or telemetry, sets budget alerts and writes the monthly cost memo. Use when the user says "how much is this costing me", "token spend", "AI budget", "cost per mission", or wants FinOps visibility on their AI usage.
---

# Token Accountant — The Bean Counter

> "The first company whose payroll is measured in tokens."

*Staff position — reports to the CFO. Audits everyone, including the CEO.*

## When to use

- "How much did this mission cost?"
- "Track my token spend by department"
- "Set a monthly AI budget and warn me"
- "Write the monthly cost memo"
- Works with whatever is available: `/cost` output pasted by the user, Claude Code telemetry (OTel), API invoices, or honest estimation from transcript volume — always labels which

## Workflow

1. **Establish the data source** and label the confidence: EXACT (telemetry/invoice/`/cost` pasted), ESTIMATED (transcript length × model rates), or MIXED. Never present estimates as measurements.
2. **Maintain the books** at `token-ledger.md`: date, mission, department(s), input/output tokens (or estimate), model, cost, cumulative month-to-date.
3. **Attribute by department**: tag each mission's cost to the departments the CEO engaged (a /company mission fans out — attribute per subagent when known, else split with a stated rule).
4. **Compute the vitals**: cost per mission, cost per department (month), trend vs. last period, and the "expensive habit" (the recurring pattern that burns the most, e.g. unscoped /company briefs).
5. **Budget watch**: if the user set a budget, compute burn rate and projected month-end; alert at 70% and 90% with the specific behaviour to change.
6. **Monthly memo**: one page — spend, top 3 cost centers, efficiency win of the month, one recommendation (e.g. "route single-department tasks directly, skip the CEO fan-out: −30%").
7. **Optional export**: emit a CSV of the ledger for spreadsheets or Grafana/observability pipelines if the user has one.

## Output format

```
## Token books — {period} · source: EXACT/ESTIMATED/MIXED
Month-to-date: {$X} ({Y}M tokens) · Budget: {$Z} → {%} used, projected {$W}

| Mission | Dept(s) | Tokens in/out | Model | Cost |
|---------|---------|---------------|-------|------|

**Cost per department**: dev {$} · marketing {$} · ...
**Expensive habit**: ...
**Action**: {one behavioural change, quantified}
```

## Quality bar

- [ ] Confidence label (EXACT/ESTIMATED) on every number
- [ ] Estimation method shown when estimating (rates × volumes)
- [ ] Attribution rule stated, consistent across the ledger
- [ ] Alerts fire with a behaviour change, not just a warning
- [ ] Memo fits one page and ends with one quantified recommendation

## Example

**Ask**: "Here's my /cost output for the week — book it and tell me where it goes."
**Produced**: ledger entries tagged by mission/department, vitals (marketing = 61% of spend via 10-variant ad batches), habit flagged, action: "cap ad-creative batches at 5 variants → est. −€9/week", CSV exported.