Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add fabric-testbed/claude-plugin-marketplace/plugin install fablibWrote 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-perfsonar)<a href="https://agentmods.dev/skills/fabric-testbed/claude-plugin-marketplace/fabric-perfsonar"><img src="https://agentmods.dev/badge/skills/fabric-testbed/claude-plugin-marketplace/fabric-perfsonar/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-perfsonar"><img src="https://agentmods.dev/badge/skills/fabric-testbed/claude-plugin-marketplace/fabric-perfsonar.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 | $0.00024 | $0.01958 |
| Opus 5.5 | $0.00010 | $0.00783 |
| Sonnet 5.5 | $0.00005 | $0.00392 |
| Haiku 4.5 | $0.00002 | $0.00196 |
Grade B, and why
fabric-perfsonar scanned grade B 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 2mo 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.
node.execute(f'sudo sh -c \'echo "{etc_hosts}" >> /etc/hosts\'') How it starts
The opening of the file, as written. The whole thing — 248 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Instructions
When invoked, generate code to set up perfSONAR network monitoring on FABRIC nodes. perfSONAR measures network performance metrics including throughput, latency, RTT, MTU, and traceroute between endpoints.
Deployment options:
- Docker Testpoint — Lightweight container-based deployment
- Native Install with perfsonar-extensions — Full stack with pSConfig, Grafana, and archive (recommended)
- Ad-Hoc Tests — Quick one-off measurements with pScheduler
Guide the user on which deployment model to use and what tests to configure.
API Reference
perfSONAR Test Types
| Test Type | Tool | Measures |
|---|---|---|
| throughput | iperf3 |
Bandwidth between endpoints |
| latency / latencybg | owamp |
One-way delay |
| rtt | ping |
Round-trip time |
| trace | traceroute/tracepath |
Network path |
| disk-to-disk | nuttcp |
Disk-to-disk transfer rate |
pSConfig Mesh Configuration
perfSONAR tests are coordinated via pSConfig (perfSONAR Configuration) mesh files that define which nodes test to which others and what tests to run. The psconfig_builder.py tool from perfsonar-extensions generates these configurations.
Patterns
Full Stack perfSONAR with perfsonar-extensions (Recommended)
from fabrictestbed_extensions.fablib.fablib import FablibManager
fablib = FablibManager()
TOTAL_NODES = 2
slice_name = "perfsonar-monitoring"
sites = fablib.get_random_sites(TOTAL_NODES)
slice = fablib.new_slice(name=slice_name)
for i, s in enumerate(sites):
prefix = "central" if i == 0 else "remote"
net = slice.add_l3network(name=f"{s}-l3", type="IPv4")
node = slice.add_node(
name=f"{prefix}-{s}",
site=s,
image="default_ubuntu_24",
cores=16,
ram=32,
disk=100,
)
iface = node.add_component(model="NIC_Basic", name="nic1").get_interfaces()[0]
iface.set_mode('auto')
net.add_interface(iface)
node.add_route(subnet=fablib.FABNETV4_SUBNET, next_hop=net.get_gateway())
slice.submit()
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.
- 2mo ago First seen · 248 lines · 24 tokens per session scan B 382afd3c7d41
fabric-perfsonar is a skill published in the GitHub repository fabric-testbed/claude-plugin-marketplace (2 stars, last pushed 8mo ago), licensed Apache-2.0. It adds 24 tokens to every session and 1,958 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it B with 1 finding (asks for root). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
fabric-perfsonar compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| fabric-perfsonarfabric-testbed/claude-plugin-marketplace | Skill | 2 | 8mo ago | Apache-2.0 | B | 24 | Claude Code |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |