pipeline-runner

You can automate multi-step agent workflows by loading a structured pipeline definition that orchestrates agent calls and records run IDs, timestamps, and per-step results in a central registry for end-to-end traceability.

Pipeline orchestration for repeatable automation scenarios is the process of executing structured step definitions sequentially or in parallel, passing inputs and capturing outputs between designated agents to handle deployment workflows and data processing tasks.

To structure a pipeline file for agent orchestration, define each step with required attributes including id, name, agent, input, output, success_condition, next_step, and on_failure to enforce structured step execution and reliable failure handling.

Yes, you can use pipeline automation for CI/CD-like deployment workflows and data processing tasks by assigning each step to a designated agent and applying retry or alert strategies for failure handling in repeatable automation scenarios.

The best way to handle failures in multi-step pipeline execution is to define an on_failure strategy within each step's structured definition, allowing the pipeline runner to apply retry logic or alert strategies and record the outcome in the central registry.

Yes, a central registry is required to log pipeline run results and traceability data, storing run IDs, timestamps, statuses, and per-step results to ensure proper auditing and troubleshooting of your automation workflows.