Verify logo

Verify

OrganizationPopular
zenbu-labs
verify

Drive an engine app headlessly in a pty, record a video of the whole verification, and open a summary page (video + timeline + checks) with pixel open.

Overview

Publisherzenbu-labs
Repositoryterminal-browser
Skill nameverify
Stars
3.6K
Forks
173
Bundled files
Instructions only
LicenseMIT
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 zenbu-labs on GitHub. Read the source before you install it.

Installation

Install the 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/zenbu-labs/terminal-browser/tree/main/.claude/skills/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/zenbu-labs/terminal-browser.git /tmp/terminal-browser
mkdir -p .claude/skills
cp -r /tmp/terminal-browser/.claude/skills/verify .claude/skills/verify
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable 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 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 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.

Apps here render via the kitty graphics protocol, so they can be verified without a real terminal. Every verification is recorded: the harness in tools/verify-recorder/ captures every frame the app emits, overlays your inputs (click ripples, caption bar), encodes a video, and generates a summary page. Do not hand-roll one-off pty scripts that only dump PNGs.

Writing a verification

Write a driver script (in /tmp is fine) using the checked-in package:

python
import sys
sys.path.insert(0, "<repo>/tools/verify-recorder")
from driver import Driver
from recorder import Recorder

rec = Recorder("wheel-pan", title="Wheel pan keeps cursor anchored")
d = Driver(["<repo>/engine/target/debug/typing"], rec,
           cols=120, rows=32, xpixel=1200, ypixel=800)

d.pump(3.0)                                  # pump between actions so frames arrive
rec.check("app painted", d.frame_size is not None, f"{d.frame_size}")
w, h = d.frame_size                          # REAL framebuffer size — always use this

d.text("hello", "type into editor")          # every input takes a description
d.click(w // 2, h // 3, "select the note")   # mouse coords are pixels (1016 mode)
d.wheel(w // 2, h // 2, down=True, n=3, description="scroll content")
d.pump(1.0)
rec.check("scroll redrew", len(rec.frames) > 40, f"{len(rec.frames)} frames")
rec.still("after-scroll")                    # named snapshot for the summary page

d.stop("ctrl+c")                             # or "ctrl+q" depending on the app
rec.finish()                                 # composites markers, encodes mp4, writes summary
  • Driver spawns the argv in a pty (TERM=xterm-kitty, TIOCSWINSZ with pixel dims, answers the \x1b[?1016$p mouse probe), decodes kitty a=T,f=32,o=z frames, and feeds them to the recorder. Node apps: spawn ["npx", "tsx", "src/main.tsx", ...] with cwd= the package dir (tsx resolves tsconfig from cwd; a wrong cwd silently drops jsx config).
  • Input methods: key("enter"/"esc"/"ctrl+q"/"super+shift+z"), text, click, press/drag/release (a drag needs all three — click sends press+release together), move, wheel. Descriptions become the video caption bar and the summary timeline — write what the step is testing.
  • rec.check(name, ok, detail) for every assertion; rec.still(name) to pin the current frame into the summary.
  • Give checks real assertions (frame deltas, decoded pixel colors via recorder.png_read(rec.frames[-1]["path"])) — the summary shows pass/fail.

Ending a verification (required)

rec.finish() prints the run dir and summary path. Always end by opening the summary in a split:

pixel open file:///tmp/verify-runs/<name>-<stamp>/summary.html

That page is the deliverable: what was tested (clickable timeline that seeks the video), the checks table, the stills, and the video of the whole run. Watch out for FAIL rows before declaring the verification passed.

Gotchas

  • The engine rounds the window down to the cell grid, so the framebuffer can be narrower than the requested winsize. Take coordinates from d.frame_size, never from the requested pixels, or clicks land ~5% off.
  • Keep pumping after quit (d.stop does) or the exit is never observed.
  • Escape must be kitty CSI-u (d.key("esc") handles it); a bare \x1b makes the app swallow the next escape sequence as literal text.
  • If a press lands on a node without handlers, the engine dispatches the click at the release position — a missed drag can silently click something else.
  • Hover state only updates on move events; end interactions with a move if the screenshot should show hover styling.
  • Apps taking a file path argv need an ABSOLUTE path (their cwd is the package dir).
  • Run artifacts live in /tmp/verify-runs/<name>-<stamp>/: frames/, events.jsonl, run.json, verification.mp4, summary.html.

Frequently asked questions

What does the Verify AI skill do?

Drive an engine app headlessly in a pty, record a video of the whole verification, and open a summary page (video + timeline + checks) with pixel open.

Why use Verify on TypingMind?

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

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

Which AI models can use 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 Verify?

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

Is the Verify AI skill free?

Yes. It is published on GitHub by zenbu-labs under the MIT 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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