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生産性・共同作業 · SKILL.md

sif-to-csv

sif-to-csv

Convert a SIF (Standard Interchange Format) file to a clean, readable CSV or Google Sheet.

Independent GitHub snapshot · Automated classification · Original documentation governs

スキルの説明

GitHub

name: sif-to-csv description: Convert a SIF (Standard Interchange Format) file to a clean, readable CSV or Google Sheet. allowed-tools:

  • Read
  • Write
  • Edit
  • Bash
  • Glob
  • Grep
  • AskUserQuestion
  • mcp__google__sheets_values_get
  • mcp__google__sheets_values_update
  • mcp__google__sheets_spreadsheet_get user-invocable: true

/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

CodeNameDescription
SFSpecification FileProject reference (header)
STSpecification TitleDisplay title (header)
PNProduct NumberSKU — starts a new record
PDProduct DescriptionProduct name
MCManufacturer Code3-5 char code
MNManufacturer NameFull name
QTQuantityInteger
NTQuantity (alt)Some systems use NT instead of QT
GCCategory / Group CodeProduct category
G0Vendor / Group IDVendor identifier

Pricing fields

CodeNameDescription
PLList PriceUnit list price
P1-P5Price TiersAlternate price tiers
I1Unit List Price (Cyncly)Cyncly Worksheet
I2Purchase 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

CodeNameDescription
TGSide Mark / TagRoom, area, or project tag
ON / ODOptionNumber + description pair
AN / ADAttributeNumber + description pair
WTWeightProduct weight
VOVolumeProduct volume
PRCProduct Category (Cyncly)Cyncly category

Link fields

CodeNameDescription
ProductURLProduct Page URLLink to product page
ImageURLProduct Image URLLink to product image
PVPicture PathLocal file path

Alternate manufacturer codes

SystemCodePurpose
StandardMC3-5 char manufacturer code
CynclyMGManufacturer code (replaces MC)
CETECManufacturer 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:

  1. Header fields: Extract SF and ST
  2. Records: Split on PN= boundaries
  3. For each record, extract all fields
  4. Detect manufacturer code variant: look for MC, MG, or EC — normalize to brand name
  5. Detect price variant: look for PL, P1, I1 — use whichever is present
  6. Detect quantity variant: look for QT or NT
  7. 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

Manufacturer code expansion

MCBrandMCBrand
HMIHerman MillerBLUBlu Dot
MKNMillerKnollDWRDesign Within Reach
KNLKnollFRHFritz Hansen
STCSteelcaseVITVitra
HAWHaworthARPArper
TEKTeknionFLSFlos
HUMHumanscaleLPOLouis Poulsen
KIMKimballARTArtemide
OFSOFSHBFHBF
GEIGeigerBRNBernhardt

For unknown codes, keep as-is and flag.

Options and attributes

  • Multiple ON/OD pairs → concatenate into "Options" column, separated by |
  • Multiple AN/AD pairs → 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):

  • Column A (Link) ← ProductURL
  • Column C (Product Name) ← PD
  • Column E (SKU) ← PN
  • Column F (Brand) ← MC expanded
  • Column J (Category) ← GC or PRC
  • Column K-O (Dims) ← parsed from AD where AN=DIM
  • Column P (Weight) ← WT
  • Column T (List Price) ← PL/P1/I1
  • Column U (Sale Price) ← calculated sell price
  • Column S (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-spec-bulk-cleanup — normalize the parsed data
  • /ffe-schedule — reformulate dealer data into a formatted schedule
  • /product-enrich — add categories and tags to imported products
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