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Cml Topology Builder

Community
automateyournetwork
cml-topology-builder

Build CML topologies — add nodes, create interfaces, wire links, set link conditioning, add annotations. Use when building a network topology in CML, adding routers or switches to a lab, wiring links between nodes, or simulating WAN conditions.

Overview

Publisherautomateyournetwork
Repositorynetclaw
Skill namecml-topology-builder
Stars
680
Forks
189
Bundled files
Instructions only
LicenseApache-2.0
Links
  • 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 Topology Builder AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/automateyournetwork/netclaw/tree/main/workspace/skills/cml-topology-builder
  4. 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.
2

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-topology-builder .claude/skills/cml-topology-builder
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cml Topology Builder 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 Topology Builder 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 Topology Builder 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 Topology Builder

MCP Server

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

Available Tools

Node Management

ToolParametersWhat It Does
get_node_defsnoneList all available node definitions (IOSv, NX-OS, IOS-XR, etc.)
create_nodelab_id/lab_title, node_def, label, x, yAdd a node to a lab
get_nodeslab_id/lab_titleList all nodes in a lab
get_nodelab_id/lab_title, node_id/node_labelGet details of a specific node

Interface Management

ToolParametersWhat It Does
create_interfacelab_id/lab_title, node_id/node_label, slot?Create a new interface on a node
get_interfaceslab_id/lab_title, node_id/node_labelList all interfaces on a node
get_interfacelab_id/lab_title, node_id/node_label, interface_id/interface_labelGet interface details

Link Management

ToolParametersWhat It Does
create_linklab_id/lab_title, src_node/src_label, src_intf, dst_node/dst_label, dst_intfCreate a link between two interfaces
get_linkslab_id/lab_titleList all links in a lab
get_linklab_id/lab_title, link_idGet link details
set_link_conditionlab_id/lab_title, link_id, bandwidth?, latency?, jitter?, loss?Set link conditioning (WAN simulation)
set_link_statelab_id/lab_title, link_id, stateSet link state (up/down) — simulate link failures

Annotations

ToolParametersWhat It Does
create_annotationlab_id/lab_title, annotation_type, content, x, y, width?, height?Add a text/shape annotation
get_annotationslab_id/lab_titleList all annotations
delete_annotationlab_id/lab_title, annotation_idRemove an annotation

Available Node Definitions

Common node types available in CML (use get_node_defs to get the full list):

Node Definition IDDescriptionTypical Use
iosvCisco IOSv (IOS 15.x)Routing, switching labs
iosvl2Cisco IOSv L2Layer 2 switching labs
iosxrv9000Cisco IOS XR 9000vSP, MPLS, Segment Routing
nxosv9000Cisco NX-OS 9000vData center, VXLAN
csr1000vCisco CSR 1000v (IOS-XE)SD-WAN, routing
cat8000vCisco Catalyst 8000vEnterprise routing
asavCisco ASAvFirewall labs
serverUbuntu/Alpine serverTraffic gen, testing
external_connectorExternal bridgeConnect lab to host/internet
unmanaged_switchUnmanaged L2 switchSimple L2 connectivity
wan_emulatorWAN emulatorAdd latency/loss between nodes

Workflow: Build Topology from Description

When the user describes a topology:

  1. Create the lab (or get an existing one via get_lab)
  2. Get node definitions: get_node_defs to know what's available
  3. Plan the layout: Calculate x,y coordinates for visual placement
    • Use a grid layout: 200px spacing horizontally, 200px vertically
    • Group by role: core in center, edge on sides, servers at bottom
  4. Create nodes: create_node for each device with meaningful labels
  5. Create interfaces: create_interface for each connection point
  6. Wire links: create_link to connect interface pairs
  7. Set conditions (if requested): set_link_condition for WAN links
  8. Add annotations: create_annotation for labels, IP addressing plans
  9. Report the topology: List all nodes, interfaces, and links

Layout Guidelines

When placing nodes, use this visual grid approach:

Topology Layout (x, y coordinates):

Layer 0 (Top):     Core routers         y=100
Layer 1:           Distribution          y=300
Layer 2:           Access / Leaf         y=500
Layer 3 (Bottom):  Servers / Endpoints   y=700

x spacing: 200px between nodes in the same layer
Center the topology: start x at 100, distribute evenly

Example for a 2-spine, 4-leaf topology:

Spine1: (300, 100)    Spine2: (500, 100)
Leaf1:  (100, 300)    Leaf2:  (300, 300)    Leaf3:  (500, 300)    Leaf4:  (700, 300)
Srv1:   (100, 500)    Srv2:   (300, 500)    Srv3:   (500, 500)    Srv4:   (700, 500)

Link Conditioning

Use set_link_condition to simulate real-world WAN characteristics:

ScenarioBandwidthLatencyJitterLoss
LAN(none)(none)(none)(none)
Metro Ethernet100 Mbps5 ms1 ms0%
WAN (good)50 Mbps20 ms5 ms0.1%
WAN (poor)10 Mbps100 ms20 ms1%
Satellite5 Mbps300 ms50 ms2%
Congested link1 Mbps200 ms100 ms5%

Workflow: Annotate Topology

After building a topology, add visual documentation:

  1. Title annotation: Lab name and purpose at the top
  2. IP addressing: Annotation blocks showing subnet assignments per link
  3. AS numbers: Label BGP AS boundaries
  4. Area labels: Mark OSPF areas, VRF names, VLAN IDs
  5. Notes: Any special instructions or test scenarios

Workflow: Simulate Link Failure

When testing network resilience:

  1. Get the link: get_links to find the link ID between the two nodes
  2. Capture baseline: Use execute_command to check routing tables before failure
  3. Bring link down: set_link_state with state "down"
  4. Observe convergence: Execute show commands on affected nodes (OSPF neighbors, BGP summary, routing table)
  5. Optionally capture traffic: Use cml-packet-capture to capture reconvergence traffic
  6. Restore link: set_link_state with state "up"
  7. Verify recovery: Confirm routing adjacencies re-establish
  8. Report: Document failover/failback time and behavior

Important Rules

  • Always use get_node_defs first to verify available node types before creating nodes
  • Create interfaces before links — you need interface IDs to wire links
  • Use descriptive labels — "R1-Core" not "Node1"
  • Plan before building — figure out the full topology before starting to create nodes
  • Lab must be STOPPED to add nodes — cannot modify topology of a running lab
  • Position nodes logically — hierarchical layout makes the topology readable in CML UI
  • Record in GAIT — log topology creation for audit trail

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 Topology Builder AI skill do?

Build CML topologies — add nodes, create interfaces, wire links, set link conditioning, add annotations. Use when building a network topology in CML, adding routers or switches to a lab, wiring links between nodes, or simulating WAN conditions.

Why use Cml Topology Builder on TypingMind?

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

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

Which AI models can use Cml Topology Builder?

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 Topology Builder?

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

Is the Cml Topology Builder 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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