voyager-new-pipelinelisted

# Create New AI Pipeline Create a YAML pipeline configuration for Axelera AI hardware using Voyager SDK ## Use This Skill When / Not When - Use when: the user explicitly wants a YAML pipeline configuration file only (detection, classification, segmentation, pose, cascade, parallel). - Not when: they want it built, run, or validated -- route to voyager-launch. - Not when: they want Python application code -- route to voyager-new-app. ## Instructions Follow these steps to create a new AI pipeline: **$ARGUMENTS** ### Step 0: Data Source & Environment Selection {{INCLUDE common/voyager-sdk-setup.md}} ### Step 0.5: Axelera Voyager Project & Task Integration {{INCLUDE common/voyager-task-integration.md}} {{INCLUDE common/examples-catalog.md}} ### Step 1: Pipeline Requirements Analysis - Parse the pipeline type from arguments (detection, classification, segmentation, pose, cascade, parallel) - If no arguments provided, ask user for: - Pipeline purpose (object detection, classification, segmentation, pose estimation, etc.) - Target model from model zoo or custom model - Input source type (camera, video file, image, RTSP stream) - Output requirements (display, file, metadata only) ### Step 2: Model Selection - Examples-first: check `common/examples-catalog.md`. If a shipped example matches the request, prefer running it (route complete/runnable requests to `voyager-launch`) rather than authoring a new pipeline. - If the user wants a complete runnable packag