k8s_openclaw

Retrieve stored memory files from Kubernetes clusters using token-based authentication.

21|6|Updated Aug 26, 2025
One-click install
npx skills add https://github.com/hepai-lab/drsai --skill k8s-openclaw
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: k8s_openclaw
Source: https://github.com/hepai-lab/drsai/tree/main/agent_skills/skills_tmp/k8s_openclaw
Command: npx skills add https://github.com/hepai-lab/drsai --skill k8s-openclaw

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, and includes scripts (resource) components.

What problem does it solve?

This skill helps users locate and retrieve stored memory files within Kubernetes-based workflows, enabling quick access to past experiments, tool outputs, and memory records.

Core Features & Use Cases

  • Memory discovery and retrieval from Kubernetes clusters to access historical data.
  • Token-based authentication to securely access memory artifacts and logs.
  • Use Case: Imagine running long experiments in a Kubernetes environment and needing to pull memory artifacts to reproduce results and audit activities.

Quick Start

Provide the memory file identifier and cluster context to retrieve the stored memory artifact.

Frequently Asked Questions about k8s_openclaw

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I retrieve stored memory files from a Kubernetes cluster?

To retrieve stored memory files from a Kubernetes cluster, you need a script that authenticates via an access token and queries the cluster's API. This skill uses Python 3 and the requests library to fetch historical memory data.

What is the best way to access historical memory data and audit logs in Kubernetes?

Accessing historical memory data and audit logs in Kubernetes requires token-based authentication against the cluster's endpoint. This approach securely retrieves past experiment artifacts and tool outputs stored within your workflows.

Do I need an access token to query memory artifacts from Kubernetes workflows?

Yes, you need an access token to query memory artifacts from Kubernetes workflows. The retrieval process requires authenticating against the cluster's endpoint first to securely obtain permissions for subsequent API calls.

Can I use Python and the requests library to fetch Kubernetes memory records?

Yes, you can use Python 3 and the requests library to fetch Kubernetes memory records. This combination allows you to handle token-based authentication and execute API calls to retrieve stored memory artifacts effectively.

How to reproduce experiment results by pulling memory artifacts from Kubernetes?

To reproduce experiment results by pulling memory artifacts from Kubernetes, provide the memory file identifier and cluster context. This fetches the specific historical data and tool outputs needed to audit past activities.

What are the limitations of retrieving memory data from Kubernetes clusters?

Limitations of retrieving memory data from Kubernetes clusters include the strict dependency on Python 3 and the requests library. Additionally, successful retrieval requires prior access to the cluster's authentication endpoint to obtain a valid token.