| name | product-data-cleanup |
| description | Clean up an FF&E schedule — normalize casing, dimensions, units, language, materials, and formatting for consistency. |
| allowed-tools | ["Read","Write","Edit","Bash","Glob","Grep","AskUserQuestion","mcp__google-sheets__get_sheet_data","mcp__google-sheets__update_cells","mcp__google-sheets__list_sheets"] |
/product-data-cleanup — Product Data Normalizer
Takes a messy FF&E schedule and normalizes everything: casing, dimensions, units, language, materials vocabulary, currency formatting, and duplicates. Outputs a clean, consistent, spec-ready schedule.
Operates on the master Google Sheet — the same 33-column schema used by all product skills. Also works on standalone CSV files and pasted tables.
Input
The user provides a schedule in one of these ways:
- Master Google Sheet — the shared product library. Provide spreadsheet ID or URL.
- File path — a
.csv, .tsv, .xlsx export, or .md file
- Pasted table — markdown or tab-separated data in the message
If the input format is unclear, ask.
Cleanup Rules
1. Casing
| Field | Rule | Example |
|---|
| Product Name | Title Case | eames lounge chair → Eames Lounge Chair |
| Brand | Title Case, preserve known abbreviations | HERMAN MILLER → Herman Miller, HAY → HAY |
| Collection | Title Case | cosm → Cosm |
| Category | Title Case, singular | chairs → Chair, TABLES → Table |
| Materials | Sentence case, lowercase after first word | MOLDED PLYWOOD, FULL GRAIN LEATHER → Molded plywood, full grain leather |
| Colors/Finishes | Title Case per item | walnut/black leather → Walnut / Black Leather |
Known brand abbreviations to preserve: HAY, USM, B&B, DWR, CB2, HBF, OFS, SitOnIt, 3form, ICF
2. Category Normalization
Map free-text categories to the canonical vocabulary and alias table defined in ../../schema/product-schema.md. Read that file for the full mapping of variations (English, Spanish, legacy terms) to canonical category names.
If a category is ambiguous, keep the closest match and add a [?] flag for the user to review.
3. Dimensions
Splitting combined dimensions:
| Input | → W | → D | → H | → Unit |
|---|
32 x 24 x 30 in | 32 | 24 | 30 | in |
80 × 60 × 75 cm | 80 | 60 | 75 | cm |
W32 D24 H30 | 32 | 24 | 30 | (infer) |
32"W x 24"D x 30"H | 32 | 24 | 30 | in |
Ancho: 80, Prof: 60, Alto: 75 cm | 80 | 60 | 75 | cm |
Dimension rules:
- Always store as separate W, D, H columns with a Unit column
- If dimensions are already split, validate they're numeric (strip any unit text from the number)
- Interpret
" as inches, ' as feet (convert to inches: 2'6" → 30)
- Accept
×, x, X, by, por as separators
- Convention: W × D × H (width × depth × height). If only 2 values, ask which is missing.
- Round to 2 decimal places max
- If unit is missing but values suggest inches (all < 100 for furniture), assume
in. If values suggest cm (> 100 or explicit), use cm. If truly ambiguous, flag with [?].
Do NOT convert units. Keep the original unit. Designers need the manufacturer's spec for ordering.
4. Language Normalization
Detect the language of each field value and normalize to English unless the user specifies otherwise.
| Spanish (common in UY sources) | → English |
|---|
| Silla | Chair (category) |
| Mesa | Table (category) |
| Escritorio | Desk (category) |
| Madera | Wood (material) |
| Cuero | Leather (material) |
| Acero | Steel (material) |
| Vidrio | Glass (material) |
| Tela | Fabric (material) |
| Mármol | Marble (material) |
| Roble | Oak (material) |
| Nogal | Walnut (material) |
| Blanco | White (color) |
| Negro | Black (color) |
| Natural | Natural (keep as-is) |
| Cromado | Chrome (finish) |
Rule: Translate category, material, and color/finish fields. Leave Product Name and Brand as-is (proper nouns).
If the user says "keep in Spanish" or specifies a target language, respect that.
5. Materials & Finishes Vocabulary
Standardize common material terms:
| Variations | → Standard |
|---|
| SS, Stainless, S/S | Stainless steel |
| Ply, Plywood, Mold ply | Molded plywood |
| MDF, Medium density | MDF |
| HPL, High pressure laminate | HPL |
| Lam, Laminate | Laminate |
| Fab, Textile | Fabric |
| COM, C.O.M. | COM (Customer's Own Material) |
| COL, C.O.L. | COL (Customer's Own Leather) |
| Powder coat, PC, Pwdr | Powder-coated |
| Chrm, Chrome plated | Chrome |
| Anodized alum, Anod. | Anodized aluminum |
| Ven, Veneer | Veneer |
| Sol. wood, Solid | Solid wood |
6. Price & Currency
- Strip currency symbols (
$, €, £, ¥) — store symbol as currency code in separate column
- Remove thousands separators (both
. and , — detect locale: 1.234,56 is EU format, 1,234.56 is US)
- Store as plain decimal number:
5695.00
- If price says "Contact", "Quote", "Trade", "A consultar", "Consultar" → set to empty
- Currency detection:
$ alone defaults to USD unless context suggests otherwise (UY site → UYU, EU site → EUR)
- If a schedule mixes currencies, keep each row's original currency. Add a note at the top.
7. Duplicate Detection
- Flag rows with identical Product Name + Brand as potential duplicates
- Flag rows with identical URL as definite duplicates
- Don't auto-delete — present duplicates to the user and ask what to keep
8. Whitespace & Formatting
- Trim leading/trailing whitespace from all fields
- Collapse multiple spaces to single space
- Remove line breaks within field values
- Normalize list separators:
wood / metal / glass → Wood, Metal, Glass (comma-separated)
- Remove trailing commas or semicolons
Workflow
Step 1: Load the schedule
Read the input. Report: "Loaded N rows with M columns."
Map input columns to the canonical schema. If column mapping is ambiguous (e.g., a column called "Size" could be combined dimensions), ask the user.
Step 2: Analyze issues
Scan all rows and produce a summary:
## Cleanup Preview
- **Casing**: X product names need Title Case
- **Categories**: Y rows have non-standard categories (mapping: "chairs" → Seating, etc.)
- **Dimensions**: Z rows have combined dimensions to split
- **Language**: W rows have Spanish-language fields to translate
- **Materials**: V rows have non-standard material terms
- **Prices**: U rows need currency formatting cleanup
- **Duplicates**: T potential duplicate rows found
- **Empty fields**: S rows missing dimensions, R rows missing price
Step 3: Confirm scope
Ask: "Apply all fixes, or select which ones?"
If the user wants to be selective, let them pick from the list. Otherwise, apply all.
Step 4: Apply fixes
Process every row through the active cleanup rules. Track every change made.
Step 5: Present results
Show a before/after diff for a sample of changed rows (up to 5 examples). Then show the full cleaned table.
Report:
## Cleanup Complete
- Rows processed: N
- Changes made: X
- Flagged for review: Y (marked with [?])
Step 6: Save
Ask: "Save where?"
Options:
- Overwrite original file (if local file input)
- Save as new file (default: append
-clean to filename)
- Write to Google Sheet (same sheet or new one)
- Just show the table — leave in conversation
Edge Cases
- Mixed-language schedule: Detect dominant language per column, normalize to one language
- Merged cells or irregular formatting: Flag and ask user how to handle
- Extra columns not in schema: Preserve them as-is at the end, don't delete
- Empty rows: Remove silently
- Header detection: Auto-detect header row (first row with text that matches known field names). If uncertain, ask.
