| name | xpu-runtime-preflight |
| description | Run a read-only go/no-go preflight before any Intel GPU/XPU skillpack work. Checks driver health, /dev/dri permissions, render/video groups, Docker, /dev/shm, disk, proxy, and optional container-level XPU visibility. Use when the user asks whether a machine is ready for XPU model work or needs a reusable lab readiness report. Not for launching workloads, pulling images, editing system config, or verifying model output. |
xpu-runtime-preflight
Use this as the shared readiness gate before Intel GPU/XPU skills in
this pack. It answers "is this host/container ready for the requested
skill path?", reports a READY / READY WITH WARNINGS / BLOCKED
verdict, and routes failures to focused skills. It does not start model
servers, run benchmarks, capture profiles, restart Docker, pull large
images, edit system configuration, or validate generated content.
When To Use
Run this before a model run, benchmark, profile, or container workflow
when readiness depends on more than GPU discovery. Use xpu-discover
for device inventory and driver health; use this skill for the broader
go/no-go path: /dev/dri, groups, Docker, shared memory, disk, proxy
and network checks, plus optional container XPU visibility.
If preflight finds a blocker, follow the generated SUMMARY.md handoff.
Do not duplicate routing guidance in this skill body.
Quick start
plugins/intel-gpu-ai-skills/skills/xpu-runtime-preflight/scripts/check_runtime_preflight.sh \
--target-gpu 0 \
--out-dir .out/skills/xpu-runtime-preflight
Add an already-local image when the next skill path runs in a container:
plugins/intel-gpu-ai-skills/skills/xpu-runtime-preflight/scripts/check_runtime_preflight.sh \
--target-gpu 0 \
--image <already-local-image>
When downloads or image builds are part of the next step, add a network
check:
plugins/intel-gpu-ai-skills/skills/xpu-runtime-preflight/scripts/check_runtime_preflight.sh \
--env-file .env \
--target-gpu 0 \
--network-check
The script writes:
.out/skills/xpu-runtime-preflight/SUMMARY.md
.out/skills/xpu-runtime-preflight/status.tsv
.out/skills/xpu-runtime-preflight/preflight.log
It also writes per-check evidence files such as
xpu-smi-discovery.txt, xpu-smi-precheck.txt,
xpu-smi-diag-target.txt, xpu-smi-stats-target.txt,
target-driver.txt, dev-dri.txt, docker-info.txt, and, when
--image is supplied, image-preflight.txt.
What Counts As Ready
Hard pass before GPU/XPU skill work:
xpu-smi discovery sees the target GPU.- The target GPU has an inspectable kernel driver binding.
xe and
i915 are accepted; vfio* blocks because the host driver did not
bind the target GPU for XPU runtime use.
- Targeted
xpu-smi diag -d <id> -l 1 and bounded
xpu-smi stats -d <id> complete or leave inspectable warning
artifacts.
/dev/dri/renderD* exists and permissions are understandable.- Docker daemon is reachable by the current user.
/dev/shm and disk space are not obviously too small.- If
--image is supplied, the selected container sees XPU through a
Level Zero or Python XPU visibility probe. The default Python probe
requires torch.xpu.is_available() and a nonzero XPU device count.
Warnings do not block every workflow. A missing proxy is fine on direct
networks; missing BuildKit is fine unless the next step builds an image;
a workstation xpu-smi diag permission warning may still allow GPU work
if the computation sub-test passes.
Result Routing
Use the generated SUMMARY.md as the source of truth for failure-to-next
skill routing. The script builds that section from the checks it actually
ran, so do not maintain a separate static routing table in this skill.
For final answers, read status.tsv or the SUMMARY.md status table,
then report hard blockers first and follow the SUMMARY.md "Next Skill
Routing" section for the recommended handoff.
SUMMARY.md includes a Verdict field:
READY when no checks fail or warn.READY WITH WARNINGS when no checks fail but at least one warning is
present.BLOCKED when any check fails.
When blocked, SUMMARY.md also includes First blocker: with the
first failing check from status.tsv.
Image Preflight Notes
The script refuses to implicitly pull an image. If --image is not
already local, verify host/Docker/container proxy settings or run the
skill that owns the image choice.
The generic image preflight sources oneAPI (if present) and then runs
the XPU visibility probe against whatever python3 is on the image's
PATH. It does not activate conda, miniforge, or any other Python
environment — that is the image's responsibility:
source /opt/intel/oneapi/setvars.sh --force
If the image needs a conda/venv activation, a non-default oneAPI path,
or any other setup before python3 -c "import torch" works, pass
--image-command '<shell command>' to supply the full probe.
Image preflight uses Docker bridge networking by default. This avoids
masking container-network issues with host networking. If the target
runtime will intentionally use another Docker network mode, pass
--image-network <mode> so the preflight matches that run.
Reporting
In final answers, report:
- target host and GPU ID
- verdict
- PASS/WARN/FAIL counts
- first blocker and hard blockers
- the next skill to use for each blocker
- the output artifact paths
Do not claim container readiness from host checks alone when the next
step uses a container image; run the optional --image preflight for
that image.
