Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add AlpacaLabsLLC/skills-for-architects --skill product-enrichgit clone --depth 1 https://github.com/AlpacaLabsLLC/skills-for-architectsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/alpacalabsllc/skills-for-architects/product-enrich)<a href="https://agentmods.dev/skills/alpacalabsllc/skills-for-architects/product-enrich"><img src="https://agentmods.dev/badge/skills/alpacalabsllc/skills-for-architects/product-enrich/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/alpacalabsllc/skills-for-architects/product-enrich"><img src="https://agentmods.dev/badge/skills/alpacalabsllc/skills-for-architects/product-enrich.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00039 | $0.01371 |
| Opus 5 | $0.00019 | $0.00685 |
| Sonnet 5 | $0.00008 | $0.00274 |
| Haiku 4.5 | $0.00004 | $0.00137 |
Grade A, and why
product-enrich scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/as:product-enrich — Product Enrichment
Harness note: use
/as:<skill>on Claude Code and$<skill>on Codex. Resolve<skill-root>as the directory containing this loadedSKILL.mdand<plugin-root>as the plugin root that containsskills/, and use equivalent native tools when host tool names differ.
Takes product rows from the nearest project's product-library.csv or pasted data and proposes missing category, color, material, and style metadata.
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:
CSV file:
/as:product-enrich ./products.csv
Pasted data:
/as: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
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 134 lines · 39 tokens per session scan A 85b45e80c949
product-enrich is a skill published in the GitHub repository AlpacaLabsLLC/skills-for-architects (353 stars, last pushed 8d ago), licensed MIT. It adds 39 tokens to every session and 1,371 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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