Question 1

How does SkillzBench security-scan an agent skill before I put it on my resume?

Accepted Answer

SkillzBench's Verify pillar is being built to pin every skill version to a commit SHA, then validate it, license-check it, security-scan it, and quality-judge it. Results feed a 0-100 trust score built from security, quality, license, maintenance and community signals, so you can cite a scanned, pinned version rather than an unknown GitHub download.

Question 2

What does the SkillzBench trust score actually measure, and can I trust it as a job seeker?

Accepted Answer

The trust score is a 0-100 composite of security, quality, license, maintenance and community signals. Importantly, measured performance (Lift) is always shown separately from ratings, and money never touches scores — SkillzBench is an independent lab, so a paid placement can't inflate a skill's standing.

Question 3

Does SkillzBench work with the AI agents security teams actually use?

Accepted Answer

SkillzBench's Equip pillar is being built as one MCP server supporting instruction-only skills (SKILL.md packages) for agents like Claude Code, Codex, Cursor, Gemini CLI and chat-app agents. You toggle skills and tools per agent, and each agent only sees what you chose. Script-bearing skills are listed link-out only at launch.

Question 4

Is SkillzBench available now, or when can I start scanning skills?

Accepted Answer

SkillzBench is pre-launch and actively being built — the waitlist and newsletter are live, but the product itself is not yet public. Join the waitlist to be notified when Discover, Verify, Benchmark, Equip and Stay current go live. No live user or skill counts should be assumed yet.

Question 5

How is SkillzBench different from just browsing GitHub for agent skills?

Accepted Answer

GitHub shows stars and READMEs; SkillzBench shows evidence. Every skill is deduped from continuous crawling, pinned to a commit SHA, security-scanned, license-checked, and benchmarked in a sandbox with the same model with and without the skill — publishing the Lift in percentage points. You get a trust score and measured performance instead of popularity signals.

Agent Security Scanning for Job Seekers