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SKILL verified MIT Self-run

Product Enrich

skill-alpacalabsllc-skills-for-architects-product-enrich · by AlpacaLabsLLC

Auto-tag FF&E products with categories, colors, materials, and style tags using AI.

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Install

$ agentstack add skill-alpacalabsllc-skills-for-architects-product-enrich

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

Security review passed
0 installs to date
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1mo ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.

How agent discovery & health will work →
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About

/product-enrich — Product Enrichment

Takes a product list with basic info (name + brand) and fills in missing metadata — category, subcategory, primary color, material, and style tags — using AI. Works on CSV files, Google Sheets, or pasted data.

When to Use

  • After a bulk import where products are missing categories or tags
  • When a designer clips products quickly without filling in details
  • To standardize metadata across products from different sources
  • Before generating an FF&E schedule (enriched data makes better schedules)

Step 1: Accept Input

Accept product data in any format:

Google Sheet ID:

/product-enrich 1FMScYW9guezOWc_m4ClTQxxFIpS6TNRr373R-MJGzgE

CSV file:

/product-enrich ~/Documents/project/products.csv

Pasted data:

/product-enrich
Eames Lounge Chair, Herman Miller
Saarinen Tulip Table, Knoll
PH 5 Pendant, Louis Poulsen
Togo Sofa, Ligne Roset

Step 2: Analyze Each Product

For each product, infer the following fields:

Category

Map to the canonical vocabulary (22 terms) defined in ../../schema/product-schema.md.

Subcategory

More specific classification within the category:

  • Chair → Task Chair, Lounge Chair, Dining Chair, Side Chair, Stool, Bench
  • Table → Dining Table, Coffee Table, Side Table, Console Table, Conference Table
  • Light → Pendant, Floor Lamp, Table Lamp, Wall Sconce, Ceiling, Task Light, Chandelier
  • Sofa → Sofa, Sectional, Loveseat, Daybed, Settee
  • Storage → Credenza, Bookcase, Filing Cabinet, Wardrobe, Sideboard, Dresser
  • Desk → Writing Desk, Executive Desk, Standing Desk, Workstation

Primary Color

The dominant color of the product as typically sold:

  • Use standard color names: Black, White, Gray, Brown, Beige, Navy, Blue, Green, Red, Orange, Yellow, Pink, Purple, Natural, Walnut, Oak, Teak, Chrome, Brass, Copper, Multi

Material

Primary materials, comma-separated:

  • Wood (specify type if known: Walnut, Oak, Maple, Teak, Birch, Ash, Beech)
  • Metal (specify: Steel, Aluminum, Brass, Chrome, Iron, Copper)
  • Upholstery (specify: Leather, Fabric, Velvet, Bouclé, Mohair, Linen, Wool)
  • Other: Glass, Marble, Concrete, Ceramic, Plastic, Fiberglass, Rattan, Cane, Acrylic

Style Tags

2-4 descriptive tags from:

  • Period/movement: Mid-Century Modern, Art Deco, Bauhaus, Scandinavian, Japanese, Industrial, Contemporary, Traditional, Minimalist, Postmodern, Memphis
  • Character: Organic, Geometric, Sculptural, Modular, Stackable, Compact, Statement, Classic, Iconic
  • Context: Residential, Contract, Hospitality, Healthcare, Education, Outdoor

Image Analysis

If the product data includes an image URL (column AC in the master schema), use Claude vision to verify and refine the enrichment. The image may reveal:

  • Actual color (not just what the name suggests)
  • Material details not in the product name
  • Style characteristics

Step 3: Present Preview

Show a preview of the enrichment before applying:

## Product Enrichment Preview

| Product | Brand | Category | Subcategory | Color | Material | Style Tags |
|---------|-------|----------|-------------|-------|----------|------------|
| Eames Lounge Chair | Herman Miller | Chair | Lounge Chair | Walnut/Black | Molded plywood, Leather | Mid-Century Modern, Iconic, Residential |
| Saarinen Tulip Table | Knoll | Table | Dining Table | White | Marble, Aluminum | Mid-Century Modern, Sculptural, Organic |
| PH 5 Pendant | Louis Poulsen | Light | Pendant | White | Aluminum | Scandinavian, Classic, Iconic |
| Togo Sofa | Ligne Roset | Sofa | Sofa | Brown | Fabric | Contemporary, Organic, Sculptural |

4 products enriched. Apply? (y/n)

Flag any products where enrichment is uncertain:

⚠ "Custom Reception Desk" — unknown product, category set to Desk but verify

Step 4: Apply

To Google Sheet

Write enriched fields to the master 33-column schema:

  • Column A (Category) — enriched category
  • Column R (Materials) — enriched materials
  • Column S (Colors/Finishes) — enriched color
  • Column AD (Tags) — enriched style tags, appended to existing tags

Do NOT overwrite existing values unless the field is empty or the user explicitly asks to overwrite.

To CSV

Add new columns if they don't exist: Category, Subcategory, Primary Color, Material, Style Tags. Save as {original-name}-enriched.csv.

To conversation

Output the enriched table in markdown.

Step 5: Summary

✓ Enriched 4 products
  Categories: 4 assigned (0 already had values)
  Colors: 4 assigned
  Materials: 4 assigned
  Style tags: 14 total tags across 4 products
  Uncertain: 1 (flagged for review)

Pairs With

  • /product-spec-bulk-fetch — fetch specs first, then enrich the results
  • /product-data-cleanup — cleanup normalizes formatting, enrich adds metadata
  • /product-data-import — enriched products make better formatted schedules
  • /product-match — enriched tags help find better matches

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.