voyager-debuglisted

# Debug Pipeline or Model Systematically debug and fix issues with Axelera AI pipelines, models, or inference ## Use This Skill When / Not When - Use when: the user brings an existing error, crash, log, regression, or wrong output. - Use when: the SDK install is missing, broken, or old, the driver/firmware mismatch, or the Metis board is not detected -- follow `references/install-and-board-health.md`. - Not when: debugging is part of building a brand-new pipeline -- route to voyager-launch. - Not when: they want pure performance measurement of a working pipeline -- route to voyager-bench. - Process precedence: when a failure is on the table, this skill runs before any domain skill changes code or config. ## Instructions Debug the specified issue: **$ARGUMENTS** {{INCLUDE common/voyager-sdk-setup.md}} {{INCLUDE common/voyager-task-integration.md}} ### Step 1: Issue Classification Identify the type of issue: - **Deployment Error**: Model fails to compile/deploy - **Runtime Error**: Inference fails or crashes - **Accuracy Issue**: Model produces incorrect results - **Performance Issue**: Low throughput or high latency - **Display Issue**: Visualization problems ### Step 2: Environment Diagnostics Run initial diagnostics. Only probe hardware directly when `.voyager-runtime.json` says `execution.mode` is `execute_on_device`. ```bash # Check environment echo "AXELERA_FRAMEWORK: $AXELERA_FRAMEWORK" echo "AXELERA_RUNTIME_DIR: $AXELERA_RUNTIME_DIR" echo "PYTHO