hyperpod-issue-report

hyperpod-issue-report is a skill for Claude Code from awslabs/agent-plugins. It costs 99 tokens per session (864 once invoked), scanned A, original, Apache-2.0.

A diagnostic report generator for HyperPod clusters running on Amazon Web Services, using either EKS or Slurm. It collects logs and configuration details from cluster nodes and stores the results in Amazon S3.

In plain words
What is it for?
Use it to investigate HyperPod cluster problems, collect diagnostics from selected or all nodes, and create a report for troubleshooting or AWS Support.
Why use it?
It gathers the information needed to investigate failed nodes and prepare an AWS Support case. This avoids collecting diagnostic files manually from many machines.

Skill for Claude Code ✓ vendor

Written for Claude Code: shipped in a Claude Code plugin.

Part of the sagemaker-ai plugin — 19 skills shipped together

Good fit Use it to investigate HyperPod cluster problems, collect diagnostics from selected or…

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/awslabs/agent-plugins/hyperpod-issue-report
About the project

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.

awslabs/agent-plugins · 889 stars · on GitHub

Install

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.

Any agent
npx skills add awslabs/agent-plugins --skill hyperpod-issue-report
Clone the repo
git clone --depth 1 https://github.com/awslabs/agent-plugins

Made for: Claude Code.

Or install sagemaker-ai, the plugin that ships this one along with the rest of its 19 skills.

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.

agentmods badge for hyperpod-issue-report

README.md
[![agentmods](https://agentmods.dev/badge/skills/awslabs/agent-plugins/hyperpod-issue-report.svg)](https://agentmods.dev/skills/awslabs/agent-plugins/hyperpod-issue-report)
Your own site
<a href="https://agentmods.dev/skills/awslabs/agent-plugins/hyperpod-issue-report"><img src="https://agentmods.dev/badge/skills/awslabs/agent-plugins/hyperpod-issue-report.svg" alt="Measured on agentmods" height="20"></a>
Per session 99 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 864 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original 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 $0.00099 $0.00864
Opus 5 $0.00049 $0.00432
Sonnet 5 $0.00020 $0.00173
Haiku 4.5 $0.00010 $0.00086

Measured 7d ago against content hash 03700baaf3e9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

hyperpod-issue-report 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 7d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/hyperpod_issue_report.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

plugins/sagemaker-ai/skills/hyperpod-issue-report/SKILL.md · 75 lines

How it starts

The opening of the file, as written. The whole thing — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.

HyperPod Issue Report

Collect diagnostic logs from HyperPod cluster nodes via SSM, store results in S3. Supports both EKS and Slurm clusters with auto-detection. Uses the bundled scripts/hyperpod_issue_report.py for reliable parallel collection.

Prerequisites

  • AWS CLI configured with permissions: sagemaker:DescribeCluster, sagemaker:ListClusterNodes, ssm:StartSession, s3:PutObject, s3:GetObject, eks:DescribeCluster
  • Python 3.8+ and uv (see uv installation docs for install options)
  • SSM Agent running on target nodes; node IAM roles need s3:GetObject/s3:PutObject on the report bucket
  • For EKS clusters: kubectl installed and configured (see Workflow step 2)

Workflow

1. Gather Information

Collect from the user:

  • Cluster identifier (required): accepts cluster name or full cluster ARN (e.g., arn:aws:sagemaker:us-west-2:123456789012:cluster/abc123)
  • AWS region (required unless extractable from ARN)
  • S3 path for report storage (required, e.g. s3://bucket/prefix). If the user doesn't have a bucket, create one (e.g., s3://hyperpod-diagnostics-<account-id>-<region>)
  • Issue description (optional)
  • Target scope: all nodes, specific instance groups, or specific node IDs (optional)

2. Verify Environment

aws sts get-caller-identity
aws sagemaker describe-cluster --cluster-name <name-or-arn> --region <region>

If the S3 bucket doesn't exist, create it:

aws s3 mb s3://<bucket-name> --region <region>

For EKS clusters (check Orchestrator.Eks in describe-cluster output):

  1. Ensure kubectl is installed (which kubectl). If missing, install it for the current platform.

  2. Configure kubeconfig using the EKS cluster name from the describe-cluster response:

    aws eks update-kubeconfig --name <eks-cluster-name> --region <region>
    

3. Run the Collection Script

uv run scripts/hyperpod_issue_report.py \
  --cluster <cluster-name-or-arn> \
  --region <region> \
  --s3-path s3://<bucket>[/prefix]

Read the full file on GitHub · 75 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 7d ago First seen · 75 lines · 99 tokens per session scan A 03700baaf3e9

Subscribe to this mod's changes

hyperpod-issue-report is a skill published in the GitHub repository awslabs/agent-plugins (889 stars, last pushed 2d ago), licensed Apache-2.0. It adds 99 tokens to every session and 864 once invoked, about $0.0005 per session on Opus 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 2026-08-30.

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