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 fabric-testbed/claude-plugin-marketplace --skill fabric-gpugit clone --depth 1 https://github.com/fabric-testbed/claude-plugin-marketplaceWrote 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/fabric-testbed/claude-plugin-marketplace/fabric-gpu)<a href="https://agentmods.dev/skills/fabric-testbed/claude-plugin-marketplace/fabric-gpu"><img src="https://agentmods.dev/badge/skills/fabric-testbed/claude-plugin-marketplace/fabric-gpu/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/fabric-testbed/claude-plugin-marketplace/fabric-gpu"><img src="https://agentmods.dev/badge/skills/fabric-testbed/claude-plugin-marketplace/fabric-gpu.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 | $0.00016 | $0.01628 |
| Opus 5 | $0.00008 | $0.00814 |
| Sonnet 5 | $0.00003 | $0.00326 |
| Haiku 4.5 | $0.00002 | $0.00163 |
Grade B, and why
fabric-gpu scanned grade B with 2 findings 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 10d 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.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
stdout, stderr = node.execute("sudo apt-get install -y -q pciutils && lspci | grep -i 'nvidia\\|3d controller'") Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
f"wget https://developer.download.nvidia.com/compute/cuda/repos/{distro}/{architecture}/cuda-keyring_1.1-1_all.deb", How it starts
The opening of the file, as written. The whole thing — 243 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Instructions
When invoked, generate code to provision a FABRIC node with GPU(s) and install drivers. The workflow is:
- Find a site with available GPUs
- Create a slice with a GPU node
- Submit and wait for the slice
- Install NVIDIA/CUDA drivers
- Reboot and verify with
nvidia-smi
Ask the user which GPU type they need and whether they need CUDA toolkit.
API Reference
Available GPU Models
| Model String | GPU | Filter Field |
|---|---|---|
GPU_TeslaT4 |
NVIDIA Tesla T4 | tesla_t4_available |
GPU_RTX6000 |
NVIDIA RTX 6000 | rtx6000_available |
GPU_A30 |
NVIDIA A30 | a30_available |
GPU_A40 |
NVIDIA A40 | a40_available |
Available FPGA Models
| Model String | FPGA | Filter Field |
|---|---|---|
FPGA_Xilinx_U280 |
Xilinx Alveo U280 | fpga_u280_available |
FPGA_Xilinx_SN1022 |
Xilinx SN1022 | fpga_sn1022_available |
Finding GPU Sites
fablib.get_random_site(
filter_function=lambda x: x["rtx6000_available"] > 0
)
Adding GPU to Node
node.add_component(model="GPU_RTX6000", name="gpu1")
Patterns
Complete GPU Node with CUDA Driver Install
from fabrictestbed_extensions.fablib.fablib import FablibManager
fablib = FablibManager()
# Step 1: Find a site with the desired GPU
GPU_MODEL = "GPU_RTX6000"
GPU_FILTER_FIELD = "rtx6000_available"
site = fablib.get_random_site(
filter_function=lambda x: x[GPU_FILTER_FIELD] > 0
)
print(f"Selected site: {site}")
# Step 2: Create slice
slice = fablib.new_slice(name="gpu-experiment")
node = slice.add_node(
name="gpu-node",
site=site,
cores=8,
ram=32,
disk=100,
image="default_ubuntu_22",
)
node.add_component(model=GPU_MODEL, name="gpu1")
# Step 3: Submit
slice.submit()
print("Slice is ready!")
# Step 4: Install NVIDIA CUDA drivers
node = slice.get_node(name="gpu-node")
# Verify GPU PCI device is visible
stdout, stderr = node.execute("sudo apt-get install -y -q pciutils && lspci | grep -i 'nvidia\\|3d controller'")
print(stdout)
# Install prerequisites
commands = [
"sudo apt-get -q update",
"sudo apt-get -q install -y linux-headers-$(uname -r) gcc",
]
for cmd in commands:
node.execute(cmd)
# Install CUDA (adjust distro/version as needed)
distro = "ubuntu2204"
version = "12.6"
architecture = "x86_64"
commands = [
f"wget https://developer.download.nvidia.com/compute/cuda/repos/{distro}/{architecture}/cuda-keyring_1.1-1_all.deb",
"sudo dpkg -i cuda-keyring_1.1-1_all.deb",
"sudo apt-get -q update",
f"sudo apt-get -q install -y cuda-{version.replace('.', '-')}",
]
for cmd in commands:
stdout, stderr = node.execute(cmd)
# Step 5: Reboot to load driver
node.execute("sudo reboot")
# Wait for node to come back
slice.wait_ssh(timeout=360, interval=10, progress=True)
slice.update()
slice.test_ssh()
# Step 6: Verify
stdout, stderr = node.execute("nvidia-smi")
print(stdout)
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.
- 10d ago First seen · 243 lines · 16 tokens per session scan B db369e629954
fabric-gpu is a skill published in the GitHub repository fabric-testbed/claude-plugin-marketplace (2 stars, last pushed 6mo ago), licensed Apache-2.0. It adds 16 tokens to every session and 1,628 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it B with 2 findings (asks for root, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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