sample-sagemaker-agentic-model-deployment: Instructions file for Codex

AGENTS.md

sample-sagemaker-agentic-model-deployment AGENTS.md is an instructions file for Codex, OpenCode from aws-samples/sample-sagemaker-agentic-model-deployment. It costs 8 tokens per session, scanned A, original, MIT-0.

Project-specific instructions for deploying and benchmarking open-weight AI models on Amazon SageMaker, AWS’s managed machine-learning platform.

In plain words
What is it for?
Use them when working on the sample-sagemaker-agentic-model-deployment project.
Why use it?
They give agents the rules for handling staging, deployment, testing, and optimization in that repository.

Instructions file for CodexOpenCode ✓ vendor

Written for Codex and OpenCode: the file is AGENTS.md.

This is aws-samples/sample-sagemaker-agentic-model-deployment's own configuration. It tells Codex and OpenCode how to work on sample-sagemaker-agentic-model-deployment itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything sample-sagemaker-agentic-model-deployment configures →

About the project

sample-sagemaker-agentic-model-deployment is a coding-agent workflow that takes an open-weight model from a public checkpoint to a deployed, benchmarked, and optimized endpoint on Amazon SageMaker AI. It is for automating model staging, serving-configuration selection, deployment, benchmarking, and optimization without manually writing the surrounding API and polling code. Its skills and instruction define the portable agent workflow.

aws-samples/sample-sagemaker-agentic-model-deployment · 5 stars · on GitHub

Reuse

Borrowing it

Nothing to install: this file belongs to aws-samples/sample-sagemaker-agentic-model-deployment. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/aws-samples/sample-sagemaker-agentic-model-deployment/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/aws-samples/sample-sagemaker-agentic-model-deployment

Made for: Codex, OpenCode.

Wrote 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.

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README.md
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Your own site
<a href="https://agentmods.dev/instructions/aws-samples/sample-sagemaker-agentic-model-deployment/agents-md"><img src="https://agentmods.dev/badge/instructions/aws-samples/sample-sagemaker-agentic-model-deployment/agents-md/github.svg" alt="Measured on agentmods" height="20"></a>

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Your own site · 80×15
<a href="https://agentmods.dev/instructions/aws-samples/sample-sagemaker-agentic-model-deployment/agents-md"><img src="https://agentmods.dev/badge/instructions/aws-samples/sample-sagemaker-agentic-model-deployment/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 8 This file is loaded in full into every session.
When invoked 8 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00008 $0.00008
Opus 5.5 $0.00003 $0.00003
Sonnet 5.5 $0.00002 $0.00002
Haiku 4.5 $0.00001 $0.00001

Measured 2mo ago against content hash 0b99eee90295, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

sample-sagemaker-agentic-model-deployment AGENTS.md 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 2mo 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.

AGENTS.md · 1 lines

The source is not reproduced here

Licensed MIT-0

The repository is licensed MIT-0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.

Read it on GitHub

Changes

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.

  1. 2mo ago First seen · 1 lines · 8 tokens per session scan A 0b99eee90295

Subscribe to this mod's changes

sample-sagemaker-agentic-model-deployment AGENTS.md is an instructions file published in the GitHub repository aws-samples/sample-sagemaker-agentic-model-deployment (5 stars, last pushed 3mo ago), licensed MIT-0. It adds 8 tokens to every session, about $0.0000 per session on Opus 5.5. 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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