What does the Opensearch AI skill do?

Use when installing or configuring the OpenSearch extension for KubeSphere, which provides distributed search and analytics engine for storing logs, events, auditing, and notification history

Why use Opensearch on TypingMind?

Because you install it once and use it with any model. Opensearch is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Opensearch in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/kubesphere/kubesphere/tree/master/skills/opensearch. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Opensearch?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Opensearch?

As many as you like. As long as a model supports skills, you can use Opensearch with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Opensearch AI skill free?

It is published on GitHub by kubesphere. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

Opensearch by kubesphere — AI Skill for Any LLM

OpenSearch Extension

Overview

OpenSearch is a distributed search and analytics engine built into the KubeSphere WizTelemetry Observability Platform. It is used to store, search, and analyze observability data including logs, auditing events, K8s events, and notification history.

When to Use

Installing OpenSearch cluster for KubeSphere observability extensions
Configuring OpenSearch storage for logging, events, auditing, and notifications
Managing OpenSearch Dashboard and Curator components

Components

Component	Description	Default
opensearch-master	Master node for cluster coordination	1 replica
opensearch-data	Data nodes for storing indices	3 replicas
opensearch-dashboards	Web UI for visualizing data	disabled
opensearch-curator	Scheduled task to clean old indices	enabled

Prerequisites

Check Installation Status

bash
# Check if OpenSearch is installed
kubectl get installplan opensearch -o jsonpath='{.spec.enabled}'

# Get installed version
kubectl get extension opensearch -o jsonpath='{.status.installedVersion}'

# Get target clusters
kubectl get installplan opensearch -o jsonpath='{.spec.clusterScheduling.placement.clusters}'

Returns:

"true" - installed and enabled
"false" - installed but disabled
Empty/Error - not installed

Get Available Clusters

bash
kubectl get clusters -o jsonpath='{.items[*].metadata.name}'

Confirm Target Clusters (MUST DO)

⚠️ CRITICAL: Do Not guess.

⚠️ CRITICAL: DO NOT proceed until target clusters are determined.

If user explicitly specified target clusters in the request → Use those clusters directly
If user did NOT specify target clusters → You MUST ask user to confirm which clusters to deploy to

Ask user (if not specified):


Available clusters: host, dev
Which clusters do you want to deploy OpenSearch to?

Get Latest Version

MUST do this to get the latest version:

bash
kubectl get extensionversions -l kubesphere.io/extension-ref=opensearch -o jsonpath='{range .items[*]}{.spec.version}{"\n"}{end}' | sort -V | tail -1

Installation

⚠️ CRITICAL: InstallPlan metadata.name MUST be opensearch. DO NOT use any other name.

Use the latest version obtained from "Get Latest Version" step.

Minimal Installation

yaml
apiVersion: kubesphere.io/v1alpha1
kind: InstallPlan
metadata:
  name: opensearch
spec:
  extension:
    name: opensearch
    version: <VERSION>  # From Get Latest Version step
  enabled: true
  upgradeStrategy: Manual
  clusterScheduling:
    placement:
      clusters:
        - host

With OpenSearch Dashboard

yaml
apiVersion: kubesphere.io/v1alpha1
kind: InstallPlan
metadata:
  name: opensearch
spec:
  extension:
    name: opensearch
    version: <VERSION>  # From Get Latest Version step
  enabled: true
  upgradeStrategy: Manual
  config: |
    opensearch-dashboards:
      enabled: true
  clusterScheduling:
    placement:
      clusters:
        - host

Disable Curator

yaml
apiVersion: kubesphere.io/v1alpha1
kind: InstallPlan
metadata:
  name: opensearch
spec:
  extension:
    name: opensearch
    version: <VERSION>  # From Get Latest Version step
  enabled: true
  upgradeStrategy: Manual
  config: |
    opensearch-curator:
      enabled: false
  clusterScheduling:
    placement:
      clusters:
        - host

Configuration

Parameters

Parameter	Type	Default	Description
`opensearch-master.replicas`	int	1	Number of master nodes
`opensearch-master.opensearchJavaOpts`	string	"-Xmx512M -Xms512M"	JVM options
`opensearch-master.resources`	object	-	Resource limits/requests
`opensearch-data.replicas`	int	3	Number of data nodes
`opensearch-data.opensearchJavaOpts`	string	"-Xmx1536M -Xms1536M"	JVM options
`opensearch-data.resources`	object	-	Resource limits/requests
`opensearch-data.service.type`	string	NodePort	Service type
`opensearch-data.service.nodePort`	int	30920	NodePort for external access
`opensearch-dashboards.enabled`	bool	false	Enable OpenSearch Dashboards
`opensearch-curator.enabled`	bool	true	Enable index cleanup job

Resource Configuration

yaml
opensearch-master:
  replicas: 1
  opensearchJavaOpts: "-Xmx512M -Xms512M"
  resources:
    requests:
      cpu: "100m"
      memory: "512Mi"
    limits:
      cpu: "500m"
      memory: "1Gi"

opensearch-data:
  replicas: 3
  opensearchJavaOpts: "-Xmx2048M -Xms2048M"
  resources:
    requests:
      cpu: "200m"
      memory: "2Gi"
    limits:
      cpu: "2000m"
      memory: "4Gi"
  persistence:
    size: 50Gi
    storageClass: "local-volume"

Operations

Access Target Cluster

⚠️ CRITICAL: You MUST access the target cluster BEFORE checking status or running any kubectl commands below.

❌ DO NOT run kubectl commands without using the target cluster kubeconfig ✅ MUST run: kubectl --kubeconfig=/tmp/<cluster>-kubeconfig ...

Checklist (must complete before any operation):

1. Find target clusters:

bash
kubectl get installplan opensearch -o jsonpath='{.spec.clusterScheduling.placement.clusters}'

2. Get cluster kubeconfig:

bash
kubectl get cluster <cluster-name> -o jsonpath='{.spec.connection.kubeconfig}' | base64 -d > /tmp/<cluster-name>-kubeconfig

3. Use this kubeconfig for ALL subsequent commands

Note: Replace <cluster-name> with the actual cluster name. Use spec.connection.kubeconfig for imported clusters.

Check Status

⚠️ REQUIRED: Complete Access Target Cluster checklist FIRST

bash
# Extension status
kubectl --kubeconfig=/tmp/<cluster>-kubeconfig get extension opensearch

# InstallPlan status
kubectl --kubeconfig=/tmp/<cluster>-kubeconfig get installplan opensearch

Get Pods

⚠️ REQUIRED: Complete Access Target Cluster checklist FIRST

bash
# All pods
kubectl --kubeconfig=/tmp/<cluster>-kubeconfig get pods -n kubesphere-logging-system -l app.kubernetes.io/instance=opensearch-agent

# By component
kubectl --kubeconfig=/tmp/<cluster>-kubeconfig get pods -n kubesphere-logging-system -l app.kubernetes.io/name=opensearch-master
kubectl --kubeconfig=/tmp/<cluster>-kubeconfig get pods -n kubesphere-logging-system -l app.kubernetes.io/name=opensearch-data

# Status
kubectl --kubeconfig=/tmp/<cluster>-kubeconfig get pods -n kubesphere-logging-system -l app.kubernetes.io/instance=opensearch-agent -o wide

External Endpoint

⚠️ REQUIRED: Complete Access Target Cluster checklist FIRST

OpenSearch uses NodePort (default: 30920) to expose service externally.

bash
# Get NodePort service
kubectl --kubeconfig=/tmp/<cluster>-kubeconfig get svc -n kubesphere-logging-system opensearch-cluster-data

# Get node IP
kubectl --kubeconfig=/tmp/<cluster>-kubeconfig get nodes -o jsonpath='{.items[0].status.addresses[?(@.type=="InternalIP")].address}'

# Access OpenSearch externally
# URL: https://<node-ip>:30920
curl -k -u admin:admin "https://<node-ip>:30920/_cluster/health"

Output Contract (For Other Skills)

⚠️ This section defines what information this skill provides to other skills

When OpenSearch is successfully deployed, other skills can retrieve:

Field	Example Value	Description
`endpoint`	`https://127.0.0.1:30920`	Full URL for Vector sink
`nodePort`	`30920`	NodePort number
`nodeIP`	`127.0.0.1`	Node internal IP
`auth.user`	`admin`	Default username
`auth.password`	`admin`	Default password

How other skills should get this info:

Find which cluster OpenSearch was deployed to:

bash
kubectl get installplan opensearch -o jsonpath='{.spec.clusterScheduling.placement.clusters}'

Get cluster kubeconfig:

bash
kubectl get cluster <cluster-name> -o jsonpath='{.spec.connection.kubeconfig}' | base64 -d > /tmp/<cluster-name>-kubeconfig

Get OpenSearch endpoint:

bash
# NodePort
NODE_PORT=$(kubectl --kubeconfig=/tmp/<cluster>-kubeconfig get svc -n kubesphere-logging-system opensearch-cluster-data -o jsonpath='{.spec.ports[?(@.port==9200)].nodePort}')

# Node IP
NODE_IP=$(kubectl --kubeconfig=/tmp/<cluster>-kubeconfig get nodes -o jsonpath='{.items[0].status.addresses[?(@.type=="InternalIP")].address}')

# Full endpoint
echo "https://${NODE_IP}:${NODE_PORT}"

Update Configuration

yaml
apiVersion: kubesphere.io/v1alpha1
kind: InstallPlan
metadata:
  name: opensearch
spec:
  extension:
    name: opensearch
    version: <VERSION>  # From Get Latest Version step
  enabled: true
  upgradeStrategy: Manual
  config: |
    opensearch-data:
      replicas: 5
      opensearchJavaOpts: "-Xmx4096M -Xms4096M"
    opensearch-dashboards:
      enabled: true
  clusterScheduling:
    placement:
      clusters:
        - host

Uninstall

Uninstall from all clusters:

bash
kubectl delete installplan opensearch

Uninstall from specific cluster:

To remove OpenSearch from a specific cluster, update the InstallPlan by removing that cluster from clusterScheduling.placement.clusters:

yaml
apiVersion: kubesphere.io/v1alpha1
kind: InstallPlan
metadata:
  name: opensearch
spec:
  extension:
    name: opensearch
    version: <VERSION>
  enabled: true
  upgradeStrategy: Manual
  config: |
    opensearch-data:
      replicas: 3
  clusterScheduling:
    placement:
      clusters:
        - <REMAINING_CLUSTERS>  # Remove the cluster you want to uninstall from

Troubleshooting

⚠️ REQUIRED: Complete Access Target Cluster checklist FIRST

Pod Issues

bash
kubectl --kubeconfig=/tmp/<cluster>-kubeconfig get pods -n kubesphere-logging-system -l app.kubernetes.io/instance=opensearch-agent

# Pod events
kubectl --kubeconfig=/tmp/<cluster>-kubeconfig describe pods -n kubesphere-logging-system -l app.kubernetes.io/instance=opensearch-agent

OpenSearch Health

⚠️ REQUIRED: Complete Access Target Cluster checklist FIRST

bash
# Cluster health
curl -k -u admin:admin "https://<node-ip>:30920/_cluster/health"

# List indices
curl -k -u admin:admin "https://<node-ip>:30920/_cat/indices"

Common Issues

Issue	Solution
Pods not starting	Check node resources and storage availability
Out of memory	Increase JVM heap size
Cannot connect	Check NodePort firewall rules
Index storage full	Increase PVC size or enable Curator

Notes

Resource Requirements: OpenSearch requires significant CPU and memory
Storage: Data nodes use persistent storage
NodePort: Default port is 30920
Multi-cluster: Can be deployed to specific clusters

Publisher	kubesphere
Repository	`kubesphere`
Skill name	`opensearch`
Stars	17.1K
Forks	2.8K
Bundled files	Instructions only
Links	Skill source Repository Homepage

Opensearch

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

OpenSearch Extension

Overview

When to Use

Components

Prerequisites

Check Installation Status

Get Available Clusters

Confirm Target Clusters (MUST DO)

Get Latest Version

Installation

Minimal Installation

With OpenSearch Dashboard

Disable Curator

Configuration

Parameters

Resource Configuration

Operations

Access Target Cluster

Check Status

Get Pods

External Endpoint

Output Contract (For Other Skills)

Update Configuration

Uninstall

Troubleshooting

Pod Issues

OpenSearch Health

Common Issues

Notes

Frequently asked questions

Set up your own AI workspace now

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

OpenSearch Extension

Overview

When to Use

Components

Prerequisites

Check Installation Status

Get Available Clusters

Confirm Target Clusters (MUST DO)

Get Latest Version

Installation

Minimal Installation

With OpenSearch Dashboard

Disable Curator

Configuration

Parameters

Resource Configuration

Operations

Access Target Cluster

Check Status

Get Pods

External Endpoint

Output Contract (For Other Skills)

Update Configuration

Uninstall

Troubleshooting

Pod Issues

OpenSearch Health

Common Issues

Notes

Frequently asked questions

Related AI Skills

Set up your own AI workspace now