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Shipping Optimizer
by
LeroyCreates
· GitHub ↗
· v1.0.0
· MIT-0
167
Downloads
0
Stars
0
Active Installs
1
Versions
Install in OpenClaw
/install shipping-optimizer
Description
Compare shipping strategies across carriers, zones, and fulfillment models to find the lowest-cost configuration that still meets customer delivery expectati...
Usage Guidance
This is an instruction-only tool that asks you to paste your SKU dimensions, monthly volumes, origins, and (optionally) your current shipping costs so it can estimate per-unit landed costs across carriers and fulfillment options. It does not fetch carrier quotes or access your carrier accounts — do not share carrier login credentials or private dashboards. Because outputs are estimates based on published rate rules and the numbers you provide, validate any recommended changes with real carrier quotes and your contract terms before switching providers. If you are uncomfortable sharing detailed volume or cost data, consider anonymizing or aggregating inputs (e.g., ranges or percentage splits) before using the skill.
Capability Analysis
Type: OpenClaw Skill
Name: shipping-optimizer
Version: 1.0.0
The skill bundle consists solely of metadata and a markdown instruction file (SKILL.md) for a shipping cost analysis tool. It contains no executable code, network requests, or suspicious instructions, and its data requirements (SKU dimensions, warehouse locations) are strictly aligned with its stated purpose of logistics optimization.
Capability Assessment
Purpose & Capability
The name/description (shipping cost and fulfillment model comparisons) matches the SKILL.md content. There are no unexpected requirements (no cloud credentials, no carrier API tokens) and the skill explicitly states it relies on user-provided data rather than pulling account information.
Instruction Scope
Instructions are limited to collecting user-provided catalog, origin, and delivery-window inputs and producing a comparative report. Note: the skill asks for commercially sensitive data (volumes, negotiated costs) which is expected for the task — the user should avoid sharing carrier account credentials or private dashboards because the skill does not declare any need for them.
Install Mechanism
No install spec and no code files — instruction-only. This minimizes risk because nothing is written to disk or fetched during install.
Credentials
No environment variables, credentials, or config paths are requested. The absence of declared credentials is consistent with the SKILL.md statement that it cannot access carrier dashboards and uses user-supplied numbers.
Persistence & Privilege
always is false and the skill is user-invocable; it does not request permanent/system-level presence or any modifications to other skills or agent config. Autonomous model invocation is allowed by default but not combined with other privilege concerns here.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install shipping-optimizer - After installation, invoke the skill by name or use
/shipping-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 Shipping Optimizer?
Compare shipping strategies across carriers, zones, and fulfillment models to find the lowest-cost configuration that still meets customer delivery expectati... It is an AI Agent Skill for Claude Code / OpenClaw, with 167 downloads so far.
How do I install Shipping Optimizer?
Run "/install shipping-optimizer" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Shipping Optimizer free?
Yes, Shipping Optimizer is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Shipping Optimizer support?
Shipping Optimizer is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Shipping Optimizer?
It is built and maintained by LeroyCreates (@leooooooow); the current version is v1.0.0.
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