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Product spec bulk fetch

Skill AlpacaLabsLLC/skills-for-architects/skills/product-spec-bulk-fetch

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Install
npx -y skills add AlpacaLabsLLC/skills-for-architects --skill product-spec-bulk-fetch

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

What its author says it does

Copied from the file, not written here

Extract structured FF&E specs from a list of product URLs into a schedule. Use to pull or bulk-import product-page data; not for PDF catalogs.

SKILL.md

5.7 KB, as published. Nobody here has run it

/as:product-spec-bulk-fetch — Bulk Product Spec Fetcher

Extract structured FF&E data from a list of product page URLs. Outputs a standardized schedule ready for design specs, procurement, or import into Norma.

Input

The user provides product URLs in one of these ways:

  1. Inline list — URLs pasted directly in the message (one per line, or comma-separated)
  2. File path — A .txt, .csv, or .md file containing URLs (one per line)
  3. Project library — URLs from the named Link field in product-library.csv

If the input format is unclear, ask.

Output Schema

Persistent results use the nearest project-root product-library.csv. Read ../../schema/product-schema.md for the exact 33-column contract and ../../schema/csv-conventions.md for safe local-file behavior.

Skill-specific column values:

  • AF (Status): saved
  • AG (Source): bulk-fetch
  • AD (Tags): Blank (set by user later)
  • AE (Notes): Blank
  • T (Selected Color/Finish): Blank (unknown from URL)

Extraction Process

For each URL:

  1. Fetch the page using WebFetch with the prompt below
  2. Parse the response into the schema fields
  3. Flag issues — missing price, missing dimensions, non-product page
  4. Continue to next URL — never stop the batch on a single failure

WebFetch Extraction Prompt

Use this prompt (or close variant) for each URL:

Extract structured product/furniture specification data from this page. Return a JSON object with these exact fields:

- product_name: Full product name (Title Case)
- description: Short description or tagline (1-2 sentences), or null
- sku: Product ID, SKU, model number, or catalog number, or null
- brand: Manufacturer name (Title Case)
- designer: Designer or design studio name if attributed, or null
- vendor: The retailer/website selling the product (may differ from brand), or null
- collection: Product line or collection name, or null
- category: One of: Chair, Table, Sofa, Bed, Light, Storage, Desk, Shelving, Rug, Mirror, Accessory, Tabletop, Kitchen, Bath, Window, Door, Outdoor Furniture, Textile, Acoustic, Planter, Partition, Other
- width: Numeric width value only (no units), or null
- depth: Numeric depth value only (no units), or null
- height: Numeric height value only (no units), or null
- seat_height: Numeric seat height for seating products, or null
- unit: "in", "cm", or "mm" — whichever the page uses
- weight: Weight as stated with unit (e.g. "45 lbs"), or null
- materials: Comma-separated list of primary materials
- colors_finishes: Comma-separated list of ALL available colors or finish options
- list_price: Numeric price (no currency symbol, no commas), or null
- sale_price: Discounted/sale price if shown, or null
- currency: "USD", "EUR", "GBP", etc.
- lead_time: Delivery estimate as stated, or null
- warranty: Warranty info as stated, or null
- certifications: Comma-separated certifications (GREENGUARD, FSC, BIFMA, etc.), or null
- com_col: "COM", "COL", "COM/COL" if mentioned, or null
- indoor_outdoor: "Indoor", "Outdoor", or "Indoor/Outdoor" if specified, or null
- image_url: URL of the primary product image (largest/hero image)

If this is NOT a product page, return: {"error": "not_a_product_page"}
If dimensions use a combined format like "32 x 24 x 30 in", split them into W x D x H.
If price says "Contact for pricing" or similar, set price to null.
Return ONLY the JSON object, no other text.

Workflow

Step 1: Parse input

Extract all URLs from the user's input. Report count: "Found N product URLs."

Step 2: Fetch in parallel

Process URLs using WebFetch. Use parallel tool calls — fetch up to 5 URLs simultaneously to maximize speed. Report progress after each batch.

Step 3: Compile results

Build a results table. Group into:

  • Successful — all key fields extracted
  • Partial — some fields missing (still include in output)
  • Failed — non-product page or fetch error

Step 4: Present results

Show a summary table in markdown with all successful + partial results. Flag any issues:

  • "Price not found" for trade/dealer sites
  • "Dimensions not found" if missing
  • "Failed to fetch" for errors

Step 5: Preview persistence

The results table is the Markdown output. If the user asks to save, preview the selected row count, incomplete fields, and target product-library.csv, then use the single confirmation gate.

Step 6: Save

After approval, serialize all complete canonical rows as one JSON array and invoke python3 "${CLAUDE_PLUGIN_ROOT}/skills/master-schedule/scripts/csv-library.py" append product --project <project-root> --row-json <batch.json> exactly once. Set Clipped At to the current timestamp and Source to bulk-fetch. The helper validates the complete batch and library before one atomic replacement; never loop per row.

Do not write a secondary structured export. A Markdown report may be retained separately.

Edge Cases

  • Redirects or blocked pages: Note the URL as failed, move on
  • Multiple products on one page: Extract only the primary/featured product
  • Non-English pages: Extract data as-is, note the language. The cleanup skill handles translation.
  • Vendor sites requiring login: Will likely fail — note as "Login required" and move on
  • Duplicate URLs in input: Skip duplicates, note them

Error Reporting

After the batch completes, always report:

Fetched: X/Y successful, Z partial, W failed

List any failed URLs with the reason.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.