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.
/plugin marketplace add xbim08/awesome-claude-code-pluginsnpx agentmods add plugins/xbim08/awesome-claude-code-plugins/ai-engineergit clone --depth 1 https://github.com/xbim08/awesome-claude-code-pluginsGrade A, and why
ai-engineer 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 2d 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.
This is a copy
100% identical to ai-engineer — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
{
"name": "ai-engineer",
"description": "Use this agent when implementing AI/ML features, integrating language models, building recommendation systems, or adding intelligent automation to applications. This agent specializes in practical AI implementation for rapid deployment. Examples:\\n\\n<example>\\nContext: Adding AI features to an app\\nuser: \"We need AI-powered content recommendations\"\\nassistant: \"I'll implement a smart recommendation engine. Let me use the ai-engineer agent to build an ML pipeline that learns from user behavior.\"\\n<commentary>\\nRecommendation systems require careful ML implementation and continuous learning capabilities.\\n</commentary>\\n</example>\\n\\n<example>\\nContext: Integrating language models\\nuser: \"Add an AI chatbot to help users navigate our app\"\\nassistant: \"I'll integrate a conversational AI assistant. Let me use the ai-engineer agent to implement proper prompt engineering and response handling.\"\\n<commentary>\\nLLM integration requires expertise in prompt design, token management, and response streaming.\\n</commentary>\\n</example>\\n\\n<example>\\nContext: Implementing computer vision features\\nuser: \"Users should be able to search products by taking a photo\"\\nassistant: \"I'll implement visual search using computer vision. Let me use the ai-engineer agent to integrate image recognition and similarity matching.\"\\n<commentary>\\nComputer vision features require efficient processing and accurate model selection.\\n</commentary>\\n</example>",
"version": "1.0.0",
"author": {
"name": "Michael Galpert"
},
"homepage": "https://github.com/ccplugins/awesome-claude-code-plugins/tree/main/plugins/ai-engineer"
}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.
- 2d ago First seen · 9 lines scan A 2b291cd87774
ai-engineer is a plugin published in the GitHub repository xbim08/awesome-claude-code-plugins (10 stars, last pushed 2d 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. It is 100% identical to ai-engineer, differing in 0 lines, and is treated as a copy.
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