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/Aznatkoiny/zAI-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/aznatkoiny/zai-skills/ai-toolkit)<a href="https://agentmods.dev/plugins/aznatkoiny/zai-skills/ai-toolkit"><img src="https://agentmods.dev/badge/plugins/aznatkoiny/zai-skills/ai-toolkit/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/aznatkoiny/zai-skills/ai-toolkit"><img src="https://agentmods.dev/badge/plugins/aznatkoiny/zai-skills/ai-toolkit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>Grade A, and why
ai-toolkit 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": "ai-toolkit",
"version": "2.4.0",
"description": "Skills for Deep Learning (Keras 3), Reinforcement Learning (Python & C++), Claude Prompt Optimization, x402 Web3 Payments, and OpenClaw Setup.",
"author": {
"name": "Antony Zaki"
},
"homepage": "https://github.com/Aznatkoiny/zAI-Skills",
"repository": "https://github.com/Aznatkoiny/zAI-Skills",
"license": "MIT",
"keywords": [
"deep-learning",
"reinforcement-learning",
"prompt-engineering",
"x402",
"keras",
"pytorch",
"gymnasium",
"web3",
"machine-learning",
"openclaw"
]
}
What it installs
The manifest is a name and a version. 6 skills, 4 commands, 2 agents travel with it, and installing the plugin installs all of them — 1,613 tokens a session between them. Each is measured on its own page, and each can be installed alone.
- Skill openclaw-setup A 188 tokens
- Skill reinforcement-learning A 86 tokens
- Skill x402-payments A 185 tokens
- Skill cpp-reinforcement-learning A 83 tokens
- Skill deep-learning A 91 tokens
- Skill prompt-optimizer A 205 tokens
- Command openclaw-audit A 38 tokens
- Command rl-new-project A 35 tokens
- Command optimize-prompt A 27 tokens
- Command x402-scaffold A 29 tokens
- Agent rl-debugger A 312 tokens
- Agent prompt-rewriter A 334 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 · 24 lines scan A d6239f8cdcd7
ai-toolkit is a plugin published in the GitHub repository Aznatkoiny/zAI-Skills (10 stars, last pushed 2mo 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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