Product Spec Bulk Fetch Agent Skill

/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:

• Inline list — URLs pasted directly in the message (one per line, or comma-separated)
• File path — A .txt, .csv, or .md file containing URLs (one per line)
• 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:

• Fetch the page using WebFetch with the prompt below
• Parse the response into the schema fields
• Flag issues — missing price, missing dimensions, non-product page
• 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.