Edge Copy setup link
Skill evidence / product-comparison
Skill profile

product-comparison

Let shoppers select multiple products and compare them side-by-side in a table with highlighted...

What this skill does for you

Let shoppers select multiple products and compare them side-by-side in a table with highlighted differences to help them make the right buying decision

Quoted from the skill description in the pinned source

Who made it

Publisherfinsilabs
Installs295as of Sep 27, 2026

Use it with Edge

Set up Edge for me: read getedge.cc/SKILL.md and follow it. Then use Edge to load the product-comparison skill from finsilabs/awesome-ecommerce-skills.

Paste it into Claude, ChatGPT, Codex or Cursor.

Or read the skill source first.

Security evidence

Security state at 2026-09-30: reviewed. State definitions. This records static evidence for this revision; live load eligibility is checked again.

3 static scans, 0 counted findings. The listed scanners recorded the results shown for this package revision.

ScannerDateResultFindings
Edge static checks2026-09-27Pass0
Cisco skill-scanner2026-09-27Pass0
Semgrep Edge rules2026-09-27Pass0

Static scans check the code, not how well the skill works.

Scanner scope, raw findings and mirrored provider records

Edge static checks (Edge-run): edge-static/1.0.1. Scope: Static patterns for remote execution, credentials with network sends, obfuscation, prompt overrides, hidden Unicode, binaries and persistence. Revision: 30a1fb674e41284e738608c059690c251699eb07. Raw findings: 1. Counted findings: .

Cisco skill-scanner (Edge-run): cisco-skill-scanner/2.1.0. Scope: Local static, YARA, pipeline and behavioral analyzers; no LLM or AI Defense analysis. Revision: 30a1fb674e41284e738608c059690c251699eb07. Raw findings: 1. Counted findings: .

Semgrep Edge rules (Edge-run): semgrep/1.178.0+edge-rules.c15016a36fd3+offline-v1. Scope: Six Edge-authored static rules with Semgrep CE; offline execution and metrics disabled. Semgrep-maintained rules excluded. Revision: 30a1fb674e41284e738608c059690c251699eb07. Raw findings: . Counted findings: .

Source and licence

Repository
https://github.com/finsilabs/awesome-ecommerce-skills
Pinned skill file
View source at revision
Revision
30a1fb674e41284e738608c059690c251699eb07
Package hash
sha256:2b9ef7c9236d1325f7a3d7962bae0125490dd7a44471cc889f6ae12f4e81b75e
Licence
MIT