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.
git clone --depth 1 https://github.com/neuromechanist/research-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/plugins/neuromechanist/research-skills/ml-training)<a href="https://agentmods.dev/plugins/neuromechanist/research-skills/ml-training"><img src="https://agentmods.dev/badge/plugins/neuromechanist/research-skills/ml-training/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/plugins/neuromechanist/research-skills/ml-training"><img src="https://agentmods.dev/badge/plugins/neuromechanist/research-skills/ml-training.svg" alt="Reviewed on agentmods" width="80" height="20"></a>Grade A, and why
ml-training scanned grade A with 0 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 9d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
{
"name": "ml-training",
"version": "0.1.0",
"description": "Machine-learning training and benchmarking on rented cloud GPUs: prebaked RunPod images that boot in seconds instead of minutes, pod lifecycle scripts, GPU selection and pricing ladders, and the provisioning pitfall catalog",
"author": {
"name": "Seyed Yahya Shirazi",
"email": "[email protected]"
},
"license": "BSD-3-Clause",
"skills": "./skills/",
"keywords": [
"runpod",
"gpu",
"cloud-gpu",
"cuda",
"docker",
"provisioning",
"training",
"benchmarking",
"inference",
"cost-control",
"ssh"
]
}
What it installs
The manifest is a name and a version. 1 skill travel with it, and installing the plugin installs all of them — 176 tokens a session between them. Each is measured on its own page, and each can be installed alone.
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.
- 9d ago First seen · 25 lines scan A 278bda4dd545
ml-training is a plugin published in the GitHub repository neuromechanist/research-skills (45 stars, last pushed 6d ago), licensed BSD-3-Clause. Its token cost is not measured: this kind of file is read by the harness, not the model. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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