--- title: "Qualification Task" slug: "qualification-task" updated: 2026-07-04T09:53:17Z published: 2026-07-04T09:53:17Z canonical: "docs.dataloop.ai/qualification-task" --- > ## Documentation Index > Fetch the complete documentation index at: https://docs.dataloop.ai/llms.txt > Use this file to discover all available pages before exploring further. # Qualification Task ## Overview Qualification tasks create an assignment over entire selected data for each of the assignees. By having ground-truth annotations, a score is calculated and provided for each of the assignees. ## How Qualification Works Qualification tasks provide a tool to evaluate annotators' skills and performance by letting them work on a 'test' task that has ground-truth answers hidden from them. After completing their work (the assignment-completed event), scores can be calculated by comparing annotations in items in their assignment with ground-truth annotations from the original data. Unlike consensus tasks, the annotator's work is not merged back into the original item, maintaining it as a clean qualification-test copy. By creating multiple qualification tests in the project context, managers can obtain insights into annotators' performances with various data (for example, image and video) and tools (box, polygon, etc.). --- ## Continuous Qualification Task Qualification tasks by nature never ends. Any new user added to them as an assignee receives an assignment that includes all items. This allows for creating a qualification test once in a project and using it for testing new annotators along the project's lifecycle. --- ## Qualification Score When selecting to enable qualification score, a Pipeline is created with 2 nodes: 1. Task node - the qualification task itself 2. Application node - running Dataloop default score function. Dataloop default score function is in [our GIT repository](https://github.com/dataloop-ai-apps/dtlpy-metrics/blob/main/README.md), and includes documentation of how score are calculated and saved for the different annotation types. As such, you can fork our GIT repo and customize the score function to facilitate your custom logic, then add it as a [new Application](https://docs.dataloop.ai/docs/faas-tutorial) and place it in the Pipeline instead of the default Dataloop score function. To learn more, contact the [Dataloop](https://dataloop.ai/contact/) team. --- ## Create Qualification Tasks 1. Open the **Human Tasks** from the left-side menu. 2. Click **Create Task**. The task type section popup is displayed. 3. Select the **qualification** from the popup. 4. Click **Continue**. ![](https://cdn.document360.io/53f32fe9-1937-4652-8526-90c1bc78d3f8/Images/Documentation/Screenshot 2026-02-11 at 14.24.09.png) #### 1. General Enter or select the required details in the **General** section: 1. **Task Name**: Enter a name for the new task. By default, the project name + (total number of tasks + 1) is displayed. *For example, if the project name is* ***abc*** *and the total number of tasks you have already is* ***5****, then the new task name is* ***abc-6****.* 2. **Owner**: By default, the current user's email ID is displayed. Click on it to select a different owner from the list. 3. **Priority**: Select a priority from the list. By default, **Medium** is selected. 4. **Completion Due Date** (Optional): Select a task due date from the calendar. If a date is chosen, you will have the option to lock the task once the due date has passed. 5. **Lock Task After Due Date**: When enabled, all assignments in this task will be locked for editing after the due date passes. Read [here](/1-3-8/docs/manage-your-tasks#lock-unlock-tasks) to unlock the task. 6. Click **Next: Data Source**. #### 2. Data source 1. Enter or select a Dataset from the list. 2. Click **Next: Recipe and Instructions**. #### 3. Recipe and Instructions 1. In the **Recipe and Instructions** section, enter or select a recipe according to your task and data type. The number of Labels and Attributes is displayed on the top-right side of the page: 1. **Recipe**: Select a recipe from the list. A preview of the recipe is displayed on the right-side panel. 1. If there is no recipe, select the [Project Recipe](https://docs.dataloop.ai/docs/recipes-overview#project-recipes), or click **Set Recipe** to create an unique recipe for your task. **Annotation Managers** can select the **Project Recipe** and view its details through Quick Preview; however, they do not have permission to open or modify the Project Recipe. 2. (Optional) Click on the recipe drop-down, and click on the **three dots** of a recipe to view more actions like [clone recipe](/1-3-8/docs/recipe-actions#clone-recipes), open the recipe in a new tab, etc. 3. (Optional) Click on the **three dots** from the right-side **Recipe Preview** for more actions like [clone recipe](/1-3-8/docs/recipe-actions#clone-recipes), open the recipe in the editor, [export ontology](/1-3-8/docs/recipe-actions#export-ontology), etc. 1. **Labeling Instructions (.pdf)**: The labeling instruction document is displayed, if available. Go to the **Recipe** section to upload a PDF instruction. You can select the page range accordingly. 1. Click **Next: Statuses**. The **Statuses** section is displayed. #### 4. Statuses 1. By default, the **Completed** status is selected. Click **Add New Status** to add a new status. 2. Click **Next: Assignments**. #### 5. Assignments 1. Configure the Distribution method in the **Assignments** section. **Allocation Method**: Distribution is selected by default. The distribution allocation method means that the items will be distributed in advance among users, equally or based on a custom percentage. The **Auto Distribution** option distributes the task equally among the users. By default, it is checked. 2. **Available Users**: Search for or select users from the list, and click the **Forward arrow** icon to add them to the Assigned users list. 3. **Assigned Users**: 1. Search for or view the assigned users from the list. The allocation percentage is equally distributed if you select Auto Distribution. 2. Select and click the **Backward** arrow icon to remove them from the Assigned Distribution list. Inactive users Inactive users are grayed out and disabled for redistribution, and available for reassignment. 1. Click **Next: Qualification**. #### 6. Qualification Enable advanced quality monitoring options to ensure data quality and review performance. 1. Apply [score function](https://docs.dataloop.ai/docs/tasks-overview#task-scoring-process), if required. 2. Click **Create Task**. The qualification task will be created and is displayed in the tasks list. To edit a qualification task, see the [Edit a task](https://docs.dataloop.ai/docs/create-labeling-tasks#edit-a-labeling-task) section.