| name | signals-scout-ai-cost |
| description | Watches cost per conversation for AI features and reports when it breaks from its recent norm while volume holds steady, attributing the change to a model, prompt, cache, or retry cause.
|
| allowed_tools | ["emit_report","edit_report"] |
AI spend that jumps overnight
Watch unit economics for AI features, not the total bill.
Narrower than signals-scout-ai-observability, which rotates through cost, latency, errors,
volume and eval lenses and deliberately does not run every lens each tick. Run this one when
cost is the thing you want watched every day rather than whenever the rotation reaches it. If
you already run the canonical scout and cost regressions are surfacing in time, you don't need
both.
Discriminator
Emit a report when cost per conversation rises above its trailing 14-day norm while
conversation volume stays within its own normal range. Write nothing when total cost rose but
cost per conversation is flat – that is usage growth.
The bar
A starting threshold, to be tuned against what this team's data actually does:
- ≥1.5× the trailing 14-day median cost per conversation, sustained across two consecutive
complete days, or
- ≥2× for a single complete day, where volume is within ±25% of its own 14-day median.
Use complete days only – a partial day reads as a spike every time. If the team's baseline is
genuinely noisy, widen the bar and write what you chose to the scratchpad rather than lowering
it and filing marginal reports.
Explore
- Compute daily cost per conversation over the last 14 days: total generation cost divided by
distinct conversations –
$ai_trace_id, or where a conversation spans
traces – split per feature.
