vmware-aiops
AI-powered VMware vCenter/ESXi monitoring and operations. Manage infrastructure via natural language: inventory queries, health monitoring, VM lifecycle (create, delete, power, snapshot, clone, migrate), VM deployment (OVA, template, linked clone, batch), cluster management (create, HA/DRS), iSCSI configuration, datastore browsing, vSAN management, Aria Operations analytics, Kubernetes clusters, and scheduled log scanning.
What this skill does
# VMware AIops
AI-powered VMware vCenter and ESXi operations tool. Manage your entire VMware infrastructure using natural language through any AI coding assistant.
> **Need read-only monitoring only?** Use [VMware-Monitor](https://github.com/zw008/VMware-Monitor) — an independent repository with code-level safety (zero destructive code in the codebase). Install: `clawhub install vmware-monitor`
## When to Use This Skill
- Query VM, host, datastore, cluster, and network inventory
- Check health status, active alarms, hardware sensors, and event logs
- Perform VM lifecycle operations: power on/off, create, delete, snapshot, clone, migrate
- Deploy VMs from OVA, templates, linked clones, or batch specs
- Create and manage clusters: HA/DRS configuration, add/remove hosts
- Configure iSCSI storage: enable adapter, add/remove targets, rescan
- Browse datastores and discover ISO/OVA/VMDK images
- Monitor vSAN health, capacity, disk groups, and performance
- Access Aria Operations (VCF Operations) for historical metrics, anomaly detection, and capacity planning
- Manage vSphere Kubernetes Service (VKS) clusters
- Run scheduled scanning with webhook notifications (Slack, Discord)
## Quick Install
All install methods fetch from the same source: [github.com/zw008/VMware-AIops](https://github.com/zw008/VMware-AIops) (MIT licensed). We recommend reviewing the source code before installing.
```bash
# Via Skills.sh (fetches from GitHub)
npx skills add zw008/VMware-AIops
# Via ClawHub (fetches from ClawHub registry snapshot of GitHub)
clawhub install vmware-aiops
# Via PyPI (recommended for version pinning)
uv tool install vmware-aiops==1.0.16
```
### Claude Code
```
/plugin marketplace add zw008/VMware-AIops
/plugin install vmware-ops
/vmware-ops:vmware-aiops
```
## Usage Mode
Choose the best mode based on your environment:
| Scenario | Recommended Mode | Why |
|----------|-----------------|-----|
| **Cloud models** (Claude, GPT-4o, Gemini) | MCP or CLI | Both work well; MCP gives structured JSON I/O |
| **Local/small models** (Ollama, Llama, Qwen <32B) | **CLI** | Lower token cost (~2K vs ~10K), higher accuracy — small models struggle with 31 MCP tool schemas |
| **Token-sensitive workflows** | **CLI** | CLI via SKILL.md uses ~2K tokens; MCP loads ~10K tokens of tool definitions into every conversation |
| **Automated pipelines / Agent chaining** | **MCP** | Structured JSON input/output, type-safe parameters, no shell parsing |
### Calling Priority
- **MCP-native tools** (Claude Code, Cursor): MCP first, CLI fallback
- **Local models / Token-sensitive**: CLI first (MCP not needed)
- **All other tools**: CLI first
> **Tip**: For token-sensitive scenarios, use CLI mode — the AI reads SKILL.md (~2K tokens) and calls commands via Bash. MCP mode loads all 31 tool schemas (~10K tokens) into context on every conversation turn.
### CLI Examples
```bash
# Activate venv first
source /path/to/VMware-AIops/.venv/bin/activate
# Inventory
vmware-aiops inventory vms --target home-esxi
vmware-aiops inventory hosts --target home-esxi
# Health
vmware-aiops health alarms --target home-esxi
# VM operations
vmware-aiops vm info my-vm --target home-esxi
vmware-aiops vm power-on my-vm --target home-esxi
```
### MCP Mode (Optional)
For Claude Code / Cursor users who prefer structured tool calls, add to `~/.claude/settings.json`:
```json
{
"mcpServers": {
"vmware-aiops": {
"command": "/path/to/VMware-AIops/.venv/bin/python",
"args": ["-m", "mcp_server"],
"cwd": "/path/to/VMware-AIops",
"env": {
"VMWARE_AIOPS_CONFIG": "~/.vmware-aiops/config.yaml"
}
}
}
}
```
MCP exposes 43 tools across 8 categories. All accept optional `target` parameter.
| Category | Tools |
|----------|-------|
| Inventory | `list_virtual_machines`, `list_esxi_hosts`, `list_all_datastores`, `list_all_clusters` |
| Health | `get_alarms`, `get_events`, `vm_info` |
| VM Lifecycle | `vm_power_on`, `vm_power_off`, `vm_set_ttl`, `vm_cancel_ttl`, `vm_list_ttl`, `vm_clean_slate` |
| Deployment | `deploy_vm_from_ova`, `deploy_vm_from_template`, `deploy_linked_clone`, `attach_iso_to_vm`, `convert_vm_to_template`, `batch_clone_vms`, `batch_linked_clone_vms`, `batch_deploy_from_spec` |
| Guest Operations | `vm_guest_exec`, `vm_guest_upload`, `vm_guest_download` |
| Plan → Apply | `vm_create_plan`, `vm_apply_plan`, `vm_rollback_plan`, `vm_list_plans` |
| Datastore | `browse_datastore`, `scan_datastore_images`, `list_cached_images` |
| Cluster | `cluster_create`, `cluster_delete`, `cluster_add_host`, `cluster_remove_host`, `cluster_configure`, `cluster_info` |
| Storage / iSCSI | `storage_iscsi_enable`, `storage_iscsi_status`, `storage_iscsi_add_target`, `storage_iscsi_remove_target`, `storage_rescan` |
`list_virtual_machines` auto-compacts when inventory exceeds 50 VMs (returns compact fields only). Use `limit` or `fields` to override.
## Architecture
```
User (Natural Language)
↓
AI Tool (Claude Code / Aider / Gemini / Codex / Cursor / Trae / Kimi)
↓
├─ CLI mode (default): vmware-aiops CLI ──→ pyVmomi ──→ vSphere API
│
└─ MCP mode (optional): MCP Server (stdio) ──→ pyVmomi ──→ vSphere API
↓
vCenter Server ──→ ESXi Clusters ──→ VMs
or
ESXi Standalone ──→ VMs
```
## Capabilities
### 1. Inventory
| Feature | vCenter | ESXi | Details |
|---------|:-------:|:----:|---------|
| List VMs | ✅ | ✅ | Name, power state, CPU, memory, guest OS, IP |
| List Hosts | ✅ | ⚠️ Self only | CPU cores, memory, ESXi version, VM count, uptime |
| List Datastores | ✅ | ✅ | Capacity, free/used, type (VMFS/NFS), usage % |
| List Clusters | ✅ | ❌ | Host count, DRS/HA status |
| List Networks | ✅ | ✅ | Network name, associated VM count |
### 2. Health & Monitoring
| Feature | vCenter | ESXi | Details |
|---------|:-------:|:----:|---------|
| Active Alarms | ✅ | ✅ | Severity, alarm name, entity, timestamp |
| Event/Log Query | ✅ | ✅ | Filter by time range, severity; 50+ event types |
| Hardware Sensors | ✅ | ✅ | Temperature, voltage, fan status |
| Host Services | ✅ | ✅ | hostd, vpxa running/stopped status |
**Monitored Event Types:**
| Category | Events |
|----------|--------|
| VM Failures | `VmFailedToPowerOnEvent`, `VmDiskFailedEvent`, `VmFailoverFailed` |
| Host Issues | `HostConnectionLostEvent`, `HostShutdownEvent`, `HostIpChangedEvent` |
| Storage | `DatastoreCapacityIncreasedEvent`, SCSI high latency |
| HA/DRS | `DasHostFailedEvent`, `DrsVmMigratedEvent`, `DrsSoftRuleViolationEvent` |
| Auth | `UserLoginSessionEvent`, `BadUsernameSessionEvent` |
### 3. VM Lifecycle
| Operation | Command | Confirmation | vCenter | ESXi |
|-----------|---------|:------------:|:-------:|:----:|
| Power On | `vm power-on <name>` | — | ✅ | ✅ |
| Graceful Shutdown | `vm power-off <name>` | Double | ✅ | ✅ |
| Force Power Off | `vm power-off <name> --force` | Double | ✅ | ✅ |
| Reset | `vm reset <name>` | — | ✅ | ✅ |
| Suspend | `vm suspend <name>` | — | ✅ | ✅ |
| VM Info | `vm info <name>` | — | ✅ | ✅ |
| Create VM | `vm create <name> --cpu --memory --disk` | — | ✅ | ✅ |
| Delete VM | `vm delete <name>` | Double | ✅ | ✅ |
| Reconfigure | `vm reconfigure <name> --cpu --memory` | Double | ✅ | ✅ |
| Create Snapshot | `vm snapshot-create <name> --name <snap>` | — | ✅ | ✅ |
| List Snapshots | `vm snapshot-list <name>` | — | ✅ | ✅ |
| Revert Snapshot | `vm snapshot-revert <name> --name <snap>` | — | ✅ | ✅ |
| Delete Snapshot | `vm snapshot-delete <name> --name <snap>` | — | ✅ | ✅ |
| Clone VM | `vm clone <name> --new-name <new>` | — | ✅ | ✅ |
| vMotion | `vm migrate <name> --to-host <host>` | — | ✅ | ❌ |
| Set TTL | `vm set-ttl <name> --minutes <n>` | — | ✅ | ✅ |
| Cancel TTL | `vm cancel-ttl <name>` | — | ✅ | ✅ |
| List TTLs | `vm list-ttl` | — | ✅ | ✅ |
| Clean Slate | `vm clean-slate <name> [--snapshot baseline]` | Double | ✅ | ✅ |
| Guest Exec | `vm guest-exec <name> --cmd /bin/bash --args "-c 'whoami'"` | — | ✅ | ✅ |
| Guest Upload | `vm guest-upload <name> --local f.sRelated in Cloud & DevOps
appbuilder-action-scaffolder
IncludedCreate, implement, deploy, and debug Adobe Runtime actions with consistent layout, validation, and error handling. Use this skill whenever the user needs to add actions to an App Builder project, understand action structure (params, response format, web/raw actions), configure actions in the manifest, use App Builder SDKs (State, Files, Events, database), deploy and invoke actions via CLI, debug action issues, or implement patterns such as webhook receivers, custom event providers, journaling consumers, large payload redirects, action sequence pipelines, and Asset Compute workers. Also trigger when users mention serverless functions in Adobe context, action logging, IMS authentication for actions, or cron-style scheduled actions.
orchestrating-datacloud
IncludedSalesforce Data Cloud product orchestrator for connect→prepare→harmonize→segment→act workflows. Use this skill when the user needs a multi-step Data Cloud pipeline, cross-phase troubleshooting, or data space and data kit management. TRIGGER when: user needs a multi-step Data Cloud pipeline, asks to set up or troubleshoot Data Cloud across phases, manages data spaces or data kits, or wants a cross-phase sf data360 workflow. DO NOT TRIGGER when: work is isolated to a single phase (use the matching phase-specific skill), the task is STDM/session tracing/parquet telemetry (use observing-agentforce), standard CRM SOQL (use querying-soql), or Apex implementation (use generating-apex).
github-project-automation
IncludedAutomate GitHub repository setup with CI/CD workflows, issue templates, Dependabot, and CodeQL security scanning. Includes 12 production-tested workflows and prevents 18 errors: YAML syntax, action pinning, and configuration. Use when: setting up GitHub Actions CI/CD, creating issue/PR templates, enabling Dependabot or CodeQL scanning, deploying to Cloudflare Workers, implementing matrix testing, or troubleshooting YAML indentation, action version pinning, secrets syntax, runner versions, or CodeQL configuration. Keywords: github actions, github workflow, ci/cd, issue templates, pull request templates, dependabot, codeql, security scanning, yaml syntax, github automation, repository setup, workflow templates, github actions matrix, secrets management, branch protection, codeowners, github projects, continuous integration, continuous deployment, workflow syntax error, action version pinning, runner version, github context, yaml indentation error
sf-datacloud
IncludedSalesforce Data Cloud product orchestrator for connect→prepare→harmonize→segment→act workflows. TRIGGER when: user needs a multi-step Data Cloud pipeline, asks to set up or troubleshoot Data Cloud across phases, manages data spaces or data kits, or wants a cross-phase `sf data360` workflow. DO NOT TRIGGER when: work is isolated to a single phase (use the matching sf-datacloud-* skill), the task is STDM/session tracing/parquet telemetry (use sf-ai-agentforce-observability), standard CRM SOQL (use sf-soql), or Apex implementation (use sf-apex).
fabric-cli
IncludedUse this skill for Fabric.so CLI workflows with the `fabric` terminal command: diagnose/install/login, search or browse a Fabric library, save notes/links/files, create folders, ask the Fabric AI assistant, manage tasks/workspaces, generate shell completion, check subscription usage, produce JSON output, and use Fabric as persistent agent memory. Do not use for Microsoft Fabric/Azure/Power BI `fab`, Daniel Miessler's Fabric framework, Python Fabric SSH, Fabric.js, or textile/fashion fabric.
lark
IncludedLark/Feishu CLI skills: lark-cli operations for docs, markdown, sheets, base, calendar, im, mail, task, okr, drive, wiki, slides, whiteboard, apps, approval, attendance, contact, vc, minutes, event. Use when the user needs to operate Lark/Feishu resources via lark-cli, send messages, manage documents, spreadsheets, calendars, tasks, OKRs, deploy web pages, or any Feishu/Lark workspace operations.