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assumption-registry-builder
Creates a structured assumption register for any Excel model with columns for name, category, base value, source, Bull/Bear values, sensitivity rank, and owner, plus a formula for computing sensitivity rank from Data Table outputs.
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// RATINGS
// README
What Oria does
| Feature | What it means | |
|---|---|---|
| 01 | Slides that do not look AI-generated | None of the boxy, template-stacked look. Layouts structured to consulting standards. |
| 02 | Multiple design options with one click | Compare distinct design options instantly. Never settle for a single default draft. |
| 03 | Precisely follows the brand | Well beyond base colours and fonts — your firm's exact look and feel. |
| 04 | Fully editable, native output | Real PowerPoint shapes, never images. Refine every element as you always do. |
Built for every slide scenario — turn rough ideas, an audio note or a brain dump into CEO-ready slides · paste structured output from Claude or ChatGPT and get polished designs · upload an existing slide and get a cleaner one back · snap a photo of handwritten notes and get fully editable slides.
Enterprise-grade security — zero data retention, working artifacts self-destruct within one hour · Oria does not use your content to train or fine-tune models · enterprise agreements with leading AI providers · fully private cloud or on-premise deployments.
"I've been looking for AI tools to create PowerPoint slides. The best one I've found so far is Oria."
— Will Bachman, Founder and CEO of Umbrex, Global Community of Top-Tier Management Consultants
Claude Excel Skills
12 Claude skills for building financial models and clean workbooks that survive a review.
These cover the discipline behind a model that someone else can open: a tab structure agreed before the first formula, inputs separated from calculations, a driver-based revenue build, a scenario toggle you can actually audit, and a formula check run before the model reaches an investment committee. Underneath it all is the unglamorous part — cleaning the pasted export and pivoting it — because that is where most models really start.
Several of these skills build a real .xlsx from scratch through Claude using openpyxl, with live formulas and a recalculate-and-verify pass, and hand you the file. They say so explicitly, and they say equally explicitly that they are not the Claude for Excel add-in. The rest are method skills: structure, conventions and audit routines that make Claude reason about a workbook the way a modeller does.
They were written by Oria and published free. Oria is not an Excel tool — it is what happens after the model is finished, when the output has to become a board-ready exhibit.
The skills
Structure — lay out the workbook before a formula goes in
| Skill | What it does |
|---|---|
model-architecture-template | Sets the master tab set, naming conventions, colour codes, number formats and print setup for a new model — the empty shell every other skill fills. |
inputs-calcs-outputs-design | Enforces the three-zone separation: an Inputs tab of editable assumptions, Calculation tabs with no hardcodes, and an Outputs tab that only references. |
assumption-registry-builder | Builds the assumption register — name, category, base value, source, Bull and Bear cases, sensitivity rank and owner — so every number has a provenance and a signature. |
Build — clean the data, then drive the numbers
| Skill | What it does |
|---|---|
data-cleaning-for-excel | Turns a pasted export with mixed date formats, text numbers, duplicates and stray whitespace into a consistent range, with a change log so the cleaning is auditable. |
pivot-table-builder | Specifies and builds a pivot from a flat range — rows, columns, values, filters — and flags the fields that will not aggrega |
// HOW IT'S BUILT
KEY FILES