validation-rules

Automating pipeline validation checks verifies that feature_input.yaml and task_specs.yaml parse as valid YAML, contain required non-empty sections, and maintain valid cross-file references to prevent structural defects from propagating downstream.

Per-stage validation is the process of verifying structural, semantic, and cross-file integrity across pipeline artifacts like clarifications.md and high_level_plan.md. You need it to ensure traceability and prevent defects before they propagate to later stages.

Enforcing topological task ordering and risk checks involves validating dependencies and risk awareness across stages by running an automated validation workflow that checks task_specs.yaml for correct ordering and cross-file coverage of RFC requirements.

Yes, pipeline validation works with Markdown files like clarifications.md and high_level_plan.md by verifying they exist, are non-empty, and meet structural criteria alongside YAML files to ensure end-to-end workflow integrity.

The best way to validate cross-file references is running an automated validation workflow that guarantees coverage of RFC requirements by tasks and validates dependencies between context_pack.yaml and task_specs.yaml to ensure semantic consistency.

Feature pipeline validation fails on empty sections because the rules enforce non-empty fields across artifacts like feature_input.yaml and high_level_plan.md, ensuring that required structural and semantic data is present before stage progression.