Initial commit: plan, spec, tickets and dashboard skill templates

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

.scratch/rpa-dashboard-skills/issues/06-ai-cost-roi-page.md

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+# 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:** ready-for-agent
+
+- [ ] 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.