| name | run-comfy-workflow |
| description | Execute an existing VibeComfy/ComfyUI workflow, ready template, recipe, or scratchpad and collect outputs. Use when the user asks to run, queue, execute, generate, render, smoke test, use a local/remote ComfyUI runtime, or run on RunPod. |
Run Comfy Workflow
Use this for execution. If the graph must change first, use edit-comfy-workflow. If ComfyUI or paths are not configured, use vibecomfy-setup. If a run fails, use debug-comfy-workflow.
Preflight
vibecomfy inspect <workflow>
vibecomfy validate <workflow>
vibecomfy doctor <workflow> --json
For raw JSON, convert before running:
vibecomfy port check <workflow.json> --json
vibecomfy port convert <workflow.json> --out out/scratchpads/<name>.py --json
Embedded Runtime
Use embedded when local ComfyUI is discoverable in the active environment:
vibecomfy run <workflow.py> --runtime embedded
vibecomfy run image/z_image --ready --runtime embedded
Prompt/seed/steps CLI overrides only work when the workflow exposes matching public inputs:
vibecomfy run image/z_image --ready --runtime embedded --prompt "..." --seed 7 --steps 20
Use dependency helpers only when the user wants VibeComfy to prepare local runtime assets:
vibecomfy run <workflow.py> --runtime embedded --ensure-packs --ensure-models
--ensure-packs is embedded-only.
Existing ComfyUI Server
Use this when the user already has ComfyUI running locally or remotely:
vibecomfy run <workflow.py> --runtime server --server-url http://127.0.0.1:8188
vibecomfy run image/z_image --ready --runtime server --server-url http://127.0.0.1:8188
Python-format workflows work against an existing server. VibeComfy imports the workflow's build(), compiles the VibeWorkflow to API JSON, and queues that JSON to the server.
The external server must already have the required custom nodes and models unless the user separately stages them into that server's environment. Do not use --ensure-packs with server runtime. --ensure-models can only prepare the local/shared model path VibeComfy can see.
For a VibeComfy-managed local HTTP server, omit --server-url:
vibecomfy run <workflow.py> --runtime server
--runtime auto attaches to an active default session when one exists; otherwise it falls back to embedded execution.
RunPod
Use RunPod when requested or when local execution is unavailable and a GPU run is necessary:
python scripts/runpod_acceptance.py
python scripts/runpod_validate.py
VIBECOMFY_MATRIX_SCOPE=<family> uv run python scripts/runpod_corpus_matrix.py
pytest --runpod -m runpod tests/smoke/test_layer2_runpod_ops.py
Use runpod_acceptance.py when the user asks whether the package works end to end in practice. It proves setup inspection, dependency dry-runs, direct API JSON queueing, raw JSON conversion, Python ready-template execution, converted-JSON Python execution, embedded runtime, existing ComfyUI server runtime, and artifact collection. Add --model-template <ready_id> --model-phase <phase> when the live proof must include a real model-backed template.
Use runpod_validate.py only for the cheapest launch/runtime sanity check. Use runpod_corpus_matrix.py after acceptance is green and the question is model-family or corpus coverage. Start with the smallest family/smoke scope that answers the question.
Report Outputs
Runs return a RunResult with run_id, prompt_id, outputs, metadata_path, and log_path. The same fields are persisted under out/runs/<run_id>/.
Report:
- generated files under the run directory
out/runs/<run_id>/metadata.jsonprompt_id when available- relevant
vibecomfy logs tail lines if execution failed
Do not report an edit candidate as a run result. A candidate graph from the Comfy app or agentic edit harness becomes a run result only after it is applied or executed through vibecomfy run / runtime APIs.
