wardrobe-receipt-cataloger

name

wardrobe-receipt-cataloger

description

Scan Gmail for clothing purchase receipts, extract item details (brand, product, color, size, price, purchase date), download product images, then catalog each item in the Logseq wiki: update Wardrobe.md in the correct section, create/update brand pages, and link to the product page, Internet Archive snapshot, and original receipt email. TRIGGER when the user wants to sync recent clothing purchases to their wiki, catalog new wardrobe items from email receipts, or audit what they've bought.

wardrobe-receipt-cataloger

What This Skill Does

Given a date range (defaulting to the last 90 days), this skill:

1. Searches Gmail for clothing purchase receipts
2. Parses each receipt to extract: brand, product name, color/colorway, size, price, purchase date, product URL
3. Downloads product images to logseq/assets/ with structured filenames
4. Fetches an Internet Archive (Wayback Machine) snapshot URL for each product
5. Updates logseq/pages/Wardrobe.md in the correct section
6. Creates or updates brand pages in logseq/pages/
7. Links each entry to the product page, Wayback Machine snapshot, purchase date journal entry, and original Gmail thread

---

Phase 0 — Scope

Load Gmail tools first:

ToolSearch: select:mcp__claude_ai_Gmail__search_threads,mcp__claude_ai_Gmail__get_thread,mcp__claude_ai_Gmail__list_labels

Then ask:

AskUserQuestion:
  header: "Date range"
  question: "Which time window should I scan for clothing receipts?"
  options:
    - "Last 30 days (Recommended)"
    - "Last 90 days"
    - "Last 6 months"
    - "Custom range — I'll specify via Other"

AskUserQuestion:
  header: "Filter"
  question: "Should I catalog all clothing brands or focus on specific ones?"
  options:
    - "All clothing brands found in receipts (Recommended)"
    - "Only brands not yet in Wardrobe.md"
    - "Specific brands — I'll name them via Other"

---

Phase 1 — Gmail Receipt Search

1a — Run parallel searches

Use mcp__claude_ai_Gmail__search_threads with these queries in parallel (one call per query):

"order confirmation" "clothing" newer_than:{days}d
"receipt" ("shirt" OR "pants" OR "jacket" OR "shorts" OR "shoes" OR "blazer" OR "hoodie" OR "trousers") newer_than:{days}d
"your order" ("Patagonia" OR "REI" OR "Roark" OR "Bonobos" OR "Dandy Del Mar" OR "lululemon" OR "prAna" OR "1620 Workwear" OR "Engelbert Strauss" OR "Taylor Stitch" OR "Faherty" OR "Suitsupply" OR "J.Crew" OR "Banana Republic" OR "Express" OR "Buck Mason") newer_than:{days}d
"shipping confirmation" ("apparel" OR "clothing" OR "wear" OR "shirt" OR "jacket") newer_than:{days}d

Replace {days} with: 30 → 30, 90 → 90, 6 months → 180.

1b — Deduplicate threads

Collect all thread IDs, deduplicate. Fetch each unique thread with mcp__claude_ai_Gmail__get_thread.

1c — Classify

For each thread, determine:

• Is this a clothing purchase receipt? (vs. tracking update, marketing, non-clothing)
• What retailer/brand is it from?
• Skip: tracking-only emails, marketing/promotional, returns/refunds unless re-purchased

---

Phase 2 — Receipt Parsing

For each confirmed clothing receipt thread, extract:

Field	Notes
brand	Retailer brand name (e.g., "Patagonia", "Roark")
product_name	Full product name as listed (e.g., "M's Houdini Jacket")
color	Color/colorway name (e.g., "Buckhorn Green")
size	Size as ordered (e.g., "M", "31W × 32L", "S")
price	Item price (USD)
purchase_date	Date of purchase (YYYY-MM-DD)
product_url	Direct product URL from receipt (if present)
order_number	Order number/ID
gmail_thread_id	Thread ID for back-linking to email

If multiple items in one order: extract each item separately.

Size normalization:

• Tops: S / M / L / XL or brand-specific (Slim S, etc.) — preserve exact size code as ordered
• Pants: W × L format (e.g., 31×32)
• Shoes: US size

---

Phase 3 — Image Acquisition

For each item:

3a — Try to get the product image

1. If product_url exists:
   • Load: ToolSearch: select:mcp__read-website-fast__read_website
   • Fetch the product page: mcp__read-website-fast__read_website(url=product_url)
   • Extract the main product image URL from the page (look for og:image or primary product photo)
2. If no image found from product page, search: mcp__brave-search__brave_web_search for {brand} {product_name} {color} site:brand.com to find a direct image URL

3b — Download the image

Load: ToolSearch: select:mcp__website-downloader__download_page

• Save to: logseq/assets/{brand-slug}-{product-slug}.jpg
• Filename rules (Android compatibility — NO : * ? " < > | \):
  • Brand slug: lowercase, spaces → hyphens (e.g., dandy-del-mar)
  • Product slug: lowercase, keep color, remove special chars (e.g., houdini-jacket-buckhorn-green)
  • Full example: patagonia-houdini-jacket-buckhorn-green.jpg
• If image download fails, note "image pending" and continue — don't block cataloging

3c — Fetch Wayback Machine snapshot

For each product_url:

• Archive URL pattern: https://web.archive.org/web/*/{product_url}
  • This retrieves the most recent available snapshot
• Also construct a save-request URL: https://web.archive.org/save/{product_url}
  • Note this in the catalog entry so the user can trigger a fresh save if desired

---

Phase 4 — Section Classification

Map each item to the correct Wardrobe.md section:

Item type	Section → Subsection
Blazer, sport coat, suit jacket	Tops → Dress / Smart Casual
Dress shirt, linen shirt	Tops → Dress / Smart Casual
Button-down, woven shirt, OCBD	Tops → Button-Down & Woven Shirts
T-shirt, polo, athletic shirt	Tops → T-Shirts & Athletic Shirts
Hoodie, fleece, long-sleeve performance	Tops → Hoodies & Long-Sleeve Performance
Sun sleeves, buff, neck gaiter	Tops → Sun Protection & Neckwear
Dress trousers, chinos, linen trousers	Bottoms → Pants
Jeans, casual pants, cargo pants	Bottoms → Pants
Shorts	Bottoms → Shorts
Jacket, vest, rain shell, wind shell	Outerwear & Layering
Tank top, undershirt	Dress Accessories
Hat, cap, beanie, sunglasses, belt	Headwear & Accessories
Shoes, boots, sneakers, sandals	Footwear
Work pants, work shirt, tool vest	Work & Trade Clothing
Jersey, fan apparel	Sports & Fan Apparel

---

Phase 5 — Wiki Updates

5a — Update Wardrobe.md

Read logseq/pages/Wardrobe.md. For each new item, append to the correct section:

- [[{Brand}]] {Product Name} — {Color}, {Size} ({Month} {Year}) · [product]({product_url}) · [archive](https://web.archive.org/web/*/{product_url}) · [receipt](https://mail.google.com/mail/u/0/#inbox/{gmail_thread_id})

Format rules:

• Check for duplicates before appending: if an identical entry (same brand + product + color + size + year/month) already exists, skip
• Sort within subsections: most recent purchase last (chronological)
• If the subsection doesn't exist yet, create it under the correct parent section

Example output:

- [[Patagonia]] M's Houdini Jacket — Buckhorn Green, M (Aug 2024) · [product](https://www.patagonia.com/product/mens-houdini-jacket/24142.html) · [archive](https://web.archive.org/web/*/https://www.patagonia.com/product/mens-houdini-jacket/24142.html) · [receipt](https://mail.google.com/mail/u/0/#inbox/18c3b2a1d0e9f7g6)

5b — Update or create brand page

Check if logseq/pages/{Brand}.md exists.

If it doesn't exist, create it with this template:

tags:: [[Clothing]], [[Brand]], [[Shopping]]

- **{Brand}** — {one-line brand description from website or receipt context}
- ## Purchases
	- ### {Year}
		- **{Product Name}** — {Color}, {Size} · [product]({product_url}) · [archive](https://web.archive.org/web/*/{product_url})
			- ![{Brand} {Product Name}](../assets/{image-filename}.jpg)
			- Purchased {Month} {Year} · ${price} · [receipt](https://mail.google.com/mail/u/0/#inbox/{gmail_thread_id})
- ## Related
	- [[Wardrobe]]

If it exists, append the new item under ## Purchases in the correct year subsection. Create the year subsection if it doesn't exist.

5c — Update Key Brands list in Wardrobe.md

If the brand is new (not already in the ## Key Brands section), append:

- [[{Brand}]] — {short descriptor}

And add it to the ## Related section at the bottom.

---

Phase 6 — Summary Report

After all items are processed, output a summary table:

## Receipt Cataloging Summary

| Brand | Product | Color | Size | Date | Wardrobe Section | Image | Status |
|---|---|---|---|---|---|---|---|
| Patagonia | M's Houdini Jacket | Buckhorn Green | M | Aug 2024 | Outerwear | ✅ | Added |
| … | … | … | … | … | … | … | … |

### Skipped
- {Thread subject} — reason (e.g., "non-clothing", "already cataloged", "return/refund")

### Images Pending
- {Brand} {Product} — image URL not found; manually add to logseq/assets/{filename}.jpg

Then ask:

AskUserQuestion:
  header: "Next step"
  question: "Items cataloged. What would you like to do next?"
  options:
    - "Commit the changes to git"
    - "Review the Wardrobe.md changes first"
    - "Run again for a longer date range"
    - "Done for now"

---

Execution — Reusable Scripts

Rather than making individual file edits (which require per-call approval), this skill uses two reusable scripts that only need one approval to run:

Files

File	Purpose
~/.claude/skills/wardrobe-receipt-cataloger/catalog_wardrobe.py	Main script: downloads images, updates Wardrobe.md, creates/updates brand pages
~/.claude/skills/wardrobe-receipt-cataloger/receipts.json	Data: extracted receipt data in structured JSON format

Workflow

1. Extract receipt data from Gmail threads into receipts.json
2. Run catalog_wardrobe.py once — single script approval covers all file writes
3. Verify with --dry-run first, then execute for real

# Dry run (preview only)
python3 ~/.claude/skills/wardrobe-receipt-cataloger/catalog_wardrobe.py \
  --wiki-root /path/to/personal-wiki \
  --dry-run

# Execute
python3 ~/.claude/skills/wardrobe-receipt-cataloger/catalog_wardrobe.py \
  --wiki-root /path/to/personal-wiki

# Skip already-processed receipts on re-runs
python3 ~/.claude/skills/wardrobe-receipt-cataloger/catalog_wardrobe.py \
  --wiki-root /path/to/personal-wiki \
  --skip-processed

Adding new receipts

When new receipts are found, add entries to receipts.json in this format:

{
  "thread_id": "19e75dd...",
  "brand": "Brand Name",
  "order_number": "12345",
  "order_date": "2026-05-29",
  "items": [
    {
      "product_name": "Product Name",
      "color": "Color Name",
      "size": "M",
      "price": 89.00,
      "wardrobe_section": "Tops",
      "wardrobe_subsection": "Button-Down & Woven Shirts",
      "existing_search": null,
      "image_url": "https://cdn.example.com/image.jpg",
      "image_filename": "brand-product-color.jpg",
      "product_url": "https://brand.com/product"
    }
  ]
}

Set existing_search to the exact text of an existing Wardrobe.md line to add receipt links to it instead of creating a new entry.

---

Notes & Constraints

Android filename safety

Never use : * ? " < > | \ in any filename written to logseq/assets/. Always validate before writing.

Duplicate detection

Before adding any entry to Wardrobe.md or a brand page, check if an entry with the same (brand + product slug + color + size + year) already exists. If so, skip silently.

Wayback Machine links

Use the * wildcard form (/web/*/url) which redirects to the most recent snapshot — more robust than a dated snapshot URL that may not exist yet. If the product URL is very new, the archive may not have a snapshot; note this in the summary rather than failing.

Gmail thread links

Gmail deep-link format: https://mail.google.com/mail/u/0/#inbox/{thread_id} Use the thread ID from mcp__claude_ai_Gmail__get_thread response.

Purchase date → journal link

Logseq journal format: logseq/journals/YYYY_MM_DD.md If the journal entry for the purchase date exists, you may reference it as:

[[{Month} {Day}th, {Year}]]

using Logseq's journal page link syntax.

Rate limiting

If fetching many product pages, add brief pauses between requests. Prefer reading receipt email HTML for images over scraping retailer websites when possible.