awslabs/agent-plugins is a collection of plugins, skills, instructions, an MCP server, a hook, and a setting that guide AI coding agents in architecting, deploying, and operating software on Amazon Web Services. It is for developers using coding agents such as Claude Code, Codex, and Cursor with AWS projects. The catalogue entries are the repository's own agent workflows and supporting components.
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/awslabs/agent-pluginsWrote 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/awslabs/agent-plugins/sagemaker-ai)<a href="https://agentmods.dev/plugins/awslabs/agent-plugins/sagemaker-ai"><img src="https://agentmods.dev/badge/plugins/awslabs/agent-plugins/sagemaker-ai/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/awslabs/agent-plugins/sagemaker-ai"><img src="https://agentmods.dev/badge/plugins/awslabs/agent-plugins/sagemaker-ai.svg" alt="Reviewed on agentmods" width="80" height="20"></a>Grade A, and why
sagemaker-ai 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
{
"author": {
"name": "Amazon Web Services"
},
"description": "Build, train, and deploy AI models with deep AWS AI/ML expertise brought directly into your coding assistants, covering the surface area of Amazon SageMaker AI.",
"homepage": "https://github.com/awslabs/agent-plugins",
"keywords": [
"sagemaker",
"machine-learning",
"generative-ai",
"fine-tuning",
"training",
"deployment",
"inference",
"mlops",
"aws"
],
"license": "Apache-2.0",
"name": "sagemaker-ai",
"repository": "https://github.com/awslabs/agent-plugins",
"version": "1.3.0"
}
What it installs
The manifest is a name and a version. 19 skills travel with it, and installing the plugin installs all of them — 1,935 tokens a session between them. Each is measured on its own page, and each can be installed alone.
- Skill hyperpod-node-debugger A 139 tokens
- Skill dataset-transformation A 110 tokens
- Skill hyperpod-cluster-debugger A 80 tokens
- Skill hyperpod-nccl A 150 tokens
- Skill hyperpod-performance-debugger A 133 tokens
- Skill hyperpod-slurm-debugger A 162 tokens
- Skill planning A 115 tokens
- Skill dataset-evaluation A 93 tokens
- Skill use-case-specification A 85 tokens
- Skill hyperpod-issue-report A 99 tokens
- Skill hyperpod-version-checker A 120 tokens
- Skill model-selection A 98 tokens
- Skill finetuning-technique A 87 tokens
- Skill directory-management A 62 tokens
- Skill finetuning A 85 tokens
- Skill model-deployment A 76 tokens
- Skill model-evaluation A 65 tokens
- Skill sdk-getting-started A 71 tokens
- Skill hyperpod-ssm B 105 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 · 23 lines scan A e37dbce79fcc
sagemaker-ai is a plugin published in the GitHub repository awslabs/agent-plugins (921 stars, last pushed today), 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 2026-08-30.
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