{
  "context": "Evaluates how the solution leverages JupyterLab's extension manager APIs to reconcile allow/block directives. Checks that code reads extension state from the manager model, performs installs/enables/disables/removals through manager methods, and builds summaries from those results.",
  "type": "weighted_checklist",
  "checklist": [
    {
      "name": "Manager API only",
      "description": "Obtains the `IExtensionManager` token from `@jupyterlab/extensionmanager` and routes all extension operations through it instead of shelling out to pip/npm or editing settings files directly.",
      "max_score": 20
    },
    {
      "name": "Read state via model",
      "description": "Uses the manager's model (e.g., `manager.model` / `ListModel`) to enumerate installed extensions and their enabled flags before applying directives, rather than relying on hardcoded lists.",
      "max_score": 20
    },
    {
      "name": "Install allowlist",
      "description": "For missing allow-list entries, calls `manager.install(name)` and then `manager.enable(name)` to pull from the default index and activate the extension when installation succeeds.",
      "max_score": 20
    },
    {
      "name": "Disable/remove blocklist",
      "description": "For blocked extensions that are present, invokes `manager.disable(name)` and, when removal is requested, `manager.uninstall(name)` to ensure they no longer load.",
      "max_score": 20
    },
    {
      "name": "Plan reflects results",
      "description": "Builds the returned plan/warnings directly from `IExtensionManager` outcomes (successful installs/enables/disables/uninstalls or thrown errors) instead of synthesizing statuses without manager feedback.",
      "max_score": 20
    }
  ]
}