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/yeaight7/agent-powerupsWrote 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/yeaight7/agent-powerups/machine-learning-ops)<a href="https://agentmods.dev/plugins/yeaight7/agent-powerups/machine-learning-ops"><img src="https://agentmods.dev/badge/plugins/yeaight7/agent-powerups/machine-learning-ops/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/yeaight7/agent-powerups/machine-learning-ops"><img src="https://agentmods.dev/badge/plugins/yeaight7/agent-powerups/machine-learning-ops.svg" alt="Reviewed on agentmods" width="80" height="20"></a>Grade A, and why
machine-learning-ops 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 1mo 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": "machine-learning-ops",
"version": "0.6.3",
"description": "ML pipeline design, experiment tracking, model evaluation, training debugging, and reproducibility.",
"author": {
"name": "Javier Rivero Iglesias",
"email": "[email protected]"
},
"homepage": "https://github.com/yeaight7/agent-powerups#readme",
"repository": "https://github.com/yeaight7/agent-powerups",
"license": "Apache-2.0",
"keywords": ["machine-learning", "mlops", "experiment-tracking", "model-evaluation", "pipelines"],
"maturity": "beta"
}
What it installs
The manifest is a name and a version. 7 skills, 4 commands, 3 agents travel with it, and installing the plugin installs all of them — 410 tokens a session between them. Each is measured on its own page, and each can be installed alone.
- Skill baseline-comparison-review A 39 tokens
- Skill dataset-split-review A 39 tokens
- Skill experiment-tracking-review A 38 tokens
- Skill ml-leakage-check A 40 tokens
- Skill model-evaluation-reporting A 38 tokens
- Skill reproducible-training-runs A 44 tokens
- Skill training-pipeline-debugging A 42 tokens
- Command evaluation-report A 20 tokens
- Command experiment-preflight A 21 tokens
- Command leakage-check A 10 tokens
- Command ml-run-review A 0 tokens
- Agent leakage-auditor A 26 tokens
- Agent ml-experiment-reviewer A 24 tokens
- Agent training-pipeline-debugger A 29 tokens
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.
- 1mo ago First seen · 15 lines scan A 0bf2559a7821
machine-learning-ops is a plugin published in the GitHub repository yeaight7/agent-powerups (6 stars, last pushed 19d ago), licensed Apache-2.0. 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 2026-09-14.
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