k8s-memory-tune
**触发词**: oomkilled, memory_limit, jvm_heap, container_memory, k8s 内存.
Best use case
k8s-memory-tune is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
**触发词**: oomkilled, memory_limit, jvm_heap, container_memory, k8s 内存.
Teams using k8s-memory-tune should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/k8s-memory-tune/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How k8s-memory-tune Compares
| Feature / Agent | k8s-memory-tune | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
**触发词**: oomkilled, memory_limit, jvm_heap, container_memory, k8s 内存.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# k8s-memory-tune **触发词**: oomkilled, memory_limit, jvm_heap, container_memory, k8s 内存. ## Install ``` npx clawhub@latest install k8s-memory-tune ```
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