Intel GPU AI Skills is a collection of agent skills for setting up, running, benchmarking, and profiling Hugging Face models on Intel GPUs. It supports workflows involving PyTorch, vLLM-XPU, SGLang-XPU, llama.cpp-SYCL, and migration from CUDA to XPU. The catalogue contains the project's skills, instructions, agent, and plugin.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add intel/gpu-ai-skills --skill enable-xpu-monitoringgit clone --depth 1 https://github.com/intel/gpu-ai-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/intel/gpu-ai-skills/enable-xpu-monitoring)<a href="https://agentmods.dev/skills/intel/gpu-ai-skills/enable-xpu-monitoring"><img src="https://agentmods.dev/badge/skills/intel/gpu-ai-skills/enable-xpu-monitoring/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/intel/gpu-ai-skills/enable-xpu-monitoring"><img src="https://agentmods.dev/badge/skills/intel/gpu-ai-skills/enable-xpu-monitoring.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00083 | $0.02295 |
| Opus 5.5 | $0.00033 | $0.00918 |
| Sonnet 5.5 | $0.00017 | $0.00459 |
| Haiku 4.5 | $0.00008 | $0.00230 |
Grade A, and why
enable-xpu-monitoring scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s http://localhost:9090/-/healthy # Prometheus healthy How it starts
The opening of the file, as written. The whole thing — 219 lines — stays where its author put it; the contents beside it link to each section on GitHub.
enable-xpu-monitoring
Deploy a single-node monitoring stack on an Intel GPU host from
intel/xe-full-stack-monitoring.
The stack is pure Docker Compose — no CLI, no Python package, no tarball.
That repo's AGENT.md
is the source of truth; this skill gives the short path and defers detail to it.
What gets deployed
| Container | Port | Purpose |
|---|---|---|
xpumd (XPU Manager v2.0) |
9471 | GPU hardware metrics via Level Zero |
node-exporter |
9100 | CPU, RAM, disk, network |
intel-xpu-prometheus |
9090 | Scrapes xpumd, node, and vLLM |
intel-xpu-grafana |
3000 | 4 dashboards: Quickview, GPU, vLLM, System |
All listeners bind to 127.0.0.1. Grafana has no login (anonymous, read-only Viewer).
Step 1 — Preflight
ls /dev/dri/renderD* >/dev/null 2>&1 && echo "[OK] GPU render nodes" || echo "[FAIL] no render nodes"
docker info >/dev/null 2>&1 && echo "[OK] docker" || echo "[FAIL] docker not reachable"
docker compose version >/dev/null 2>&1 && echo "[OK] compose" || echo "[FAIL] compose plugin missing"
for p in 9471 9100 9090 3000; do
(ss -ltn 2>/dev/null || netstat -ltn) | grep -q ":$p " && echo "port $p IN USE" || echo "port $p free"
done
Fix any [FAIL]. Ports held by a previous run of this same stack are fine.
If 9471, 9100 or 9090 is held by anything else, it must be freed; those ports cannot be changed.
If port 3000 is held by another app, do not stop that app. Move Grafana to a free port instead:
GRAFANA_PORT=3000
if (ss -ltn 2>/dev/null || netstat -ltn) | grep -q ":3000 " \
&& ! docker ps --format '{{.Names}}' | grep -qx intel-xpu-grafana; then
for p in $(seq 3001 3099); do
(ss -ltn 2>/dev/null || netstat -ltn) | grep -q ":$p " || { GRAFANA_PORT=$p; break; }
done
fi
echo "Grafana port: $GRAFANA_PORT"
If GRAFANA_PORT is not 3000, tell the user clearly:
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 219 lines · 83 tokens per session scan A 6183c6aa4f77
enable-xpu-monitoring is a skill published in the GitHub repository intel/gpu-ai-skills (39 stars, last pushed yesterday), licensed Apache-2.0. It adds 83 tokens to every session and 2,295 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-13.
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