M

macys-research

VERIFIED

by community

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144,126,000installs
Updated Aug 2026

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Description

Looks up a Macy's product's full detail and customer reviews by its numeric productId, and pulls Macy's own search-box (typeahead) suggestions, using the Crawlora API, returning clean JSON. Use when the user has (or can get) a Macy's product page ?ID= value and wants its price/description/variants/reviews, or wants Macy's autocomplete suggestions for a query — instead of scraping macys.com. There is no full-text product search or category browse — a known numeric productId is required as the entry point.

Install macys-research

Run this in your OpenClaw agent to add macys-research from the ClawHub registry.

terminal
$openclaw skills install macys-research

Requires ClawHub registry access. Review the security analysis below before installing.

Security Analysis

危险50/100

Open Source

Code is publicly available for audit.

Community Verified

Reviewed by the ClawHub community.

Community Reviews

Real user ratings only — separate from the editorial assessment and ClawHub signal.

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Frequently asked questions

Is macys-research safe to install?

macys-research has a SkillsReview security score of 50/100. It is open source and community-verified on ClawHub. Check the full Security Analysis on this page before installing.

How much does macys-research cost?

macys-research is free to install for OpenClaw via ClawHub.

What are the best alternatives to macys-research?

You can compare macys-research side by side with similar OpenClaw skills on the SkillsReview comparison page to find the best fit for your workflow.

How do I install macys-research?

Install macys-research from ClawHub at clawhub.ai/skills/macys-research, or use the install action on this page to copy the command for your OpenClaw agent.

Community Signal

ClawHub Community Score6120.00 / 5.00
Installs144,126,000
Last UpdateAug 14, 2026
Actively maintained (0d ago)
ClawHub community score is a third-party marketplace signal. It is shown separately from SkillsReview editorial assessment and real user review averages.
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