Neither AI agent skills nor plugins are inherently safer. A skill can include executable scripts, while a plugin can add tools, an MCP server, or other client-specific behavior. To judge risk, look at what a package can access and do, how its host runs it, and what controls limit or approve those actions—not at the label on the package.
What are skills and plugins in this comparison?
Agent skills
The Agent Skills project describes a skill as a portable folder centered on a required SKILL.md file. The folder may also contain scripts, reference documents, templates, and other assets. An agent can discover available skills, load a skill’s instructions when relevant, and, depending on the host, access its supporting resources or run its scripts. This is a format and loading model, not a security certification. Microsoft Agent Framework documentation likewise describes hosts loading instructions and resources and running scripts through host-provided tools.
For that reason, “skills are only prompts” is not a safe assumption. Instructions can affect how an agent behaves, and bundled code may run if the host provides a way to execute it.
Plugins
“Plugin” does not have one universal meaning across agent products. In OpenAI’s current developer documentation, a plugin is an installable package that can bundle one or more skills and an optional MCP server, which can expose tools and structured results. It may also include a user interface. OpenAI recommends a skill when instructions and tools already available to the agent are enough; an MCP server is appropriate when an extension needs to connect to a service, expose controlled tools, authenticate users, or run behavior on infrastructure its developer controls.
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The Agent Plugins open specification also describes packages containing skills and MCP servers, with optional, namespaced client extensions. Each client defines the contents and behavior of its own extensions. A package format that can be shared across clients does not establish that every client runs it with the same safeguards.
Are AI agent skills safer than plugins?
There is no reliable category-wide ranking. A skill containing instructions but no executable code may have a narrower capability set than a plugin that connects to services and offers write-capable tools. But a host may also give a skill broad access or run its scripts with substantial privileges; a plugin may contain only a skill or operate behind tightly limited permissions. Assess the actual package and the host’s execution model.
| Security question | What to examine in a skill | What to examine in a plugin |
|---|---|---|
| Capability and permission scope | Instructions, tools the host makes available, requested data access, and any read or write actions. | Bundled skills, MCP tools, service connections, authentication, requested scopes, and any client-specific features. OpenAI’s plugin guidance notes that plugin tools can access user data, third-party APIs, and write actions. |
| Execution boundary | Whether the host can run included scripts, and what filesystem, network, secrets, environment variables, and runtime resources those scripts can reach. | Whether bundled scripts or subprocesses run, which infrastructure executes them, and what data or resources the server and client components can access. A package path check is not process isolation. |
| Provenance and change control | Who authored the folder, what version is installed, and whether its files can be inspected, approved, pinned, and updated. | The plugin publisher and version, the provenance of each bundled component, and whether administrators can inspect and control updates. |
| Human and administrator controls | Whether the host limits available tools and requires confirmation for consequential actions; whether admins can inventory and audit usage. | Whether the client and any connected service enforce role limits, confirmation for consequential actions, inventory controls, and audit logging. |
| Scanning scope | Which files and threats the scanner checks, what its result means, and what it excludes. | Whether scanning includes bundled skills and other components such as MCP servers or hooks, and how existing installations are handled. |
The Agent Plugins specification’s path-containment rules prevent package paths from escaping a plugin’s root, but the specification says those rules do not sandbox a plugin subprocess or restrict paths passed at runtime. Structural validation helps prevent a class of path errors; it does not confine a running process.
How do I know if an AI agent skill or plugin is safe?
No checklist can prove a package safe, but these checks help reveal its trust boundary before you enable it:
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- Verify provenance and version. Identify the author and source, inspect the package manifest and files, and record the version you plan to install. A widely shared format is not an endorsement of its contents.
- Map every capability. Look for scripts, hooks, MCP servers, service connections, network use, secret access, and tools that can create, edit, delete, send, or publish data. Distinguish read access from write access.
- Find out what actually runs. Determine which host, client, or server executes each component. Check what files, environment variables, credentials, network destinations, and runtime resources it can reach, and whether execution is sandboxed. Microsoft’s Agent Framework guidance recommends production sandboxing, resource limits, input validation, allow-listing, and audit trails for script runners. Its MCP archive path intentionally does not execute scripts from remote archive skills.
- Reduce permissions. Grant only the scopes, storage, tools, and network access needed for the task. OpenAI Developers’ “Security & Privacy” guidance calls this least privilege and also recommends explicit user consent, defense in depth, server-side input validation, patched dependencies, and audit logs.
- Put a person in control of high-impact actions. Require review or confirmation before irreversible or consequential operations. OpenAI’s prompt-injection guidance recommends careful review before confirming such actions; confirmation is a safeguard, not a guarantee that an action is safe.
- Set an operating policy. Keep an inventory, decide who can approve installations and updates, pin or review versions where possible, and maintain audit records. Reassess access when a package changes.
Why prompt injection changes the trust decision
An agent may process instructions not only from its user but also from tools, retrieved documents, or third-party services. OpenAI describes prompt injection as malicious instructions inserted into an agent’s context that attempt to steer it toward actions the user did not request. A skill or plugin can expand what the agent is able to do, while untrusted content can try to persuade it to do those things.
Microsoft Learn’s “Agent Safety” guidance treats user, assistant, and tool messages as untrusted and warns that a compromised data store can deliver indirect prompt injection. It says secure agent development is a shared responsibility between the framework and application developers. Validate and sanitize model output before using it in security-sensitive contexts; secure serialized sessions; and limit inputs, outputs, and request rates. Anthropic’s agent-safety principles similarly emphasize human control, transparency, secure interactions, and privacy, noting that less oversight can increase the chance of unintended actions.
OpenAI Developers states: “Assume prompt injection and malicious inputs will reach your server.” Treat that as a reason to design for containment and review, not as a claim that every attack can be prevented.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What does skill and plugin scanning actually establish?
Anthropic Help Center documents scanning for third-party skills and plugins, including skills packaged inside a plugin, on Enterprise plans in Claude, Claude Cowork, and Enterprise plugin marketplaces. For covered uploads or edits, the scanner returns pass, warn, or fail: a fail blocks use; a warn can be used after acknowledgment; and a pass means the scan did not find a threat in its target class.
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Anthropic’s documentation says scanning was off by default until October 2, 2026, when it turns on for Enterprise organizations that have not set it. Since that date has passed, administrators should check their organization’s current setting rather than assume the default is configured as expected.
- The documented scan does not cover MCP servers or hooks.
- It does not scan items installed before scanning was turned on.
- It excludes skills created with Claude and certain customer-managed-encryption, zero-data-retention, and HIPAA configurations.
- Anthropic cautions that a pass is not a guarantee that an item is safe in every respect and recommends using skills and plugins only from trusted sources.
As Anthropic puts it, “A pass result means the scan didn’t find that kind of threat.” A scanner is one layer of defense: it can flag some known or targeted concerns, but its result applies only to the components and threat classes it checks.
How much weight should you give published vulnerability rates?
A 2026 study, Agent Skills in the Wild: An Empirical Study of Security Vulnerabilities at Scale, collected 42,447 skills from two marketplaces and analyzed 31,132 using static analysis and LLM-based semantic classification. The authors reported that 26.1% of the analyzed sample contained at least one vulnerability. That figure describes those marketplaces, that sample, and the study’s detection method; it is not a prevalence estimate for every skill, marketplace, platform, or the current ecosystem.
The same study reported that skills bundling executable scripts were 2.12 times more likely to contain vulnerabilities in its analyzed sample (odds ratio 2.12; p<0.001). This is an association, not proof that scripts alone cause vulnerabilities. It is a reason to inspect executable content and its runtime permissions carefully—not a reason to conclude that every script-bearing skill is unsafe.
When is a skill or plugin the better fit?
Choose based on what the task needs, then review the security consequences of that choice. If instructions and tools already available to the agent are sufficient, OpenAI’s plugin guidance points to a skill. If the extension must connect to a service, expose controlled tools, authenticate users, or run behavior on infrastructure maintained by its developer, an MCP server or plugin package may be a better functional fit. That choice describes architecture, not a trust level: apply the same review of permissions, execution, provenance, approvals, and auditability to either.
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