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 OrcaQubits/agentic-commerce-skills-plugins --skill sf-einsteingit clone --depth 1 https://github.com/OrcaQubits/agentic-commerce-skills-pluginsWrote 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/orcaqubits/agentic-commerce-skills-plugins/sf-einstein)<a href="https://agentmods.dev/skills/orcaqubits/agentic-commerce-skills-plugins/sf-einstein"><img src="https://agentmods.dev/badge/skills/orcaqubits/agentic-commerce-skills-plugins/sf-einstein/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/orcaqubits/agentic-commerce-skills-plugins/sf-einstein"><img src="https://agentmods.dev/badge/skills/orcaqubits/agentic-commerce-skills-plugins/sf-einstein.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00051 | $0.01305 |
| Opus 5 | $0.00026 | $0.00652 |
| Sonnet 5 | $0.00010 | $0.00261 |
| Haiku 4.5 | $0.00005 | $0.00130 |
Grade A, and why
sf-einstein 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 2d 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 — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Einstein AI for Salesforce Commerce
Before Writing Code
Fetch live docs before implementing Einstein AI features.
- Web-search: "Salesforce Commerce Cloud Einstein Recommendations API 2026"
- Web-search: "Salesforce Einstein Search dictionaries relevance tuning 2026"
- Web-search: "Salesforce Data Cloud B2C Commerce personalization 2026"
- Web-search: "Salesforce Commerce Cloud PWA Kit Einstein recommendations 2026"
- Web-fetch the Einstein Recommendations API reference for current configuration parameters
- Web-fetch Data Cloud connector setup and unified profile schema docs
Conceptual Architecture
Einstein Recommendations
Recommender Types:
| Type | Description | Typical Placement |
|---|---|---|
| Product-to-Product | Similar or complementary items (cross-sell) | PDP |
| Recently Viewed | User's browsing history | Homepage, category |
| Also Bought | Products frequently purchased together | Cart, PDP |
| Trending | Popular items across all users | Homepage, category |
| Top Sellers | Best-selling products by category/site | Homepage, category |
| Personalized | ML-driven per-user recommendations | Homepage (returning users) |
Recommender Configuration (Business Manager):
- Create recommenders with specific types and filtering rules
- Configure zone placement (homepage, PDP, cart, category page)
- Set filtering: exclude out-of-stock, price range limits, category restrictions
- Map recommendation zones to recommenders
Activity Collection:
Einstein activity tracking uses a collect.js library loaded on storefront pages. It automatically captures product views, add-to-cart, purchases, and search events. Configured via Business Manager > Einstein > Activity Tracking.
Warning: The
_etmcbeacon pattern is for Marketing Cloud Einstein, not Commerce Cloud Einstein. Do not confuse the two.
Recommendation Zones:
- Define placement areas on storefront pages
- Map zones to recommenders in Business Manager
- Customize rendering per zone (carousel, grid, list)
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.
- 2d ago First seen · 163 lines · 51 tokens per session scan A 659aa6ce27e0
sf-einstein is a skill published in the GitHub repository OrcaQubits/agentic-commerce-skills-plugins (39 stars, last pushed 2d ago), licensed MIT. It adds 51 tokens to every session and 1,305 once invoked, about $0.0003 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 2026-09-15.
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