Medium Risk

install_pack

Install all skills from a curated Agent Pack in a single call. Returns a formatted text response listing each skill in the pack with its name, type, slug, and platform-specific install config. Packs are pre-built collections for specific workflows (e.g., 'research-agent' has browser, search, and ...

Part of the Loaditout server.

install_pack can modify Loaditout data, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents use install_pack to create or modify resources in Loaditout. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.

Without a policy, an AI agent could call install_pack repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Loaditout.

Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "install_pack": {
      "limits": [
        {
          "counter": "install_pack_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

See the full Loaditout policy for all 21 tools.

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These attack patterns abuse exactly the kind of access install_pack gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so install_pack only ever does what you allow.

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Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.

What does the install_pack tool do? +

Install all skills from a curated Agent Pack in a single call. Returns a formatted text response listing each skill in the pack with its name, type, slug, and platform-specific install config. Packs are pre-built collections for specific workflows (e.g., 'research-agent' has browser, search, and memory tools). Use this instead of installing skills individually when setting up for a specific role. Do not use this if you only need one specific skill (use install_skill instead).. It is categorised as a Write tool in the Loaditout MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on install_pack? +

Register the Loaditout MCP server in PolicyLayer and add a rule for install_pack: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Loaditout. Nothing to install.

What risk level is install_pack? +

install_pack is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit install_pack? +

Yes. Add a rate_limit block to the install_pack rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block install_pack completely? +

Set action: deny in the PolicyLayer policy for install_pack. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides install_pack? +

install_pack is provided by the Loaditout MCP server (loaditout-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Loaditout tool call.

Deterministic rules across all 21 Loaditout tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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