Use human approval whenever the skill can change state, access sensitive data or call external tools on its own. If a dangerous action would be unacceptable without review in a human workflow, it should not be acceptable when packaged as an agent skill. The threshold is operational impact, not convenience.
When a skill is acting like a control, not just a helper
Deciding on human-in-the-loop control starts with the skill’s authority, not its interface. If the skill can create, modify, delete, approve, transfer, publish, or otherwise change real state, it deserves review unless the organisation has explicitly accepted that risk. The same is true when the skill can reveal sensitive information or trigger tools that can reach beyond its immediate task.
A useful test is whether the action would be acceptable if a person did it without oversight. If the answer is no, packaging the action inside an agent skill does not make it safe. Treat that as a control boundary, not a convenience question.
How to separate low-risk assistance from reviewable action
Not every skill needs a person in the loop for every invocation. Teams should distinguish between informational support, where the skill summarizes, classifies, or drafts, and operational action, where it can execute something with external effect. The more a skill can influence money, access, customer data, production systems, or irreversible records, the stronger the case for approval gates.
That distinction becomes sharper when a skill can chain into other capabilities. A benign-looking request can become risky if it can call APIs, open tickets, change permissions, retrieve secrets, or pass instructions into other tools. AI Agent Authorisation Guide is a useful reference for the principle that per-action decisions and just-in-time authority are better fits than broad standing access. Privileged Access Management Guide also maps well to the idea that review becomes more important as a skill approaches privileged or high-blast-radius operations.
For teams building agentic features, the practical line is this: if the skill can act outside a sandbox, outside a draft-only flow, or outside a reversible preview, it should be treated as a governed action path rather than a convenience feature.
What security teams should standardise before enabling human approval
Human-in-the-loop works best when teams define the approval boundary in advance. That means deciding which action types always require review, which data classifications trigger review, and which tools are too sensitive for autonomous invocation. Approval should be tied to the effect of the action, not to the identity of the user asking for it or the apparent simplicity of the request.
There should also be a clear rule for escalation when a skill is close to privilege boundaries. If the skill can touch admin functions, production changes, customer records, or secrets, the approval process should be explicit, logged, and tied to a named owner. Analysis of Claude Code Security is relevant here because code-oriented agentic workflows often show the same pattern: the security question is whether human review exists before a tool-driven action can materially change the environment.
Current practice is moving toward policy by consequence, not policy by label. The most reliable programmes define review thresholds around change impact, data sensitivity, and tool reach, then enforce them consistently across all skills rather than making exceptions for “trusted” automation.
Risk and Threat Considerations
Skills that can act autonomously create concentrated exposure because one prompt, one workflow bug, or one misrouted tool call can produce a real-world change. The risk is highest where the skill can reach privileged systems, sensitive records, or external services that cannot be trivially rolled back.
Failure mechanism: A skill inherits more authority than its task needs, then a mistaken instruction, prompt injection, or logic flaw turns that authority into an unintended action path.
Impact: The result can be unauthorized change, data exposure, spend escalation, privilege misuse, or a downstream incident that is harder to contain because the action looked “automated” rather than deliberately approved.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
OWASP Agentic AI Top 10, OWASP API Security Top 10 and OWASP Non-Human Identity Top 10 address the attack and risk surface, while NIST SP 800-53 Rev 5 sets the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Agentic AI Top 10 | ASI03 — Identity & Privilege Abuse | Skills that can act on behalf of users need per-action authority checks and approval gates. |
| ASI02 — Tool Misuse | The question is about when a skill's tool access becomes risky enough for oversight. | |
| Recommendation — Enforce per-action authorization and human approval for skills that can change state or reach sensitive tools. Restrict tool invocation to approved actions and require review before sensitive tool use. | ||
| OWASP API Security Top 10 | API6 — Unrestricted Access to Sensitive Business Flows | Skills that can complete sensitive workflows without review can bypass intended business controls. |
| Recommendation — Gate sensitive workflows with approval steps before the skill can complete them. | ||
| OWASP Non-Human Identity Top 10 | NHI-05 — Overprivileged NHI | A skill with more authority than its task needs needs approval and least privilege. |
| Recommendation — Limit skill permissions to the minimum required and require review for higher-impact actions. | ||
| NIST SP 800-53 Rev 5 | AC-3 — Access Enforcement | Human-in-the-loop decisions are an access enforcement control for consequential actions. |
| Recommendation — Enforce approval before a skill can execute high-impact actions. | ||
Practitioner Guidance
What to verify: Confirm whether the skill can change state, reach sensitive data, or invoke external tools without a separate approval step. If any of those are true, review should be built into the workflow rather than added as a manual exception.
Decision rule: Use human approval for any skill action that would require review if performed by a person, even when the same action is packaged as automation. If the only reason to skip review is speed, the threshold is probably too low.
What good looks like: The skill can draft, recommend, or stage actions freely, but anything with operational impact is observable, attributable, and blocked until an approver accepts the specific effect, not just the request text.
Practitioner takeaway: Human-in-the-loop should protect the point where assistance becomes authority; once a skill can make a consequential change, the control should follow the impact, not the interface.
Related resources from NHI Mgmt Group
- How do security teams decide whether an AI agent needs PAM-style controls?
- How do IAM teams decide whether an AI security assistant needs its own access controls?
- How do teams decide whether email security needs identity controls more than another gateway layer?
- How can security teams tell whether human-in-the-loop controls are working?