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 finsilabs/awesome-ecommerce-skills --skill cross-sell-upsell-enginegit clone --depth 1 https://github.com/finsilabs/awesome-ecommerce-skillsWrote 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/finsilabs/awesome-ecommerce-skills/cross-sell-upsell-engine)<a href="https://agentmods.dev/skills/finsilabs/awesome-ecommerce-skills/cross-sell-upsell-engine"><img src="https://agentmods.dev/badge/skills/finsilabs/awesome-ecommerce-skills/cross-sell-upsell-engine/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/finsilabs/awesome-ecommerce-skills/cross-sell-upsell-engine"><img src="https://agentmods.dev/badge/skills/finsilabs/awesome-ecommerce-skills/cross-sell-upsell-engine.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 | $0.00032 | $0.02301 |
| Opus 5 | $0.00016 | $0.01151 |
| Sonnet 5 | $0.00006 | $0.00460 |
| Haiku 4.5 | $0.00003 | $0.00230 |
Grade A, and why
cross-sell-upsell-engine 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 8d 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 — 191 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cross-Sell and Upsell Engine
Overview
Cross-sells and upsells generate 10–30% incremental revenue with minimal customer acquisition cost. Every major e-commerce platform has apps that handle the recommendation logic without custom code. The key decisions are: which placement to start with (PDP, cart, or post-purchase), what recommendation logic to use (manual bundles vs. algorithm-based), and how to avoid checkout friction. Start with one placement and measure before expanding.
When to Use This Skill
- When average order value (AOV) is below industry benchmarks and you want to grow it without paid traffic
- When launching a new recommendation widget on PDP, cart, or checkout pages
- When replacing a generic "You may also like" carousel with affinity-based personalization
- When building a bundle builder or "complete the look" feature
- When wanting to A/B test recommendation placements
Core Instructions
Step 1: Choose the right tool for your platform
| Platform | Recommended Tool | Why |
|---|---|---|
| Shopify | Rebuy (most powerful) or Frequently Bought Together | Rebuy uses AI-based recommendations with multiple placement types; FBT is simpler and cheaper for basic "people also bought" |
| Shopify (Plus) | Rebuy + Shopify Functions | Shopify Functions allows custom cart transforms for bundle discounts |
| WooCommerce | WooCommerce built-in cross-sell/upsell + YITH WooCommerce Frequently Bought Together | WooCommerce has native upsell and cross-sell fields on every product; YITH adds the "FBT" widget |
| BigCommerce | Also Bought or Boost Commerce (App Marketplace) | Both integrate natively with BigCommerce product catalog |
| Custom / Headless | Rebuy API or Recombee | Both offer recommendation APIs; Rebuy integrates directly with Shopify/BigCommerce backends |
Step 2: Decide on placement — start with one
| Placement | Expected AOV Lift | Conversion Risk | Start Here? |
|---|---|---|---|
| Product page (below Add to Cart) | Moderate | Low | Yes — best starting point |
| Cart page (sidebar or bottom) | High | Low | Yes — high intent, low friction |
| Post-purchase page | High | None (order already placed) | Yes — zero risk to conversion |
| Checkout page | High | Medium-High | No — test this last; can hurt CVR |
What ships with it
7 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.
- evals/affinity-score-computation-pipeline/criteria.json 2.4 KB
- evals/affinity-score-computation-pipeline/task.md 1.6 KB
- evals/layered-recommendation-api-with-placemen/criteria.json 3.0 KB
- evals/layered-recommendation-api-with-placemen/task.md 1.7 KB
- evals/react-widget-analytics-tracking-and-a-b-/criteria.json 3.0 KB
- evals/react-widget-analytics-tracking-and-a-b-/task.md 1.7 KB
- tile.json 321 B
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.
- 8d ago First seen · 191 lines · 32 tokens per session scan A e4a74087b476
cross-sell-upsell-engine is a skill published in the GitHub repository finsilabs/awesome-ecommerce-skills (52 stars, last pushed 6mo ago), licensed MIT. It adds 32 tokens to every session and 2,301 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 2026-09-03.
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