Safe Agent Skills helps you browse risk. You still need an install verdict.
Safe Agent Skills is useful catalog-style infrastructure for seeing analyzed skill risk at scale. Agent Skill Safety Kit is the decision workflow around a specific skill: permission boundaries, memory-write policy, receipts, exception handling, eval evidence, rollback, and the final install/list/sandbox/reject verdict.
Last updated: 2026-09-25. This is a practical comparison, not a vendor attack. For high-authority AI-agent skills, catalog risk data and explicit review contracts should work together.
Use Safe Agent Skills when you want broad catalog discovery and precomputed skill-safety signals. Use Agent Skill Safety Kit when your team needs to decide whether a particular skill should be installed, listed, sold, delegated, sandboxed, or rejected in your environment.
Open the free kit Run the scorecard Validate a permission manifestWhere each layer fits
| Question | Safe Agent Skills | Agent Skill Safety Kit |
|---|---|---|
| Which public skills look risky at a glance? | Strong fit. Catalog, risk labels, and safety data sheets help builders browse a large universe of skills before they install. | Not a replacement for a broad catalog. The kit is focused on reviewing a chosen skill or candidate package. |
| What authority will this skill receive inside our agent? | Catalog risk can inform the decision, but it cannot know your local tools, secrets, workflows, customers, memory stores, or approval rules. | Primary fit. The permission manifest makes allowed reads, writes, browser/API actions, memory updates, messages, spend, and approvals explicit. |
| Can we explain why we approved or rejected the skill? | Safety sheets are useful evidence, but the final business/engineering rationale still needs local policy and disposition. | Primary fit. The review kit produces a clear verdict: install, install with limits, ask for changes, reject, or manual/paid review. |
| What proof should the skill leave after it acts? | Catalog risk labels usually stop before runtime receipt design. | Primary fit. Requires receipt fields, before/after state, source-of-truth checks, exception behavior, and rollback notes. |
The workflow I would actually use
- Discover: use Safe Agent Skills or a similar catalog to identify candidate skills and obvious red flags.
- Pin provenance: source URL, version, author/vendor identity, package hash or commit, and claimed use case.
- Scan and inspect: run static scanners where available; record findings as evidence, not as the whole decision.
- Write a permission manifest: exact local authority for reads, writes, tools, memory, messages, outbound actions, spend, and human gates.
- Score the skill: check identity, inputs, data access, tool authority, output contract, receipts, memory, exceptions, evals, rollback, and portability.
- Decide launch verdict: install, install with limits, sandbox, ask for changes, reject, or request a short custom review.
Why catalog safety is not enough by itself
A medium-risk research skill can become high-risk if your agent runs with browser, SaaS, customer-message, finance, file, or durable-memory authority.
Your approval gates, source-of-truth rules, private data boundaries, and rollback requirements are not visible from a public catalog entry.
Before a skill crosses a trust boundary, teams should know what proof it leaves and how failures are queued, reversed, or escalated.
Free artifacts
- Agent Skill Safety Kit — free review workflow and downloadable package.
- Agent Skill Safety Scorecard — browser-local 100-point readiness check.
- Permission Manifest Template — define authority before delegation.
- Permission Manifest Validator — locally validate manifest completeness.
- Sample Mini-Report — what a concise review verdict looks like.
If a skill has real browser/file/SaaS/customer/memory authority and the free review exposes gaps, use the $29 Custom Agent Audit Mini-Report for a short redaction-friendly review. For low-authority skills, the free kit is enough.