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/aiopshwang/data-analysis-ml-agent-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/aiopshwang/data-analysis-ml-agent-skills/data-analysis-ml-agent-skills)<a href="https://agentmods.dev/plugins/aiopshwang/data-analysis-ml-agent-skills/data-analysis-ml-agent-skills"><img src="https://agentmods.dev/badge/plugins/aiopshwang/data-analysis-ml-agent-skills/data-analysis-ml-agent-skills.svg" alt="Measured on agentmods" height="20"></a>Grade A, and why
data-analysis-ml-agent-skills 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 8d 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
{
"$schema": "https://json.schemastore.org/claude-code-plugin-manifest.json",
"name": "data-analysis-ml-agent-skills",
"displayName": "Decision-Grade Data Science",
"version": "0.2.0",
"description": "Evidence-first AI agent skills for reliable data analysis, machine learning, and reproducible model validation.",
"author": { "name": "aiopshwang", "url": "https://github.com/aiopshwang" },
"homepage": "https://github.com/aiopshwang/data-analysis-ml-agent-skills#readme",
"repository": "https://github.com/aiopshwang/data-analysis-ml-agent-skills",
"license": "MIT",
"keywords": ["agent-skills", "data-analysis", "data-science", "machine-learning", "data-quality", "model-validation", "reproducibility"],
"skills": "./skills/"
}
What it installs
The manifest is a name and a version. 7 skills travel with it, and installing the plugin installs all of them — 418 tokens a session between them. Each is measured on its own page, and each can be installed alone.
- Skill shipping-reproducible-results A 62 tokens
- Skill designing-leakage-safe-experiments A 59 tokens
- Skill diagnosing-ml-failures A 65 tokens
- Skill running-decision-grade-data-science A 61 tokens
- Skill validating-models-and-claims A 58 tokens
- Skill auditing-data-and-ground-truth A 60 tokens
- Skill using-data-analysis A 53 tokens
What ships with it
1 file beside plugin.json in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 8d ago First seen · 14 lines scan A 821816aefa7c
data-analysis-ml-agent-skills is a plugin published in the GitHub repository aiopshwang/data-analysis-ml-agent-skills (12 stars, last pushed 11d ago), licensed MIT. 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 2026-08-31.
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