Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Verify skill provenance and build trust scores for ClawHub skills. Checks publisher history, version consistency, dependency trust chains, and generates trus...
Verify skill provenance and build trust scores for ClawHub skills. Checks publisher history, version consistency, dependency trust chains, and generates trus...
This item's current download entry is known to bounce back to a listing or homepage instead of returning a package file.
Use the source page and any available docs to guide the install because the item currently does not return a direct package file.
I tried to install a skill package from Yavira, but the item currently does not return a direct package file. Inspect the source page and any extracted docs, then tell me what you can confirm and any manual steps still required.
I tried to upgrade a skill package from Yavira, but the item currently does not return a direct package file. Compare the source page and any extracted docs with my current installation, then summarize what changed and what manual follow-up I still need.
Trust, but verify. Assess the trustworthiness of a ClawHub skill by analyzing its publisher, history, dependencies, and consistency.
Security scanning catches known malicious patterns. But what about skills that are technically clean but published by unknown authors, have inconsistent version histories, or depend on untrusted packages? Trust Verifier fills the gap between "no vulnerabilities detected" and "safe to install."
python3 {baseDir}/scripts/trust_verifier.py assess --path ~/.openclaw/skills/some-skill/
python3 {baseDir}/scripts/trust_verifier.py attest --path ~/.openclaw/skills/some-skill/ --output trust.json
python3 {baseDir}/scripts/trust_verifier.py verify --attestation trust.json --path ~/.openclaw/skills/some-skill/
python3 {baseDir}/scripts/trust_verifier.py deps --path ~/.openclaw/skills/some-skill/
Publisher reputation: Known vs unknown publisher, account age, skill count Version consistency: Do updates match expected patterns? Sudden permission changes? Content integrity: SHA-256 hashes of all files, reproducible builds Dependency chain: Are dependencies from trusted sources? Community signals: Moltbook mentions, upvotes, known endorsements
VERIFIED β Meets all trust criteria, attestation valid TRUSTED β Most signals positive, minor gaps UNKNOWN β Insufficient data to assess trust SUSPICIOUS β One or more trust signals failed UNTRUSTED β Multiple trust failures, do not install
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Largest current source with strong distribution and engagement signals.