27 lines
1.6 KiB
Markdown
27 lines
1.6 KiB
Markdown
# 06: AI cost page: tokens, cost, monthly spend, model choice
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Part of: ../spec.md
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**What to build:** The AI dashboard gets a cost/ROI page. It shows:
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- input, output and thinking tokens and cost per run;
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- total spend and this month's spend, with a month-by-month breakdown;
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- a coverage pill ("N of M documents priced");
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- an "against doing it by hand" panel with editable assumptions, clearly labelled as assumptions.
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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.
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**Blocked by:** 05
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**Status:** resolved
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- [ ] Cost per call = input tokens × input rate + (output + thinking tokens) × output rate, per million tokens. Long-context rates apply above the threshold.
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- [ ] An unknown model raises an error that names the known models. Cost never silently defaults to zero.
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- [ ] A Python self-check covers normal, long-context, thinking-token and unknown-model cases.
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- [ ] Contract: `RoiRun{model,input_tokens,output_tokens,thinking_tokens,total_cost}` and a fetch-ROI action. (Shape from the Superbill prototype.)
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- [ ] 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.
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- [ ] The model picker and retry-on-other-model are offered as optional sections and built only when chosen.
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## Comments
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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/`.
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