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-data-importgit 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-data-import)<a href="https://agentmods.dev/skills/alpacalabsllc/skills-for-architects/product-data-import"><img src="https://agentmods.dev/badge/skills/alpacalabsllc/skills-for-architects/product-data-import/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-data-import"><img src="https://agentmods.dev/badge/skills/alpacalabsllc/skills-for-architects/product-data-import.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 | $0.00043 | $0.01789 |
| Opus 5 | $0.00022 | $0.00894 |
| Sonnet 5 | $0.00009 | $0.00358 |
| Haiku 4.5 | $0.00004 | $0.00179 |
Grade A, and why
product-data-import scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/as:product-data-import — Product Data Importer
Harness note: use
/as:<skill>on Claude Code and$<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 raw product data and formats it as a Markdown preview or as rows in the nearest project's product-library.csv, using the shared 33-column schema.
When to Use
- Designer has a list of products in notes or conversation and needs it formatted for a deliverable
- A rough product list needs to become a spec-ready schedule with item numbers, quantities, and extended pricing
- Products from multiple sources need to be consolidated into one formatted schedule
- An existing schedule needs to be reformatted to match the standard schema
Step 1: Accept Input
The designer provides product data in any format:
Raw notes:
3x Eames Lounge Chair, Herman Miller, walnut/black leather, $5,695 each
2x Nelson Platform Bench 48", Herman Miller, natural maple, $2,195
1x Noguchi Coffee Table, Herman Miller, walnut/glass, $2,095
Pendant light for above the table - something by Flos, budget $800-1200
Pasted CSV:
Product, Brand, Qty, Price
Eames Lounge Chair, Herman Miller, 3, $5695
Nelson Bench 48, Herman Miller, 2, $2195
A file path:
/as:product-data-import ./product-list.csv
Conversational:
"We need 8 task chairs — Steelcase Leap V2, black, about $1,200 each.
Also 4 monitor arms, any brand, under $300."
Accept whatever the designer gives. Don't ask for more structure — work with what you have.
Step 2: Parse and Enrich
For each product in the input:
- Extract known fields: product name, brand, quantity, price, dimensions, materials, finish, category
- Fill in from knowledge: If the product is well-known (Eames Lounge Chair, Steelcase Leap, etc.), fill in standard dimensions, materials, and weight from your training data. Mark these as "from reference" in notes.
- Assign categories: Map to the canonical vocabulary defined in
../../schema/product-schema.md - Calculate extended prices: Unit price × quantity
- Assign item numbers: Sequential within each category group (S-01, S-02 for Seating; T-01 for Tables; L-01 for Lighting, etc.)
- Flag unknowns: If a product is vague ("pendant light, Flos, $800-1200"), note it as "TBD — needs specification" and include budget range
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.
- 13d ago First seen · 149 lines · 43 tokens per session scan A 74360f7701f6
product-data-import is a skill published in the GitHub repository AlpacaLabsLLC/skills-for-architects (353 stars, last pushed 9d ago), licensed MIT. It adds 43 tokens to every session and 1,789 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.
Other skills, from other repositories
add-excel
Adds Excel Online (Business) connector to a Power Apps code app. Use when reading or writing Excel workbook data from OneDrive or SharePoint.
pm-feedback
A feedback-analysis aid that turns spreadsheet data, CSV files, pasted text, or review screenshots into organized product insights. It groups themes, identifies sentiment, examines trends and sources, calculates NPS, and extracts user types.
spreadsheet-analysis
Inspect, profile, clean, reconcile, analyze, visualize, and verify spreadsheet data while preserving formulas, formatting, types, and source files. Use when working with .xlsx, .xlsm, .xls, .ods, .csv, or .tsv files; answering questions from a workbook; auditing formulas or data quality; comparing sheets or versions…
video-timeline
Turn a final TTS audio track (with its timed transcript) into an editable story timeline (xlsx) for a human to fill with images, slides, and video clips. Audits the audio against timing best practices first, then maps each finding to a visual offset, and QA-scores the timeline objectively. Use when a finished…
univer-pro-integrate
Integrate current Univer Pro features into browser applications. Use for licensed Sheets, Docs, Slides, Bases, Boards, or PDFs; advanced Sheets presets; collaboration and edit history; Office import/export; printing; pivot tables; charts; sparklines; shapes; Pro workers; license ordering; or Pro Facade APIs.
univer-node-backend
Run Univer Sheets, Docs, Slides, Bases, Boards, or PDFs in Node.js without browser UI. Use for server-side or backend Univer, OSS Sheets or Docs Node presets, Pro product Facades and collaboration, JSON snapshot processing, formula or Base child-process workers, or automated unit manipulation with @univerjs/rpc-node.