sif-to-csv
DocumentsConvert a SIF (Standard Interchange Format) file to a clean, readable CSV or Google Sheet.
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/sif-to-csv — SIF to CSV Converter
Converts a SIF (Standard Interchange Format) file from a dealer or procurement system into a clean, human-readable CSV or Google Sheet. Translates field codes to column headers, expands options and attributes, calculates pricing, and computes totals.
When to Use
- Received a SIF file from a dealer and need to review it as a spreadsheet
- Importing dealer pricing back into your FF&E schedule
- Comparing a dealer quote (SIF) against your original specification
- Loading dealer data into the master Google Sheet
SIF Format Reference
SIF is a text-based key-value format. Each line is CODE=VALUE, terminated by CRLF. Products are separated by records starting with PN=.
Core fields
| Code | Name | Description |
|---|---|---|
SF | Specification File | Project reference (header) |
ST | Specification Title | Display title (header) |
PN | Product Number | SKU — starts a new record |
PD | Product Description | Product name |
MC | Manufacturer Code | 3-5 char code |
MN | Manufacturer Name | Full name |
QT | Quantity | Integer |
NT | Quantity (alt) | Some systems use NT instead of QT |
GC | Category / Group Code | Product category |
G0 | Vendor / Group ID | Vendor identifier |
Pricing fields
| Code | Name | Description |
|---|---|---|
PL | List Price | Unit list price |
P1-P5 | Price Tiers | Alternate price tiers |
I1 | Unit List Price (Cyncly) | Cyncly Worksheet |
I2 | Purchase Price (Cyncly) | Cyncly Worksheet |
S- / S% | Sell Discount % | Sell = PL - (PL × S- × 0.01) |
P% / B% | Purchase/Buy % | Cost = PL × (P% × 0.01) |
Product detail fields
| Code | Name | Description |
|---|---|---|
TG | Side Mark / Tag | Room, area, or project tag |
ON / OD | Option | Number + description pair |
AN / AD | Attribute | Number + description pair |
WT | Weight | Product weight |
VO | Volume | Product volume |
PRC | Product Category (Cyncly) | Cyncly category |
Link fields
| Code | Name | Description |
|---|---|---|
ProductURL | Product Page URL | Link to product page |
ImageURL | Product Image URL | Link to product image |
PV | Picture Path | Local file path |
Alternate manufacturer codes
| System | Code | Purpose |
|---|---|---|
| Standard | MC | 3-5 char manufacturer code |
| Cyncly | MG | Manufacturer code (replaces MC) |
| CET | EC | Manufacturer code (alt) |
Step 1: Accept Input
SIF file:
/sif-to-csv ~/Documents/project/dealer-quote.sif
Pasted SIF content:
/sif-to-csv
SF=Project Alpha
ST=Dealer Quote - March 2026
PN=670
PD=Eames Lounge Chair and Ottoman
MC=HMI
QT=3
PL=5695.00
S-=42
TG=Executive Lounge
OD=Santos Palisander / Black MCL Leather
Step 2: Parse SIF
Read the file and parse each record:
- Header fields: Extract
SFandST - Records: Split on
PN=boundaries - For each record, extract all fields
- Detect manufacturer code variant: look for MC, MG, or EC — normalize to brand name
- Detect price variant: look for PL, P1, I1 — use whichever is present
- Detect quantity variant: look for QT or NT
- Calculate derived values:
- Sell Price:
PL - (PL × S- × 0.01)if discount present - Net Price:
PL × (P% × 0.01)if purchase % present - Extended List:
PL × QT - Extended Sell:
Sell Price × QT
- Sell Price:
Manufacturer code expansion
| MC | Brand | MC | Brand |
|---|---|---|---|
| HMI | Herman Miller | BLU | Blu Dot |
| MKN | MillerKnoll | DWR | Design Within Reach |
| KNL | Knoll | FRH | Fritz Hansen |
| STC | Steelcase | VIT | Vitra |
| HAW | Haworth | ARP | Arper |
| TEK | Teknion | FLS | Flos |
| HUM | Humanscale | LPO | Louis Poulsen |
| KIM | Kimball | ART | Artemide |
| OFS | OFS | HBF | HBF |
| GEI | Geiger | BRN | Bernhardt |
For unknown codes, keep as-is and flag.
Options and attributes
- Multiple
ON/ODpairs → concatenate into "Options" column, separated by| - Multiple
AN/ADpairs → concatenate into "Attributes" column, separated by| - If
AN=DIM, parse dimension string back into W/D/H if possible
Step 3: Present Preview
## SIF Import: Project Alpha — Dealer Quote March 2026
3 records parsed from dealer-quote.sif
| # | SKU | Product | Brand | Qty | List $ | Disc % | Sell $ | Ext Sell | Options | Tag |
|---|-----|---------|-------|-----|--------|--------|--------|----------|---------|-----|
| 1 | 670 | Eames Lounge Chair | Herman Miller | 3 | $5,695 | 42% | $3,303 | $9,909 | Palisander/Black | Exec Lounge |
| 2 | 164-500 | Saarinen Table 54" | Knoll | 1 | $4,750 | 38% | $2,945 | $2,945 | Arabescato/White | Dining |
| 3 | 462-CG | Gesture Chair | Steelcase | 8 | $1,189 | 45% | $654 | $5,232 | Cogent/Licorice | Open Office |
**Totals:**
- List: $22,147 · Sell: $18,086 · Savings: $4,061 (18.3%)
Step 4: Output
Ask the user for output format:
CSV file
Save as {input-name}-parsed.csv:
Item #, SKU, Product, Brand, Qty, List Price, Discount %, Sell Price, Ext List, Ext Sell, Category, Weight, Options, Attributes, Tag, Product URL, Image URL, MC Code
Google Sheet (master schema)
Write to the 33-column schema (defined in ../../schema/product-schema.md, CRUD patterns in ../../schema/sheet-conventions.md):
See ../../schema/sif-crosswalk.md for the full column-to-SIF mapping. Key fields:
- Column J (Link) ← ProductURL
- Column E (Product Name) ← PD
- Column I (SKU) ← PN
- Column B (Brand) ← MC expanded
- Column A (Category) ← GC or PRC
- Column L-P (Dims) ← parsed from AD where AN=DIM
- Column Q (Weight) ← WT
- Column U (List Price) ← PL/P1/I1
- Column V (Sale Price) ← calculated sell price
- Column T (Selected Finish) ← OD
- Column AC (Image URL) ← ImageURL
- Column AD (Tags) ← TG
- Column AE (Notes) ← "From SIF: {ST}. Discount: {S-}%. Qty: {QT} · Ext: ${ext_sell}"
- Column AF (Status) ← "quoted"
- Column AG (Source) ← "sif-to-csv"
Markdown
Output the table in conversation.
Step 5: Summary
✓ Parsed dealer-quote.sif
Specification: Project Alpha — Dealer Quote March 2026
3 records · 12 units
Total list: $22,147 · Total sell: $18,086 (18.3% avg discount)
Manufacturers: HMI (1), KNL (1), STC (1)
Saved to: ~/Documents/project/dealer-quote-parsed.csv
Pairs With
/csv-to-sif— round-trip: create SIF, send to dealer, parse their quote back/product-data-cleanup— normalize the parsed data/product-data-import— reformulate dealer data into a formatted schedule/product-enrich— add categories and tags to imported products