Feature Development Pipeline

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: parallelimplpy [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: parallelimplpy_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 [dependson: parallelimpl_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 — parallelimplpy; 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.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: Knuckles-Team
• Source: Knuckles-Team/universal-skills
• License: MIT

Install and usage instructions live in the source repository linked above.