Cml Admin

Community

automateyournetwork

cml-admin

CML administration — user/group management, system info, licensing, resource monitoring. Use when creating CML users, checking license status, monitoring CML server resources, or auditing lab usage across teams.

Overview

Publisher	automateyournetwork
Repository	`netclaw`
Skill name	`cml-admin`
Stars	680
Forks	189
Bundled files	Instructions only
License	Apache-2.0
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by automateyournetwork on GitHub. Read the source before you install it.

Installation

Install the Cml Admin AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/automateyournetwork/netclaw/tree/main/workspace/skills/cml-admin
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/automateyournetwork/netclaw.git /tmp/netclaw
mkdir -p .claude/skills
cp -r /tmp/netclaw/workspace/skills/cml-admin .claude/skills/cml-admin

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cml Admin in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Cml Admin on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Cml Admin is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

CML Administration

MCP Server

Command: cml-mcp (pip-installed, stdio transport)
Requires: CML_URL, CML_USERNAME, CML_PASSWORD environment variables

Available Tools

User Management

Tool	Parameters	What It Does
`get_users`	none	List all CML users
`create_user`	`username`, `password`, `fullname?`, `email?`, `admin?`	Create a new CML user
`get_user`	`user_id`/`username`	Get user details (labs, resource usage)
`update_user`	`user_id`/`username`, fields to update	Update user properties
`delete_user`	`user_id`/`username`	Delete a CML user

Group Management

Tool	Parameters	What It Does
`get_groups`	none	List all CML groups
`create_group`	`name`, `description?`, `members?`	Create a new group
`update_group`	`group_id`/`name`, fields to update	Update group properties
`delete_group`	`group_id`/`name`	Delete a group

System Information

Tool	Parameters	What It Does
`get_system_info`	none	CML version, uptime, resource usage (CPU, RAM, disk)
`get_node_defs`	none	List all available node definitions and their resource requirements
`get_licensing`	none	License status, node count, expiration
`get_resource_usage`	none	Current resource utilization across all labs

Workflow: Onboard a New Lab User

When an admin wants to add a new team member:

Check existing users: get_users to see current user list
Create the user: create_user with their credentials
Add to group (optional): update_group to add user to a team group
Verify: get_user to confirm creation
Share credentials: Report the username and CML URL to the admin (never share the password in Slack)

Workflow: Resource Capacity Check

Before building a large lab:

Check system resources: get_system_info for CPU, RAM, disk
Check licensing: get_licensing for available node count
Check node definitions: get_node_defs for per-node resource requirements
Calculate: Does the planned lab fit within available resources?
Report: "You have X GB RAM free, Y CPU cores available, Z node licenses remaining. Your planned lab needs A GB RAM and B nodes."

Workflow: System Health Report

For CML server health monitoring:

System info: get_system_info — version, uptime, resource usage
Licensing: get_licensing — license status and node count
Resource usage: get_resource_usage — breakdown by lab/user
Active labs: get_labs (from cml-lab-lifecycle) — list running labs
Generate report: Summary of CML platform health

Resource Planning Guide

Typical per-node resource requirements:

Node Type	vCPUs	RAM	Disk
IOSv	1	512 MB	2 GB
IOSv L2	1	768 MB	2 GB
CSR1000v / Cat8000v	1	3 GB	8 GB
NX-OS 9000v	2	6 GB	8 GB
IOS-XR 9000v	2	8 GB	16 GB
ASAv	1	2 GB	8 GB
Ubuntu Server	1	512 MB	8 GB
Unmanaged Switch	0	0	0
External Connector	0	0	0

Rule of thumb: Plan for the CML host to have at least 2x the total RAM needed by all concurrent labs, plus 8 GB for the CML OS itself.

User Roles

Role	Capabilities
Admin	Full access: create/delete users, manage all labs, system settings
User	Create/manage own labs, view shared labs

Workflow: Audit CML Usage

For tracking who's using what:

List all users: get_users
For each user: get_user to see their labs and resource usage
List all labs: get_labs with ownership info
Check resource usage: get_resource_usage for allocation breakdown
Report: Table of users, their labs, running state, and resource consumption
Identify stale labs: Labs that have been stopped for days — candidates for cleanup

Important Rules

Admin operations require admin credentials — user management needs admin-level CML access
Never share passwords in Slack — report usernames only, instruct admin to share credentials securely
Check resources before big labs — don't let users build labs that exceed server capacity
Monitor licensing — CML has node count limits; stay within license boundaries
Record in GAIT — log all admin operations for audit trail

Environment Variables

CML_URL — CML server URL
CML_USERNAME — CML username (admin for full access)
CML_PASSWORD — CML password
CML_VERIFY_SSL — Verify SSL certificate (true/false)

Failure Behavior

On a tool error (timeout, unreachable host, malformed response), report the failure and its error message directly to the user rather than fabricating or guessing at results.
Do not automatically retry a write/mutating operation after a failure — surface the error and get explicit confirmation before retrying, since a blind retry on a partially-applied change can leave state inconsistent.

Frequently asked questions

What does the Cml Admin AI skill do?

Why use Cml Admin on TypingMind?

Because you install it once and use it with any model. Cml Admin 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 Cml Admin in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/automateyournetwork/netclaw/tree/main/workspace/skills/cml-admin. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Cml Admin?

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 Cml Admin?

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

Is the Cml Admin AI skill free?

Yes. It is published on GitHub by automateyournetwork under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

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.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

CML Administration

MCP Server

Available Tools

User Management

Group Management

System Information

Workflow: Onboard a New Lab User

Workflow: Resource Capacity Check

Workflow: System Health Report

Resource Planning Guide

User Roles

Workflow: Audit CML Usage

Important Rules

Environment Variables

Failure Behavior

Frequently asked questions

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