git:20260804.fb8aaef to git:20260813.a1cc4ea

---

name: workbench-reference-workflows

description: Use when working on NPA reference workflow specs, runner scripts, cookbooks, customer-adaptable pipeline implementations, or the guarded examples that are not workflow authoring surfaces.

---

# Workbench Reference Workflows

> The supported, customer-facing catalog and source of truth is the `npa.workflow` spec set under

> `npa/workflows/workbench/npa-workflows/`. The old raw SkyPilot task catalog has

> no remaining templates. Raw SkyPilot YAMLs may still exist only as guarded

> tool-specific examples or resource profiles, not as workflow authoring

> surfaces. SkyPilot remains the engine that executes rendered specs.

## When To Use

Use this skill for repository workflow YAMLs, runner scripts, cookbooks,

artifact contracts, and customer-adaptable pipeline implementations.

## Procedure

1. Start from the closest checked-in `npa.workflow` spec under

`npa/workflows/workbench/npa-workflows/`.

2. Reuse a toolRef from

`npa/src/npa/orchestration/npa_workflow/catalog.py`; add missing behavior to

the workbench tool rather than implementing it again in a runner.

3. Keep the runner thin. Python runners materialize config, call the workflow

submission helper, and report artifacts; the spec owns the stage graph.

4. Keep all input and output paths configurable and run-scoped through S3.

Stages run in separate pods and cannot depend on a repository-relative path.

5. Declare the output the tool actually writes. Extend

`test_spec_declared_outputs.py` when a tool exposes a result-URI helper.

6. Run `validate-spec`, then `plan-spec --run-id preview`, before live submit.

Register every shipped spec in `SUBMIT_LIVE_MATRIX`.

## Current Reference YAMLs

The retired catalog path is machine-checked by

`npa/tests/guardrails/test_skypilot_catalog_retirement.py`, so a raw template

cannot quietly reappear there.

No raw SkyPilot templates remain in the retired catalog. Author workflow examples

as `npa.workflow/v0.0.1` specs under

`npa/workflows/workbench/npa-workflows/`.

## Retired Templates

These raw templates were retired once their `npa.workflow` spec had a live run

(run ids in `EVIDENCE.md`). Use the spec under

`npa/workflows/workbench/npa-workflows/`:

- `isaac-lab-rl-sweep.yaml` — parallel GPU sweep (`--runtime`).

- `cosmos3-reason.yaml` — Cosmos3 reason-stage manifest.

- `sonic-export.yaml`, `sonic-eval.yaml`, `sonic-export-eval.yaml` — SONIC

export/eval. The tools now accept `s3://` inputs and outputs directly, which is

what the templates' inline download/upload bash used to do.

- `token-factory-caption.yaml`, `token-factory-generate.yaml`,

`token-factory-cosmos-reason.yaml` — hosted Token Factory stages.

- `mjlab-eval.yaml` — MJLab locomotion evaluation.

- `retargeting.yaml` — motion retargeting. The harness synthesizes a SOMA-CSV clip

(`npa.workflows.motion_fixture`) when no real motion set is staged.

- `vlm-eval.yaml`, `vlm-eval-benchmark.yaml` — self-hosted VLM scoring and the labeled

sweep. The renderer now starts and health-checks the vLLM server the spec asks for, so

no prebuilt serving image is needed.

- `cosmos3-text-to-image-inference.yaml` — retired to

`npa-workflows/cosmos3-text-to-image.yaml`. The procedure it carried as bash inside an `envs:`

block is now `npa workbench cosmos3 text-to-image`.

- `bdd100k-pipeline.yaml` — retired to `npa-workflows/bdd100k-pipeline.yaml`. A live run needs

both in-cluster services (`lancedb` and `detection-training`) deployed first.

- `dataset-ingest-curate.yaml` — retired to `npa-workflows/dataset-ingest-curate.yaml`, whose

`register` stage reads back what `ingest` wrote to the in-cluster LanceDB service

(`npa workbench lancedb deploy --runtime kubernetes --namespace workbench`).

- `sim-to-real-pipeline.yaml` / `sim-to-real-trigger.yaml` — retired. The pipeline ran the

- `cosmos2-transfer.yaml` — retired to `npa-workflows/cosmos2-transfer.yaml`, which runs the

REAL Cosmos-Transfer2.5 model (`--execute`) instead of printing a `contract_ready` payload.

- `isaac-franka-capture-reason.yaml` — retired to

`npa-workflows/isaac-franka-capture-reason.yaml`. The capture code moved into the package

(`npa.workflows.isaac_capture`), so the stage no longer needs a repo mounted into the pod.

- `sim2real-actions.yaml` — retired into `npa-workflows/sim2real-envgen-shards.yaml` as its

fourth stage, which conditions the train slice the `split` stage just wrote.

- `tokenfactory-scene-to-rollout-judge.yaml` — hosted reasoner, GPU rollout, hosted judge. Its

twin keeps the chain: `vlm-eval run --task-from` reads the reasoner's artifact, so the judge

scores the rollout against the plan rather than a literal string.

- `tokenfactory-rollout-judge.yaml` — GPU rollout then a hosted VLM judge. Its twin is

`npa-workflows/tokenfactory-rollout-judge-combo.yaml`; note the older same-named spec is a

*different* workflow (a Cosmos reasoner feeding a judge over externally-seeded rollouts).

- `tokenfactory-train-triage.yaml` — GPU LeRobot training then a hosted triage report. Its twin

`npa-workflows/tokenfactory-train-triage.yaml` trains in the stage's own pod (the renderer

switches to the vendor image's interpreter) and triages with

`npa.workflows.token_factory_triage`. Needs a SkyPilot-hostable LeRobot image; 0.5.1 ships a

torch/torchcodec ABI mismatch, 0.6.0 does not.

- `cosmos3-ea-fetch.yaml` — Cosmos source/checkpoint fetch. Its twin

`npa-workflows/cosmos-fetch.yaml` is the two CLI commands the template wrapped in ~60 lines

of setup bash; the renderer installs `huggingface_hub[cli]`, which was the only load-bearing

line of that preamble.

- `cosmos3-generate.yaml` — Cosmos 3 omni-model generation in the `npa-cosmos3`

image. Its twin `npa-workflows/cosmos3-generate.yaml` ran through the live

submit matrix and produced `generated/generate.json` plus a non-flat 960x960

`generated/vision.jpg`.

- `nurec-reconstruct.yaml` — **relocated**, not retired: #234 deliberately

shipped and live-verified a single-pod NuRec/NRE SkyPilot task in addition to

the multi-pod `npa.workflow` spec. It now lives at

`npa/src/npa/workbench/nurec/examples/` with its own README and guardrail.

- `sim2real-envgen-split.yaml` — raw env generation + 80/20 split. Its twin

`npa-workflows/sim2real-envgen-shards.yaml` declares the shard fan-out as a `parallel:`

group instead of relying on a Kubernetes Job completion index, and runs on CPU.

- `scenario-gen-adversarial.yaml` — adversarial scenario mining. Its twin

`npa-workflows/scenario-gen-smoke.yaml` runs the same two CLI commands; the template's GPU

image advertised an RL adversary the CLI cannot select.

- `sim-to-real-loop.yaml` — the rollout-SET loop. Retired via a new tool capability

(`npa workbench vlm-eval loop`), because nothing else produced

`task_success_report.json`; the spec is `npa-workflows/vlm-eval-loop.yaml`.

- `isaac-lab-cosmos-sdg-burst-smoke.yaml` — **relocated**, not retired: a single-task input to

`npa burst submit-yaml`, now at `npa/src/npa/burst/examples/`. Burst is scoped to one

executable task, so there is no plan or stage graph for a spec to describe.

- `isaac-lab-rl-train-rtxpro.yaml`, `isaac-lab-rl-train-rtxpro-smoke.yaml`,

`isaac-lab-rl-train.yaml`, `byof-datagen-rtxpro-smoke.yaml`,

`byof-container-smoke-rtxpro.yaml` — **relocated**, not retired: they are BYOF

*resource profiles* (a pod shape), not workflows, and now live beside their

runner at `npa/src/npa/workflows/byof/profiles/`.

The retired catalog is pinned empty in

`npa/tests/guardrails/test_skypilot_catalog_retirement.py`; do not add new raw

workflow templates.

## Three-Tier Contract

- CLI: use `npa workbench workflow ...` and tool-specific workflow commands

such as `npa workbench mjlab workflow` or `npa workbench retargeting workflow`.

- SDK: route through shared workflow submission helpers rather than shelling out

from business logic.

- Workflow: the `npa.workflow` spec is the executable source of truth for stage

order, resources, configuration, and artifact paths. ToolRef argv templates

are the source of truth for commands; SkyPilot is the rendered execution

layer.

## Gotchas

- Customer-provided raw SkyPilot `envs` does not support self-referencing

interpolation; repository specs use resolved `config` tokens.

- `sky jobs launch` has no dry-run flag. Use `workflow submit --plan-only` for a

rendered spec preflight.

- Keep SONIC locomotion orchestration in its spec; do not add a Python runner

that re-implements the graph.

## Verify

```bash

npa/.venv/bin/python -m pytest npa/tests/guardrails/test_skills_index.py -q

```

The smoke test parses the listed workflow YAMLs and invokes workflow CLI help.