# Manage Annotation Workflow You can list annotation batches, inspect batch details, and create annotation jobs from the command line. ## Annotation Batches ### List Batches ```bash roboflow annotation batch list -p my-project ``` With JSON output: ```bash roboflow annotation batch list -p my-project --json ``` ### Get Batch Details ```bash roboflow annotation batch get -p my-project ``` ```bash roboflow annotation batch get -p my-project --json ``` ## Annotation Jobs ### List Jobs ```bash roboflow annotation job list -p my-project ``` ```bash roboflow annotation job list -p my-project --json ``` ### Get Job Details ```bash roboflow annotation job get -p my-project ``` ```bash roboflow annotation job get -p my-project --json ``` ### Create a Job ```bash roboflow annotation job create -p my-project \ --name "Label round 1" \ --batch \ --num-images 100 \ --labeler labeler@company.com \ --reviewer reviewer@company.com ``` #### Options | Flag | Description | | ----------------- | --------------------------------------- | | `-p`, `--project` | Project ID (required) | | `--name` | Job name (required) | | `--batch` | Batch ID to draw images from (required) | | `--num-images` | Number of images to include (required) | | `--labeler` | Labeler email address (required) | | `--reviewer` | Reviewer email address (required) | ## JSON Output All annotation commands support `--json` for structured output: ```bash roboflow annotation batch list -p my-project --json | jq '.[].id' roboflow annotation job create -p my-project --name "Job" \ --batch abc --num-images 50 --labeler a@co.com --reviewer b@co.com --json ``` Exit codes: 0 = success, 1 = error, 2 = auth error, 3 = not found. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.roboflow.com/developer/command-line-interface/manage-annotation-workflow.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.