Browser Viz Verify logo

Browser Viz Verify

Community
automateyournetwork
browser-viz-verify

Verifies that a NetClaw-generated visualization HTML file (three.js, canvas, drawio, UML, markmap) actually renders correctly — screenshot, console-error check, and an optional Lighthouse audit. Use immediately after generating any browser-based visualization output, to close the QA gap that otherwise requires a human to manually open the file. Never touches an external site or the authenticated browser profile.

Overview

Publisherautomateyournetwork
Repositorynetclaw
Skill namebrowser-viz-verify
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 Browser Viz Verify 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/browser-viz-verify
  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/browser-viz-verify .claude/skills/browser-viz-verify
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Browser Viz Verify 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 Browser Viz Verify 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 Browser Viz Verify 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.

Browser Visualization Verify Skill

Purpose

NetClaw ships several skills that generate browser-based visualization outputs — threejs-network-viz, canvas-network-viz, drawio-diagram, uml-diagram, markmap-viz. Until now, confirming that a generated file actually rendered correctly (no blank canvas, no JavaScript errors, no broken layout) required a human to manually open it in a browser. This skill closes that gap: it opens the file itself in a controlled, headless Chrome session, takes a screenshot, reads the console for errors, and optionally runs a Lighthouse audit — then reports a clear verdict.

This skill never navigates to a remote URL and never touches the persistent authenticated browser profile used by browser-gui-inspect. It only ever opens local file:// paths. See specs/048-chrome-devtools-browser-inspection/ for the full spec, research, and design behind this skill.

MCP Server

This skill uses tools provided by the chrome-devtools-mcp server (official Chrome DevTools team package, chrome-devtools-mcp on npm), spawned locally via npx -y chrome-devtools-mcp@latest over stdio transport. See mcp-servers/chrome-devtools-mcp/README.md.

Environment Variables

None. chrome-devtools-mcp takes all configuration as CLI flags, not env vars. This skill always runs headless against a local file — it never needs --headless=false or the persistent profile's authenticated sessions.


Workflow: Verify a Generated Visualization (P1 — MVP)

Input:

  • file_path (required) — absolute path to the generated visualization HTML file
  • run_audit (optional, default false) — whether to also run a Lighthouse audit

Step 1: Confirm the file exists

Before opening a browser session, verify file_path exists on disk. If it does not, stop and return:

verdict: "file_not_found"

Do not attempt to open a browser session for a path that doesn't exist.

Step 2: Open the file in a headless session

Tool: new_page
Args: { "url": "file://<file_path>" }

Step 3: Wait for the page to settle

Async-rendered visualizations (three.js scenes, canvas drawings) may take a moment to finish drawing. Use a bounded wait rather than capturing immediately:

Tool: wait_for
Args: { "text": <a string known to appear once rendering completes, e.g. a legend label>, "timeoutMs": 15000 }

If the wait times out, stop and return:

verdict: "timed_out"

Step 4: Capture a screenshot

Tool: take_screenshot

Save the result as the screenshot_path artifact, following the same output-directory convention as other NetClaw skill artifacts.

Step 5: Read the console

Tool: list_console_messages

Classify the result:

  • No errors/warnings present → verdict: "rendered_clean"
  • One or more error/warning messages present → verdict: "rendered_with_errors", and include the message text in console_errors — don't just report a blank/inconclusive screenshot when the console explains exactly what broke.

Step 6: Optional Lighthouse audit

If run_audit is true:

Tool: lighthouse_audit

Summarize the findings (performance, accessibility) into audit_summary. Skip this step entirely when run_audit is false — it adds meaningful runtime and isn't needed for a quick render check.

Step 7: Close the session

Tool: close_page

Output

{
  "verdict": "rendered_clean" | "rendered_with_errors" | "timed_out" | "file_not_found",
  "screenshot_path": "<path to captured screenshot>",
  "console_errors": ["<message>", ...],
  "audit_summary": { ... }   // present only if run_audit was true
}

Invoking from Other Skills

threejs-network-viz, canvas-network-viz, drawio-diagram, uml-diagram, and markmap-viz should each call browser-viz-verify automatically immediately after writing their generated HTML file, passing the freshly written file's path. This turns "did it render?" from a question the operator has to answer manually into a QA step NetClaw answers itself, within the ~30-second budget described in the spec's success criteria (SC-001). If browser-viz-verify returns rendered_with_errors or timed_out, surface that to the operator alongside the generated file rather than silently reporting success.

Error Handling

VerdictMeaningWhat to tell the operator
rendered_cleanScreenshot captured, no console errorsVisualization is good to share/open
rendered_with_errorsScreenshot captured, but console shows JS errors/warningsShow the exact console message(s) — don't just say "something went wrong"
timed_outPage never reached the expected rendered state within the bounded waitThe generated file may be malformed, or reference a resource that failed to load
file_not_foundfile_path doesn't existConfirm the visualization skill actually wrote the file before calling this skill

Constitution Notes

This skill is purely observational (Constitution I) — it never performs a write against any system, requires no ITSM gating (III), and needs no bespoke audit trail beyond DefenseClaw's generic tool-call logging (IV) since it is read-only and touches no external or authenticated system.

Frequently asked questions

What does the Browser Viz Verify AI skill do?

Verifies that a NetClaw-generated visualization HTML file (three.js, canvas, drawio, UML, markmap) actually renders correctly — screenshot, console-error check, and an optional Lighthouse audit. Use immediately after generating any browser-based visualization output, to close the QA gap that otherwise requires a human to manually open the file. Never touches an external site or the authenticated browser profile.

Why use Browser Viz Verify on TypingMind?

Because you install it once and use it with any model. Browser Viz Verify 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 Browser Viz Verify in TypingMind?

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

Which AI models can use Browser Viz Verify?

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 Browser Viz Verify?

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

Is the Browser Viz Verify 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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