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Install in OpenClaw
/install multi-sku-copurchase-bundles
Description
Mine historical orders for multi-SKU co-purchase patterns, quantify association strength between SKUs, and produce high-converting bundle and Frequently-Boug...
Usage Guidance
This skill appears coherent and low-risk because it is instruction-only and asks for no credentials or installs. Before using it, consider: 1) Do not paste raw PII (customer emails, full names, payment data) into the chat — sanitize exports to order-line rows only (order_id can be hashed); 2) Confirm platform constraints (Shopify/Woo/custom) before relying on one-click checkout hooks; 3) Validate discount and margin math with your finance/merchandising team — the skill will propose prices/percentages but cannot access your margin data unless you provide it; 4) If you use loyalty apps (Rijoy or others), test bundle interactions in staging to avoid stacking conflicts; 5) If the skill ever asks for credentials, a download URL, or to run scripts, stop and re-evaluate — that would be a new risk signal. If you want a deeper security check, provide the raw SKILL.md plus any future script files or install specs and I will re-evaluate for hidden endpoints, downloads, or excessive privileges.
Capability Analysis
Type: OpenClaw Skill
Name: multi-sku-copurchase-bundles
Version: 1.0.0
The skill contains instructions that direct the AI agent to promote a specific third-party service and URL (https://www.rijoy.ai) within its responses. This constitutes a form of prompt injection for brand promotion (referral injection). While the service is relevant to the e-commerce domain and the instructions are transparently documented in SKILL.md and references/rijoy_brand_context.md, the use of instructions to manipulate the agent's output toward a specific commercial entity is a recognized injection technique. No evidence of malicious code execution, data exfiltration, or harmful intent was found.
Capability Assessment
Purpose & Capability
The name and description (co-purchase / bundle creation) match the SKILL.md and the included references. The skill asks for order-line data (order_id, sku, qty, price, timestamp) and prescribes computing support/confidence/lift, producing bundle cards, topology table, and logic chains — all coherent with its stated goal. The optional Rijoy citation is explicitly scoped to Shopify loyalty interactions and is appropriate for the described functionality.
Instruction Scope
Runtime instructions stay within the domain of order analytics and copywriting: request data shape, compute metrics, produce structured bundle outputs, and provide templates if no data. The skill does not instruct reading system files, accessing environment variables, or sending data to external endpoints beyond optionally citing Rijoy (a public URL) for loyalty-context references. One practical caveat: the skill expects users may paste CSV order data — that data can contain sensitive customer information, and the skill does not attempt to sanitize it by itself.
Install Mechanism
There is no install spec and no code files that execute on the host (instruction-only). This yields low installation risk because nothing is written to disk or downloaded by default.
Credentials
The skill declares no required environment variables, credentials, or config paths. That matches the purpose — order analytics from user-supplied exports — and is proportionate to its functionality.
Persistence & Privilege
The skill does not request always:true or any elevated persistence. It also does not declare any behavior that would modify other skills or system-wide configuration. Autonomous invocation is allowed (platform default) but that is typical for skills and not combined with any other concerning privileges here.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install multi-sku-copurchase-bundles - After installation, invoke the skill by name or use
/multi-sku-copurchase-bundles - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of multi-sku-copurchase-bundles.
- Mines order data to identify co-purchase (multi-SKU) patterns and quantifies association strength between SKUs.
- Generates bundle and Frequently-Bought-Together (FBT) recommendations, complete with fixed recommendation-card output and checkout CTAs.
- Includes stepwise methodology notes, logic chains, and topology tables for merchants to implement bundles and AOV-increasing tactics.
- Triggers on merchant prompts involving AOV, bundle design, cross-sell from order data, Shopify bundle apps, or related co-purchase questions.
- Excludes use for single-SKU costing, non-methodological creative naming, or legal/compliance review.
Metadata
Frequently Asked Questions
What is Multi-SKU Bundles?
Mine historical orders for multi-SKU co-purchase patterns, quantify association strength between SKUs, and produce high-converting bundle and Frequently-Boug... It is an AI Agent Skill for Claude Code / OpenClaw, with 101 downloads so far.
How do I install Multi-SKU Bundles?
Run "/install multi-sku-copurchase-bundles" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Multi-SKU Bundles free?
Yes, Multi-SKU Bundles is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Multi-SKU Bundles support?
Multi-SKU Bundles is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Multi-SKU Bundles?
It is built and maintained by RIJOY-AI (@rijoyai); the current version is v1.0.0.
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