Question 1

How does SkillzBench handle skills that contain scripts, not just SKILL.md instructions?

Accepted Answer

At launch, SkillzBench's full pipeline — verification, benchmarking, and enablement via the MCP server — covers instruction-only skills (SKILL.md plus text references). Script-bearing skills are listed link-out only, so you get visibility without the execution risk.

Question 2

Can we restrict which AI agent skills our security engineers' agents can load?

Accepted Answer

Yes — that's the Equip pillar. One MCP server powers per-agent loadouts, and users toggle skills and tools per agent. Each agent only sees what was chosen for it, giving you a governed allowlist-style control over what reaches production tooling.

Question 3

How do you keep skill ratings trustworthy when vendors and creators are involved?

Accepted Answer

SkillzBench separates money from scores entirely — ratings and Lift are never influenced by payment. Every skill is benchmarked in a sandbox with the same model, with and without the skill, and the Lift is published in percentage points. A 0-100 trust score is built from security, quality, license, maintenance, and community signals.

Question 4

What happens when a skill we've enabled changes upstream on GitHub?

Accepted Answer

The Stay Current pillar tracks upstream changes, re-scans and re-benchmarks the skill, and notifies you. Because every version is pinned to a commit SHA, you always know exactly which version your agents are running and can decide whether to adopt the update.

Question 5

We already do manual skill reviews in-house — why add an independent testing lab?

Accepted Answer

Manual reviews don't scale and can't be reproduced consistently. SkillzBench runs every skill through the same verification pipeline — license check, security scan, quality judgment — and benchmarks it in a sandbox with the same model. Teams plans add org-level loadouts, allowlists, and audit capabilities, so governance becomes systematic rather than ad-hoc.

Team Skill Governance for Product Managers