Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/AlpacaLabsLLC/skills-for-architectsnpx agentmods add skills/alpacalabsllc/skills-for-architects/product-data-importWrote 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 | $0.00041 | $0.01560 |
| Opus 5.5 | $0.00016 | $0.00624 |
| Sonnet 5.5 | $0.00008 | $0.00312 |
| Haiku 4.5 | $0.00004 | $0.00156 |
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 1mo 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 — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/as:product-data-import — Product data and accepted intake
Read the host contract, declaration (skill:product-data-import) and selected shared profiles. Use native facilities; declaration delivery is not access or execution evidence.
Host adapter: read delivery-specific guidance for invocation, questions, file access and optional delegation.
Choose the actual outcome
Normalize supplied notes, CSV, pasted lists, observations or selected workbook data into a reviewable schedule. This skill owns accepted ffe/jobs/<job-id>/input-manifest.json only when a document-job intake is requested. An inline preview needs no project or write. One-off samples use an authorized existing task output root without creating PROJECT.md or registering a studio. Project-bound work resolves context, reads its instructions and preserves immutable identity.
Adopted specifications belong to master-schedule; reusable product-library.csv changes belong to product-library. Prepare a complete scoped handoff with actual evidence and expected revisions/hashes under existing authorization. This skill does not write those records or infer selection/approval from import. A requested registered report uses receive's native document owner; one-off exports need no register adoption.
Parse, validate and present
Accept the supplied format without requiring the user to restructure it. Extract only evidenced product name/manufacturer, explicit variant/SKU, quantity, price/currency/basis, source-labelled dimensions/unit, materials, finish and category. Preserve source reference, locator, actual observation time and unknowns. Available configurations are not selected specifications. Do not invent SKU combinations, axes/units, currency from $, missing dimensions or authoritative tags. Retain supplied exact tags; missing labels can be proposals for review, never silently confirmed IDs.
What ships with it
2 files 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.
- 1mo ago Changed 0937ad22534d
- 1mo ago Changed · -86 lines · -2 tokens per session 4a707a170ab6
- 1mo 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 (395 stars, last pushed 7d ago), licensed MIT. It adds 41 tokens to every session and 1,560 once invoked, about $0.0002 per session on Opus 5.5. 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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