workflow-runner

Orchestrate end-to-end SDLC workflows by loading YAML definitions and executing each step with checkpoint validation, guardrails, and audit logging. This enables reliable retries, rollbacks, and resumable runs across local, CI, and server environments.

Automated workflow orchestration for requirement-to-code coordinates multiple agents and skills to execute multi-step processes. It enforces guardrails, applies variable resolution, and uses state persistence to support quality gates and compliance.

Yes, workflow orchestration supports CI/server-mode execution and operates across local and cloud environments. It implements state persistence and checkpoint validation to enable reliable resumption, rollbacks, and audit analysis.

Run the workflow runner against a YAML definition file, such as a requirement-to-code workflow, in your sandbox project directory. The runner executes the defined steps, applies variable resolution, and generates audit logs for monitoring.

Yes, PyYAML is required as a dependency to load and parse the YAML workflow definitions. This dependency enables the runner to interpret multi-step process instructions and execute them with appropriate guardrails.

Checkpointed workflow orchestration provides automated and human-review checkpoints that validate state at each step. This approach prevents cascading errors by enabling reliable retries, rollbacks, and resumable runs rather than failing an entire sequential process.