Canvas Network Viz

Community

automateyournetwork

canvas-network-viz

Canvas/A2UI inline network visualizations — topology maps, health dashboards, alert cards, change timelines, config diffs, path traces, and health scorecards rendered directly in the OpenClaw chat interface. Consumes existing MCP server data (pyATS, Grafana, Prometheus, ServiceNow, SuzieQ, Batfish) and outputs A2UI JSON for Canvas rendering. Use when the operator asks to see a network map, device dashboard, alert summary, change request timeline, config diff, forwarding path trace, or health scorecard.

Overview

Publisher	automateyournetwork
Repository	`netclaw`
Skill name	`canvas-network-viz`
Stars	680
Forks	189
Bundled files	20
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.
20 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by automateyournetwork on GitHub. Read the source before you install it.

Installation

Install the Canvas Network Viz 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/canvas-network-viz
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/automateyournetwork/netclaw/tree/main/workspace/skills/canvas-network-viz

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

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/canvas-network-viz .claude/skills/canvas-network-viz

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

Use it in TypingMind

Enable Canvas Network Viz 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 Canvas Network Viz 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 Canvas Network Viz 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.

Canvas Network Visualization

Overview

This skill renders inline network visualizations in the OpenClaw chat interface using the Canvas/A2UI framework. It does NOT establish direct device connections or create new MCP servers. All data is sourced from existing MCP tools.

Visualization Types

Type	Component	Data Sources	Trigger
Topology Map	`topology-map`	pyATS CDP/LLDP, health metrics	"show network topology"
Dashboard Panel	`dashboard-panel`	pyATS, Grafana, Prometheus	"show health dashboard for {device}"
Alert Card	`alert-card`	Grafana alerts, Prometheus alertmanager	"show current alerts"
Change Timeline	`change-timeline`	ServiceNow	"show change request {CR} status"
Diff View	`diff-view`	pyATS config/route/ACL	"show config diff for {device}"
Path Trace	`path-trace`	pyATS, SuzieQ	"trace path from {src} to {dst}"
Health Scorecard	`health-scorecard`	pyATS, Grafana, Prometheus	"show health scorecard for {site}"

How It Works

Operator requests a visualization via natural language
Skill identifies visualization type from request pattern
Data is fetched from relevant MCP servers via existing tools
Data is transformed into the visualization-specific content model
A2UI JSON envelope is built with component type, props, and content
Canvas framework renders the visualization inline in chat
GAIT audit log entry is emitted for the visualization event

Output Format

All visualizations produce A2UI JSON:

json
{
  "a2ui": {
    "version": "1.0",
    "type": "canvas",
    "component": "<visualization-type>",
    "props": {
      "id": "<uuid>",
      "title": "<title>",
      "timestamp": "<ISO 8601>",
      "dataSources": [...],
      "scope": {...},
      "warnings": [...],
      "content": {...}
    }
  }
}

Graceful Degradation

If a data source is unavailable, partial data is rendered with warnings
If no data is available at all, an error-card is returned with guidance
Health status defaults to "unknown" (gray) when metrics are missing
Large topologies (200+ nodes) are automatically clustered by site

Integration with Other Skills

Skill	Integration
gait-session-tracking	All visualization events are GAIT-logged
pyats-topology	CDP/LLDP discovery data for topology maps
pyats-health-check	Health metrics for node coloring and dashboards
grafana-observability	Prometheus metrics, alerts, dashboard data
prometheus-monitoring	Direct PromQL queries for metrics
servicenow-change-workflow	Change request lifecycle data

Important Rules

Read-only: This skill never modifies network devices or MCP server state
No new credentials: Uses existing MCP server connections only
Complements Three.js HUD: Does not replace ui/netclaw-visual/
GAIT mandatory: Every visualization generation is audit-logged
WCAG 2.1 AA: Color scales meet accessibility contrast requirements

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Canvas Network Viz AI skill do?

Why use Canvas Network Viz on TypingMind?

Because you install it once and use it with any model. Canvas Network Viz 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 Canvas Network Viz in TypingMind?

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

Which AI models can use Canvas Network Viz?

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 Canvas Network Viz?

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

Is the Canvas Network Viz 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

Canvas Network Visualization

Overview

Visualization Types

How It Works

Output Format

Graceful Degradation

Integration with Other Skills

Important Rules

Bundled files

Frequently asked questions

Related AI Skills

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