analyze-node-tuning

analyze-node-tuning is a command for Claude Code from wangke19/gemini-ai-helpers. It costs 18 tokens per session (2,007 once invoked), scanned A, a copy of analyze-node-tuning, Apache-2.0.

A command that examines node-tuning data from a live OpenShift node, a debug snapshot, or an sosreport, then produces recommendations for the Node Tuning Operator.

In plain words
What is it for?
It helps audit tuning after upgrades, investigate regressions, and create JSON or Markdown reports for incidents, documentation, or CI checks.
Why use it?
It turns low-level CPU, kernel, memory, and network measurements into specific tuning or remediation suggestions.

Command for Claude Code

Written for Claude Code: argument-hint in frontmatter.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is python3 extensions/node-tuning/skills/scripts/analyze_node_tuning.py \.

Good fit It helps audit tuning after upgrades, investigate regressions, and create JSON or Markdown reports for incidents, documentation, or CI checks.

Compare 6 commands from other repositories ↓
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/wangke19/gemini-ai-helpers
agentmods
npx agentmods add commands/wangke19/gemini-ai-helpers/analyze-node-tuning

Made for: Claude Code.

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 analyze-node-tuning

README.md
[![agentmods](https://agentmods.dev/badge/commands/wangke19/gemini-ai-helpers/analyze-node-tuning/github.svg)](https://agentmods.dev/commands/wangke19/gemini-ai-helpers/analyze-node-tuning)
Your own site
<a href="https://agentmods.dev/commands/wangke19/gemini-ai-helpers/analyze-node-tuning"><img src="https://agentmods.dev/badge/commands/wangke19/gemini-ai-helpers/analyze-node-tuning/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.

agentmods 80×15 button for analyze-node-tuning

Your own site · 80×15
<a href="https://agentmods.dev/commands/wangke19/gemini-ai-helpers/analyze-node-tuning"><img src="https://agentmods.dev/badge/commands/wangke19/gemini-ai-helpers/analyze-node-tuning.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 18 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,007 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 95% copy Near-identical to another mod 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 $0.00018 $0.02007
Opus 5 $0.00009 $0.01004
Sonnet 5 $0.00004 $0.00401
Haiku 4.5 $0.00002 $0.00201

Measured 8d ago against content hash 9bb7363b3c52, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

analyze-node-tuning 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 8d 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.

Origin

This is a copy

95% identical to analyze-node-tuning — 6 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

extensions/node-tuning/commands/analyze-node-tuning.md · 117 lines

How it starts

The opening of the file, as written. The whole thing — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Name

node-tuning:analyze-node-tuning

Synopsis

/node-tuning:analyze-node-tuning [--sosreport PATH] [--collect-sosreport|--no-collect-sosreport] [--sosreport-output PATH] [--node NODE] [--kubeconfig PATH] [--oc-binary PATH] [--format json|markdown] [--max-irq-samples N] [--keep-snapshot]

Description

The node-tuning:analyze-node-tuning command inspects kernel tuning signals gathered from either a live OpenShift node (/proc, /sys), an oc debug node/<name> snapshot captured via KUBECONFIG, or an extracted sosreport directory. It parses CPU isolation parameters, IRQ affinity, huge page allocation, critical sysctl settings, and networking counters before compiling actionable recommendations that can be enforced through Tuned profiles or MachineConfig updates.

Use this command when you need to:

  • Audit a node for tuning regressions after upgrades or configuration changes.
  • Translate findings into remediation steps for the Node Tuning Operator.
  • Produce JSON or Markdown reports suitable for incident response, CI gates, or documentation.

Implementation

  1. Establish data source
    • Live (local) analysis: the helper script defaults to /proc and /sys. Ensure the command runs on the target node (or within an SSH session / debug pod).
    • Remote analysis via oc debug: provide --node <name> (plus optional --kubeconfig and --oc-binary). The helper defaults to entering the RHCOS toolbox (backed by the registry.redhat.io/rhel9/support-tools image) via oc debug node/<name>, running sosreport --batch --quiet -e openshift -e openshift_ovn -e openvswitch -e podman -e crio -k crio.all=on -k crio.logs=on -k podman.all=on -k podman.logs=on -k networking.ethtool-namespaces=off --all-logs --plugin-timeout=600, streaming the archive locally (respecting --sosreport-output when set), and analyzing the extracted data. Use --toolbox-image (or TOOLBOX_IMAGE) to point at a mirrored support-tools image, --sosreport-arg to append extra flags (repeat per flag), or --skip-default-sosreport-flags to take full control. Host HTTP(S) proxy variables are forwarded when present but entirely optional. Add --no-collect-sosreport to skip sosreport generation entirely, and --keep-snapshot if you want to retain the downloaded files.
    • Offline analysis: provide --sosreport /path/to/sosreport-<timestamp> pointing to an extracted sosreport directory; the script auto-discovers embedded proc/ and sys/ trees.
    • Override non-standard layouts with --proc-root or --sys-root as needed.

Read the full file on GitHub · 117 lines

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. 8d ago First seen · 117 lines · 18 tokens per session scan A 9bb7363b3c52

Subscribe to this mod's changes

analyze-node-tuning is a command published in the GitHub repository wangke19/gemini-ai-helpers (2 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 18 tokens to every session and 2,007 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to analyze-node-tuning, differing in 6 lines, and is treated as a copy.