Official agent skill

Hyperpod Ssm

by awslabs in awslabs/agent-plugins

Remote command execution and file transfer on SageMaker HyperPod cluster nodes via AWS Systems Manager (SSM).

OfficialApache-2.0Auto-check: notesAI & LLM Engineering

Install Hyperpod Ssm

skills CLI
$ npx skills add awslabs/agent-plugins --skill hyperpod-ssm -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install awslabs/agent-plugins hyperpod-ssm --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/awslabs/agent-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/sagemaker-ai/skills/hyperpod-ssm .claude/skills/hyperpod-ssm && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
hyperpod-ssm
GitHub stars
915
Used in
1 other repo
Token cost
~1.3k tokens
SKILL.md length
353 words
Files
5 (incl. scripts, references)
Skills in repo
33
Repo updated
First seen
Licence
Apache-2.0

At a glance

Remote command execution and file transfer on SageMaker HyperPod cluster nodes via AWS Systems Manager (SSM).

  • User request needs to execute commands on cluster nodes
  • SKILL.md covers Prerequisites, SSM Target Format, Scripts and Running Commands Across Many…, plus 3 more sections
  • Runs Shell scripts from its folder; calls aws, yum and apt
  • Upload files to nodes

What it does

Hyperpod Ssm is an agent skill from awslabs/agent-plugins, published by the product's own GitHub organization. Remote command execution and file transfer on SageMaker HyperPod cluster nodes via AWS Systems Manager (SSM). This is the primary interface for accessing HyperPod nodes — direct SSH is not available. Use when any skill, workflow, or user request needs to execute commands on cluster nodes, upload files to nodes, read/download files from nodes, run diagnostics, install packages, or perform any operation requiring shell access to HyperPod instances. Other HyperPod skills depend on this skill for all node-level…

Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts and reference files (for example `references/troubleshooting.md`, `scripts/get-cluster-info.sh` and `scripts/list-nodes.sh`).

It sits in AI & LLM Engineering. It works with Amazon Web Services and Amazon SageMaker. The repository describes itself as: Agent Plugins for AWS equip AI coding agents with the skills to help you architect, deploy, and operate on AWS. The licence is Apache-2.0.

When your agent uses it

  • User request needs to execute commands on cluster nodes
  • Upload files to nodes
  • Read/download files from nodes
  • Run diagnostics

Example prompts

  • “/hyperpod-ssm”

Requirements

  • A Bash shell

What it can do on your machine

Read from SKILL.md and the folder at commit da51970. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 3 files in scripts/ (Shell), which the agent can run.

    Shell commands in SKILL.md call:

    • aws
    • yum
    • apt
    • brew
    • bash

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use aws, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Hyperpod Ssm loads about 1.3k tokens when it runs, and up to ~1.8k if it reads all its reference files. Until then it costs about 134 tokens; SKILL.md has 353 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~134
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NoteRuns commands with sudoSKILL.md:15
    even when the command ran. Install with `sudo yum install expect`, `sudo apt install expect`, or `brew install expect`.
  • NoteRuns commands with sudoSKILL.md:96
    | CloudWatch agent | `sudo systemctl status amazon-cloudwatch-agent`                |

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from awslabs/agent-plugins at commit da51970, republished under its Apache-2.0 licence (© awslabs). 353 words, ~1,293 tokens.

Download SKILL.mdSave it as .claude/skills/hyperpod-ssm/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
hyperpod-ssm
description
Remote command execution and file transfer on SageMaker HyperPod cluster nodes via AWS Systems Manager (SSM). This is the primary interface for accessing HyperPod nodes — direct SSH is not available. Use when any skill, workflow, or user request needs to execute commands on cluster nodes, upload files to nodes, read/download files from nodes, run diagnostics, install packages, or perform any operation requiring shell access to HyperPod instances. Other HyperPod skills depend on this skill for all node-level operations.
metadata.version
1.0.0

HyperPod SSM Access

Prerequisites

  • aws CLI v2, authenticated for the target account/Region.
  • session-manager-plugin — installed alongside the AWS CLI.
  • jq — the scripts build JSON payloads with it.
  • unbuffer (from the expect package) — wraps aws ssm start-session with a PTY so the session-manager-plugin flushes stdout instead of racing to close. Without it, calls intermittently return empty output with Cannot perform start session: EOF even when the command ran. Install with sudo yum install expect, sudo apt install expect, or brew install expect. ssm-exec.sh detects and uses it automatically; falls back with a warning if missing.

SSM Target Format

Target: sagemaker-cluster:<CLUSTER_ID>_<GROUP_NAME>-<INSTANCE_ID>

  • CLUSTER_ID: Last segment of cluster ARN (NOT the cluster name). Extract via get-cluster-info.sh.
  • GROUP_NAME: Instance group name — retrieve via list-nodes.sh.
  • INSTANCE_ID: EC2 instance ID (e.g., i-0123456789abcdef0)

Scripts

Three scripts under scripts/. Resolve cluster info and nodes once, then execute per node.

get-cluster-info.sh — Resolve cluster name → ID (call once)
bash
scripts/get-cluster-info.sh CLUSTER_NAME [--region REGION]
# Output: {"cluster_id":"...","cluster_arn":"...","cluster_name":"...","region":"..."}
list-nodes.sh — List all nodes with pagination (call once)
bash
scripts/list-nodes.sh CLUSTER_NAME [--region REGION] [--instance-group GROUP] [--instance-id ID]
# Output: JSON array of ClusterNodeSummaries (InstanceId, InstanceGroupName, InstanceStatus, etc.)

list-cluster-nodes paginates at 100 nodes. This script handles pagination automatically.

ssm-exec.sh — Execute command on a node (call per node)
bash
# Execute — with pre-built target
scripts/ssm-exec.sh --target "sagemaker-cluster:CLUSTERID_GROUP-INSTANCEID" 'command' [--region REGION]

# Execute — with parts
scripts/ssm-exec.sh --cluster-id ID --group GROUP --instance-id INSTANCE_ID 'command' [--region REGION]

# Upload
scripts/ssm-exec.sh --target TARGET --upload LOCAL_PATH REMOTE_PATH [--region REGION]

# Read remote file
scripts/ssm-exec.sh --target TARGET --read REMOTE_PATH [--region REGION]

Running Commands Across Many Nodes

SSM start-session rate limit: 3 TPS per account. Plan batch size and delay accordingly.

aws ssm send-command does NOT support sagemaker-cluster: targets — only start-session works.

Show full SKILL.md (150 more words)Show less

Manual SSM Commands

When the scripts aren't suitable, use aws ssm start-session directly with AWS-StartNonInteractiveCommand. Wrap every invocation in unbuffer — without it, stdout is intermittently empty (see Prerequisites).

bash
cat > /tmp/cmd.json << 'EOF'
{"command": ["bash -c 'echo hello && whoami'"]}
EOF

unbuffer aws ssm start-session \
  --target sagemaker-cluster:{CLUSTER_ID}_{GROUP_NAME}-{INSTANCE_ID} \
  --region REGION \
  --document-name AWS-StartNonInteractiveCommand \
  --parameters file:///tmp/cmd.json
  • Always use a JSON file for --parameters — inline parameters break with special characters.
  • The document's command parameter is argv, not shell input. Wrap multi-statement scripts in bash -c '...' so pipes, semicolons, and redirects evaluate.

Common Diagnostic Commands

TaskCommand
Lifecycle logscat /var/log/provision/provisioning.log
Memoryfree -h
Disk/mountsdf -h && lsblk
GPU statusnvidia-smi
GPU memorynvidia-smi --query-gpu=memory.used,memory.total --format=csv
EFA/networkfi_info -p efa
CloudWatch agentsudo systemctl status amazon-cloudwatch-agent
Top processesps aux --sort=-%mem | head -20

Key Details

  • Default SSM non-interactive user is root.
  • SSM rate limit: 3 TPS per account.
  • For interactive sessions (rare), omit --document-name to get a shell.
  • Interactive commands (vim, top) are not supported via AWS-StartNonInteractiveCommand.
  • Large outputs may be truncated by SSM.
  • For troubleshooting common errors, see references/troubleshooting.md.

© awslabs, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (scripts, references) in plugins/sagemaker-ai/skills/hyperpod-ssm of awslabs/agent-plugins.

  • SKILL.md
  • references/troubleshooting.md
  • scripts/get-cluster-info.sh
  • scripts/list-nodes.sh
  • scripts/ssm-exec.sh

Open the folder on GitHubat commit da51970

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in awslabs/agent-plugins, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Hyperpod Ssm next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Hyperpod Ssm compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Hyperpod Ssm this skillawslabs/agent-plugins9151 repos~1.3kAutomated safety check: NotesApache-2.0
SageMaker Serving Image Selectionhuggingface/skills11k1 repos~4.6kAutomated safety check: PassApache-2.0
Python Environment Setup for SageMakerhuggingface/skills11k2 repos~1.7kAutomated safety check: PassApache-2.0
Aiml GPU Training Cluster Investigationaws/tools-for-devops-agent100—~5.4kAutomated safety check: PassApache-2.0
SageMaker Deployment Plannerhuggingface/skills11k1 repos~2.1kAutomated safety check: PassApache-2.0
Hf Cloud Serving Image Selectionwaybarrios/opencode-power-pack533—~4.3kAutomated safety check: PassApache-2.0

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All 33 skills in this repo
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  • Hyperpod Issue Report

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  • Hyperpod Performance Debugger

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    Diagnose performance issues on Amazon SageMaker HyperPod clusters — uneven NCCL bandwidth across nodes and poor filesystem throughput.

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Questions about Hyperpod Ssm

What does Hyperpod Ssm do?

Remote command execution and file transfer on SageMaker HyperPod cluster nodes via AWS Systems Manager (SSM). Hyperpod Ssm is an agent skill from awslabs/agent-plugins, published by the product's own GitHub organization. Remote command execution and file transfer on SageMaker HyperPod cluster nodes via AWS Systems Manager (SSM).

When should I use Hyperpod Ssm?

Hyperpod Ssm fits situations like: user request needs to execute commands on cluster nodes; upload files to nodes; read/download files from nodes; run diagnostics.

How do I install Hyperpod Ssm in Claude Code?

Run `npx skills add awslabs/agent-plugins --skill hyperpod-ssm -a claude-code`. Or copy the skill folder (plugins/sagemaker-ai/skills/hyperpod-ssm in awslabs/agent-plugins) into .claude/skills/hyperpod-ssm in your project. Claude Code loads it when a task matches its description.

How do I install Hyperpod Ssm in Codex?

Run `npx skills add awslabs/agent-plugins --skill hyperpod-ssm -a codex`. Or copy the skill folder (plugins/sagemaker-ai/skills/hyperpod-ssm in awslabs/agent-plugins) into .agents/skills/hyperpod-ssm in your project. Codex loads it when a task matches its description.

Can I use Hyperpod Ssm in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add awslabs/agent-plugins --skill hyperpod-ssm -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/hyperpod-ssm, .gemini/skills/hyperpod-ssm, .github/skills/hyperpod-ssm and .opencode/skills/hyperpod-ssm in your project.

What does Hyperpod Ssm need to run?

Going by SKILL.md and its folder, Hyperpod Ssm needs a shell for the scripts in its folder and the command-line tools its instructions call (aws, yum, apt, brew and bash). Our summary lists: A Bash shell.

Does Hyperpod Ssm access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Hyperpod Ssm safe to install?

Our automated static check of SKILL.md found notes only (runs commands with sudo), nothing it rates as a warning. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Hyperpod Ssm use?

Hyperpod Ssm is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Hyperpod Ssm use?

About 1.3k tokens (SKILL.md is roughly 5.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 524 tokens, read only when the agent opens those files.

What are the alternatives to Hyperpod Ssm?

Skills that share tags, products or a category with Hyperpod Ssm: SageMaker Serving Image Selection (huggingface/skills, 11k stars), Python Environment Setup for SageMaker (huggingface/skills, 11k stars), Aiml GPU Training Cluster Investigation (aws/tools-for-devops-agent, 100 stars) and SageMaker Deployment Planner (huggingface/skills, 11k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Hyperpod Ssm?

awslabs (a GitHub organization, an official publisher) maintains it in awslabs/agent-plugins, which has 915 GitHub stars. The repository holds 33 skills in this directory. The repository was last updated on October 5, 2026.

Source: awslabs/agent-plugins on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.