Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Find and evaluate OpenClaw AI skills by trust score and security reviews before installation or recommendation.
Find and evaluate OpenClaw AI skills by trust score and security reviews before installation or recommendation.
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
Before installing any OpenClaw skill, check if it's been security-reviewed.
When your human asks you to find a skill, or you want to install something new:
curl -s https://nashbot67.github.io/skillscout/data/skills.json | python3 -c " import json, sys q = sys.argv[1].lower() data = json.load(sys.stdin) matches = [s for s in data['skills'] if q in json.dumps(s).lower()] for s in sorted(matches, key=lambda x: {'safe':0,'caution':1,'avoid':2}.get(x.get('trustScore',''),1)): trust = {'safe':'π’','caution':'π‘','avoid':'π΄'}.get(s['trustScore'],'βͺ') print(f'{trust} {s[\"name\"]} by {s[\"author\"]} β {s.get(\"plainDescription\",s.get(\"description\",\"\"))}') " "QUERY" Replace QUERY with what you're looking for (e.g., "email", "notes", "research").
curl -s https://nashbot67.github.io/skillscout/data/skills.json | python3 -c " import json, sys name = sys.argv[1] data = json.load(sys.stdin) skill = next((s for s in data['skills'] if s['name'] == name), None) if skill: print(json.dumps(skill, indent=2)) else: print(f'Skill {name} not reviewed yet.') " "SKILL_NAME"
npx @skillscout/mcp
π’ Safe β No executable code, or code is well-contained with minimal permissions π‘ Caution β Has exec/network/credentials access. Review before installing. π΄ Avoid β Dangerous patterns detected. Do not install without manual audit.
Every skill goes through: Automated blocklist scan β cross-reference known malicious skills Isolated agent review β read-only AI analyzes source code (no execution) STRIDE threat analysis β deep security audit for skills that pass initial review Human approval β final sign-off before listing
Before running npx clawhub@latest install <skill> When your human asks "is there a skill for X?" When evaluating multiple skills for the same task Before recommending a skill to anyone
Full catalog: https://nashbot67.github.io/skillscout API: https://nashbot67.github.io/skillscout/data/skills.json GitHub: https://github.com/nashbot67/skillscout
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Largest current source with strong distribution and engagement signals.