gstack

Overview of gstack skill

gstack is a browser-driven AI skill for QA testing, dogfooding, and bug capture. It is best for people who need a headless browser workflow that can open real pages, click through UI, verify state, compare before/after, and produce screenshot-backed evidence instead of a speculative answer. If your goal is to validate a deployment, test a form, inspect responsive behavior, or file a bug with proof, the gstack skill is built for that job.

What gstack is best at

The core value of the gstack skill is practical verification. It is tuned for tasks like “open this page and check the signup flow,” “confirm the latest deploy didn’t break checkout,” or “capture annotated screenshots of the failing state.” That makes gstack especially useful for QA, PMs, designers, and engineers who want real browser interaction, not a text-only summary.

Why it is different from a generic prompt

A normal prompt can describe a test plan, but gstack is oriented around execution discipline: browser navigation, interaction, layout checks, screenshots, and bug evidence. It is more useful when the output must be trustworthy and reproducible. The tradeoff is that it works best when you provide a concrete target, a clear success condition, and the relevant environment context.

Best fit for UI Design and release checks

If you are using gstack for UI Design, think of it as a way to verify the designed experience in a live browser: spacing, alignment, responsive breakpoints, dialog behavior, and visual regressions. It is also a strong fit for release validation because it can check the path users actually take after deployment, not just the code path you expect.

How to Use gstack skill

Install gstack skill

Install with:

npx skills add garrytan/gstack --skill gstack

After install, start with the bundled SKILL.md, then inspect supporting files that affect how the skill behaves in practice. In this repo, the most useful early reads are README.md, AGENTS.md, metadata.json, and the scripts/ and agents/ folders.

What to tell the skill

Give gstack a specific browser task, not a vague objective. Strong inputs include the target URL or app, the user role, the flow to test, the expected result, and any hard constraints like auth state, viewport size, or whether screenshots are required. For example: “Use gstack to open the staging site, log in as a tester, complete checkout with a coupon, verify the success state, and capture annotated screenshots if anything fails.”

A good gstack usage workflow

Start with a narrow first run: open the page, confirm the entry state, then move through one critical path at a time. If the flow is complex, break it into steps such as login, navigation, action, and verification. This reduces ambiguity and helps gstack return evidence instead of guesswork. For UI Design review, specify the viewport and the exact screen or component to inspect, since responsive issues often only show up at particular sizes.

Files and repo paths to read first

If you are learning the skill or debugging behavior, read SKILL.md first, then AGENTS.md for the broader workflow map. Also inspect scripts/ for operational helpers and agents/openai.yaml for the default interface description. These files tell you how gstack is meant to be triggered and what kind of browser work it expects to perform.

gstack skill FAQ

Is gstack only for QA engineers?

No. The gstack skill is useful anywhere you need a real browser check: product QA, deployment validation, design review, support triage, and dogfooding. If the task depends on visual state or interactive behavior, gstack is usually a better fit than a plain prompt.

When should I not use gstack?

Do not use gstack when you only need static reasoning, code review, or a purely textual answer. It is also a poor fit if you cannot define the page, user flow, or expected result well enough to verify it in a browser. In those cases, a simpler prompt or a different skill will be faster.

How does gstack compare with ordinary prompts?

Ordinary prompts can suggest a test checklist. gstack is for actually executing the browser workflow and collecting evidence. That means better trust for UI bugs and release checks, but also a stronger need for setup details. The gstack skill works best when the task is observable in the browser.

Is gstack beginner-friendly?

Yes, if you can describe what you want checked. You do not need to know the full repo internals to get value, but you do need to be specific about the page, the flow, and the expected outcome. Beginners usually get better results when they ask for one critical path first instead of a full end-to-end audit.

How to Improve gstack skill

Give stronger inputs for better browser evidence

The best way to improve gstack output is to provide a complete test brief: URL, environment, login state, viewport, steps, and success criteria. For example, “Verify the pricing page at 1440px and 390px, compare desktop and mobile layouts, and flag any clipped text or broken CTA behavior.” That is much better than “check the UI.”

Avoid the most common failure mode

The most common failure mode is underspecification. If the skill has to infer the page, the user role, or what counts as success, the result will be noisier and less useful. For gstack for UI Design, include the exact component or screen, the breakpoints that matter, and whether you want visual polish, functional behavior, or both.

Iterate from evidence, not opinions

If the first run finds a problem, refine the next request around the evidence: reference the broken state, the screenshot, the exact selector or step, and the expected vs actual result. That makes the second pass more targeted and helps gstack produce a cleaner reproduction or a more accurate verification.

Use the repo as a workflow reference

To improve your gstack guide over time, read the operational files that shape the skill’s behavior and update your own prompts to match them. The useful habit is to treat gstack as a browser execution tool with a repeatable input format, not as a generic assistant. Clear task framing, explicit pass/fail criteria, and the right viewport or auth context will materially improve every run.