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/install cart-optimizer
Description
Optimize ecommerce cart top-up plans across promotions such as full-reduction, discounts, and coupons. Use when the user asks to 凑单、计算满减最优方案、比较多档优惠、推荐最低成本补单策...
README (SKILL.md)
Cart Optimizer - 凑单优化器
智能凑单助手,自动计算最优凑单方案。
功能特性
- 🎯 支持多种优惠类型:满减、折扣、优惠券
- 🧮 智能算法:最小额外支出、最大优惠利用率
- 🛒 多平台支持:淘宝、京东、拼多多
- 📊 实时计算:输入商品自动推荐凑单
- 💡 智能建议:推荐高性价比凑单品
使用方式
基础凑单
凑单 250 满 300 减 30
带购物车商品
购物车 250,凑满 300 减 30
多档优惠对比
对比凑单方案 250:满200减20 vs 满300减40
核心算法
- 背包问题变种
- 动态规划优化
- 贪心算法备选
Usage Guidance
This skill appears coherent and implements only local calculation logic for cart/coupon optimization. Before installing, consider: (1) Source trust — the package owner and homepage are unknown, so verify origin if you require provenance; (2) It runs as Node.js code/CLI on your agent-host — review or run it in a sandbox if you need to be extra cautious; (3) Functional limits — it uses simple enumeration with item limits/filters (max 20 candidates slice, maxItems defaults) so test with your real data to ensure it meets your needs; (4) It does not access accounts or network resources, but if you plan to extend it to fetch live product lists you should audit any added networking or credential use. Overall the package is consistent with its stated purpose.
Capability Analysis
Type: OpenClaw Skill
Name: cart-optimizer
Version: 1.0.0
The cart-optimizer skill is a legitimate utility for calculating e-commerce discounts and recommending item combinations to meet promotion thresholds. The code in index.js and cli.js implements standard algorithmic logic (knapsack-style optimization) and lacks any high-risk behaviors such as network requests, file system access, or data exfiltration.
Capability Assessment
Purpose & Capability
Name/description (凑单/优惠优化) matches the provided code and SKILL.md. The code implements threshold/discount calculations, rule comparison, candidate-item combination search, and advice formatting — all coherent with the stated purpose. No unrelated permissions or credentials are requested.
Instruction Scope
SKILL.md usage examples and commands map to the CLI and CartOptimizer API. The runtime instructions and code only operate on numeric inputs, rule objects, and candidate item lists; they do not read system files, environment variables, or send data externally.
Install Mechanism
There is no install spec; this is effectively an instruction+code bundle. The code is plain Node.js (cli.js, index.js) with no external network downloads or extract steps. No unusual install behavior detected.
Credentials
The skill declares no required environment variables, credentials, or config paths and the code does not reference process.env or other secrets. Requested access is proportionate to the task.
Persistence & Privilege
always is false and model invocation is allowed (platform default). The skill does not attempt to modify other skills, system settings, or persist credentials — no elevated persistence privileges are requested.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install cart-optimizer - After installation, invoke the skill by name or use
/cart-optimizer - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release
Metadata
Frequently Asked Questions
What is Cart Optimizer?
Optimize ecommerce cart top-up plans across promotions such as full-reduction, discounts, and coupons. Use when the user asks to 凑单、计算满减最优方案、比较多档优惠、推荐最低成本补单策... It is an AI Agent Skill for Claude Code / OpenClaw, with 239 downloads so far.
How do I install Cart Optimizer?
Run "/install cart-optimizer" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Cart Optimizer free?
Yes, Cart Optimizer is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Cart Optimizer support?
Cart Optimizer is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Cart Optimizer?
It is built and maintained by haidong (@harrylabsj); the current version is v1.0.0.
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