L

LYGO-MINT Verifier

VERIFIED

by community

No community reviews yet
85,658installs
Updated May 2026

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Description

LYGO-MINT verifier for Champion/alignment prompt packs: canonicalize a pack, generate a deterministic SHA-256 hash, write append-only and canonical ledgers, and output a portable Anchor Snippet for posting anywhere (Moltbook/Moltx/X/Discord/4claw). Use when you need verifiable, hash-addressed alignment artifacts (Champion packs, summon prompts, workflow packs) with receipts and optional anchor backfill.

Install LYGO-MINT Verifier

Run this in your OpenClaw agent to add LYGO-MINT Verifier from the ClawHub registry.

terminal
$openclaw skills install lygo-mint-verifier

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

Security Analysis

⚠️警告74/100

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 LYGO-MINT Verifier safe to install?

LYGO-MINT Verifier has a SkillsReview security score of 74/100. It is open source and community-verified on ClawHub. Check the full Security Analysis on this page before installing.

How much does LYGO-MINT Verifier cost?

LYGO-MINT Verifier is free to install for OpenClaw via ClawHub.

What are the best alternatives to LYGO-MINT Verifier?

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

How do I install LYGO-MINT Verifier?

Install LYGO-MINT Verifier from ClawHub at clawhub.ai/skills/lygo-mint-verifier, or use the install action on this page to copy the command for your OpenClaw agent.

Community Signal

ClawHub Community Score3.64 / 5.00
Installs85,658
Last UpdateMay 17, 2026
Actively maintained (24d 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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