hf-cloud-sagemaker-production-defaults agent skill by huggingface

At a glance

Before you install

Read from the skill's files at the directory's October 19, 2026 snapshot: what ships with it, what its code reads, and the terms it is published under.

• Bundled scripts: 6 script files (6 Python). Your agent may run them, so read them first.
• Network: its scripts use an HTTP client or a cloud SDK.
• License: Apache-2.0, an open-source or open-content license.

Install hf-cloud-sagemaker-production-defaults

The skills CLI works with Claude Code, Codex, Cursor and other agents; the other routes copy the folder by hand.

npx skills add https://github.com/huggingface/skills/tree/main/skills/hf-cloud-sagemaker-production-defaults

tmp="$(mktemp -d)"
git clone --depth 1 https://github.com/huggingface/skills.git "$tmp/repo"
mkdir -p .claude/skills
cp -R "$tmp/repo/"skills/hf-cloud-sagemaker-production-defaults .claude/skills/
rm -rf "$tmp"

python3 ~/.codex/skills/.system/skill-installer/scripts/install-skill-from-github.py \
    --repo huggingface/skills \
    --path skills/hf-cloud-sagemaker-production-defaults

huggingface/skills is third-party code. Read SKILL.md and any bundled scripts before you install it.

How the author describes it

Create a SageMaker endpoint (real-time, real-time scale-to-zero, or async) with autoscaling, CloudWatch alarms, and tagging enabled by default. Use this skill whenever about to create a SageMaker endpoint, write deployment code that calls `create_endpoint`, or finalize a deployment after the image URI and IAM role are known. Provides deploy.py for real-time endpoints, deploy_ic.py for real-time endpoints that scale to zero instances via inference components, and deploy_async.py for async endpoints (also scale-to-zero). This is the last step in the SageMaker deployment workflow. Never generate a bare `create_endpoint` call without these defaults — endpoints without autoscaling or alarms are demos, not deployments.

From the description field of SKILL.md. Agents read this line to decide when to load the skill.

Sections in SKILL.md

• What gets created
• Running the deployment
• InService is not success — smoke-test before declaring victory
• Testing a real-time endpoint
• The UTF-8 BOM gotcha (Windows)
• Invoking a generative reranker (vLLM)
• Picking the image URI
• Scale to zero for real-time endpoints
• How it differs from deploy.py
• Measured behaviour
• Sizing the component
• Invoking and testing
• Teardown order
• Async inference deployments
• How scale-to-zero works
• Async alarms

Files in the skill folder

• SKILL.md
• references/deployment-template.md
• scripts/_common.py
• scripts/deploy.py
• scripts/deploy_async.py
• scripts/deploy_ic.py
• scripts/invoke_endpoint.py
• scripts/teardown.py

Suede Skill Check: 80/100 · B

hf-cloud-sagemaker-production-defaults passes the required frontmatter check and all seven graded checks, which cover the SKILL.md format, a declared license and a commit in the last year. Those checks earn 56 of the score’s points; the rest come from description quality, instruction depth, bundled files, maintenance and curated-list citations. How the score works.

Where this skill is cited

huggingface/skills appears in 2 curated lists: heilcheng/awesome-agent-skills, skillmatic-ai/awesome-agent-skills.

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