Parallel Workflow: Feature Development Pipeline
This workflow defines the topological parallel execution steps for feature development pipeline.
Steps
Step 1: spec
Execute the spec phase for the feature-development-pipeline workflow under the dev-workflows domain. This involves orchestrating the designated specialists to process inputs, configure tools, and perform targeted operations. Expected: spec_artifacts
Step 2: plan [depends_on: spec]
Execute the plan phase for the feature-development-pipeline workflow under the dev-workflows domain. This involves orchestrating the designated specialists to process inputs, configure tools, and perform targeted operations. Expected: plan_artifacts
Step 3: parallel_impl_py [depends_on: plan]
Execute the parallel impl (py phase for the feature-development-pipeline workflow under the dev-workflows domain. This involves orchestrating the designated specialists to process inputs, configure tools, and perform targeted operations. Expected: parallel_impl_py_artifacts
Step 4: ts [depends_on: plan]
Execute the ts phase for the feature-development-pipeline workflow under the dev-workflows domain. This involves orchestrating the designated specialists to process inputs, configure tools, and perform targeted operations. Expected: ts_artifacts
Step 5: tests [depends_on: plan]
Execute the tests) phase for the feature-development-pipeline workflow under the dev-workflows domain. This involves orchestrating the designated specialists to process inputs, configure tools, and perform targeted operations. Expected: tests_artifacts
Step 6: review [depends_on: parallel_impl_py, ts, tests]
Execute the review phase for the feature-development-pipeline workflow under the dev-workflows domain. This involves orchestrating the designated specialists to process inputs, configure tools, and perform targeted operations. Expected: review_artifacts
Step 7: merge [depends_on: review]
Execute the merge phase for the feature-development-pipeline workflow under the dev-workflows domain. This involves orchestrating the designated specialists to process inputs, configure tools, and perform targeted operations. Expected: merge_artifacts
Execution
Run this workflow as a dependency-ordered DAG. Steps with no unmet depends_on run in parallel; dependents run after their prerequisites complete.
- Run first (in parallel): Step 1 — spec
- After level 0: Step 2 — plan
- After level 1: Step 3 — parallel_impl_py; Step 4 — ts; Step 5 — tests
- After level 2: Step 6 — review
- After level 3: Step 7 — merge
Execution: If graph-os is reachable, offload the whole DAG via graph_orchestrate action=execute_workflow (or the kg-delegate skill) for true parallel/swarm execution. Otherwise execute the steps natively in dependency order: run steps with no unmet depends_on in parallel, then their dependents.