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Install in OpenClaw
/install shopping-advisor
Description
Shopping decision skill. Compares similar products, explains price gaps, judges whether something is worth buying, suggests better directions, flags common p...
Usage Guidance
This skill appears coherent and low-risk: it only processes user-provided product data locally and outputs recommendations. Before installing or running, consider: (1) run the included scripts on sample inputs in a sandbox to verify behavior, (2) avoid piping sensitive files into the scripts (they only expect JSON product data), and (3) re-review any future updates for network calls or newly required environment variables — those would be the main signals of increased risk.
Capability Analysis
Type: OpenClaw Skill
Name: shopping-advisor
Version: 1.0.0
The shopping-advisor skill bundle is a well-structured decision-support tool designed to help users compare products and prices. The included Python scripts (normalize.py, decide.py, analyze.py, and common.py) handle data processing locally via standard input/output, utilizing basic JSON parsing and regex-based token matching without any network requests, file system writes, or shell command execution. The SKILL.md instructions for the AI agent are strictly aligned with the stated purpose and include explicit safety boundaries that prohibit the agent from performing unauthorized actions like making purchases or payments.
Capability Assessment
Purpose & Capability
Name/description (shopping decision helper) match the included scripts and schema: normalize -> decide -> analyze. Required capabilities (none) are proportionate to its purpose. The repository contains local Python scripts to implement the stated functionality and no unrelated cloud or admin access is requested.
Instruction Scope
SKILL.md defines a bounded workflow (collect minimal info, normalize candidates, produce a decision report). The runtime scripts only read JSON from stdin, parse/normalize product info, compute comparisons, and write JSON/text to stdout. They do not read arbitrary system files, do not open network sockets, and do not instruct the agent to access secrets or external endpoints.
Install Mechanism
No install spec is present (instruction-only installation), which is the lowest-risk pattern. The repo does include runnable Python scripts, but they are executed locally and do not pull remote code or run installers. No downloads, package installs, or extraction from untrusted URLs are used.
Credentials
The skill requests no environment variables, no credentials, and no privileged config paths. All inputs come from structured user-provided JSON (titles, URLs, price hints). There are no secrets or broad environment accesses declared or used in the code.
Persistence & Privilege
The skill does not request always:true and does not modify system or other skill configs. It runs on-demand using stdin/stdout; autonomous model invocation is allowed by platform default but the skill itself does not create persistent background services or store credentials.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install shopping-advisor - After installation, invoke the skill by name or use
/shopping-advisor - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release: shopping-advisor 1.0.0
- Provides structured shopping advice: product comparison, price gap explanation, buy-worth judgment, better alternatives, and direct recommendations.
- Supports inputs including product links, titles, screenshots, and descriptions.
- Uses a defined decision process to optimize purchasing decisions, not just information sharing.
- Always ends with a clear, actionable purchase conclusion tailored to user preferences.
- Built-in minimal script flow: input normalization, decision structuring, and user-facing analysis.
Metadata
Frequently Asked Questions
What is Shopping Advisor?
Shopping decision skill. Compares similar products, explains price gaps, judges whether something is worth buying, suggests better directions, flags common p... It is an AI Agent Skill for Claude Code / OpenClaw, with 141 downloads so far.
How do I install Shopping Advisor?
Run "/install shopping-advisor" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Shopping Advisor free?
Yes, Shopping Advisor is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Shopping Advisor support?
Shopping Advisor is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Shopping Advisor?
It is built and maintained by haidong (@harrylabsj); the current version is v1.0.0.
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