Question 1

How does SkillzBench handle script-bearing skills that could execute malicious code?

Accepted Answer

Launch scope is instruction-only skills (SKILL.md plus text references). Script-bearing skills are listed link-out only — SkillzBench never executes them, so your analysts get visibility without exposure.

Question 2

Can we control which skills each data analyst's agent can actually use?

Accepted Answer

Yes. Equip provides one MCP server plus per-agent loadouts — you toggle skills and tools per agent, and the agent only sees what was chosen. This gives you least-privilege control over AI capabilities, similar to how you govern other tool access.

Question 3

What happens when a skill we've approved changes upstream?

Accepted Answer

The Stay current pillar tracks upstream changes, re-scans, re-benchmarks, and notifies you. A skill that passed verification last month can't silently drift into a vulnerable or degraded state without you knowing.

Question 4

Is SkillzBench available now, or when can our team start using it?

Accepted Answer

SkillzBench is pre-launch and actively being built — the waitlist is live, the product is not yet public. Join the waitlist now to be first in line as the Discover, Verify, Benchmark, and Equip pillars come online.

Question 5

How is SkillzBench different from just letting analysts pick skills from GitHub or a marketplace?

Accepted Answer

Marketplaces rank by popularity and incentives; SkillzBench is an independent testing lab. Every version is pinned to a commit SHA, security-scanned, license-checked, and quality-judged, then benchmarked in a sandbox with the same model with and without the skill. Lift is always shown separately from ratings, and money never touches scores.

Team Skill Governance for Data Analysts