TASK.md

Task contract: build a resilient structured CLI pipeline with exit codes and error handling

Change only starter/pipeline.py.

• run_pipeline(items: list[dict], batch_size: int = 2) -> dict processes records in batches.
• Each record must be a dict containing non-empty 'id' (str) and positive 'value' (int or float).
• Valid items must be transformed into {'id': item['id'], 'processed_value': round(item['value'] * 1.1, 2)}.
• Invalid items must not crash the batch; they must be collected in an 'errors' list with {'id': item.get('id', 'unknown'), 'reason': str(error)}.
• The function must return a summary dict: {'total': int, 'successful': int, 'failed': int, 'results': list[dict], 'errors': list[dict]}.
• If batch_size < 1, raise ValueError.
• Do not add external dependencies; use only Python standard library.

Done means python examples/structured-pipeline/verify.py starter exits successfully.