# 06: AI cost page: tokens, cost, monthly spend, model choice

Part of: ../spec.md

**What to build:** The AI dashboard gets a cost/ROI page. It shows:
- input, output and thinking tokens and cost per run;
- total spend and this month's spend, with a month-by-month breakdown;
- a coverage pill ("N of M documents priced");
- an "against doing it by hand" panel with editable assumptions, clearly labelled as assumptions.

Cost comes from a pricing table that records its source and its as-of date. Optionally, the skill also adds a model picker for each batch and retry-on-another-model for failed runs.

**Blocked by:** 05

**Status:** resolved

- [ ] Cost per call = input tokens × input rate + (output + thinking tokens) × output rate, per million tokens. Long-context rates apply above the threshold.
- [ ] An unknown model raises an error that names the known models. Cost never silently defaults to zero.
- [ ] A Python self-check covers normal, long-context, thinking-token and unknown-model cases.
- [ ] Contract: `RoiRun{model,input_tokens,output_tokens,thinking_tokens,total_cost}` and a fetch-ROI action. (Shape from the Superbill prototype.)
- [ ] The page check asserts that the spend tiles sum the runs, the coverage pill counts priced vs. total documents, and the month breakdown groups runs correctly.
- [ ] The model picker and retry-on-other-model are offered as optional sections and built only when chosen.

## Comments

Resolved on branch `integration/rpa-dashboard-skills` (Oct 16, 2026). Tests: `uv run --with pytest --with playwright pytest tests` all green; skill eval results in `tests/evals/results/`.