Aside Browser Driver
garrytan/gstack
Drives a real browser through Aside so the agent can open a page, read it, click through a flow, take screenshots and check console errors.
Explores a web app with the agent-browser CLI to find bugs and UX problems, then writes a report with screenshots, repro videos and step-by-step reproduction for each issue.
$ npx skills add vercel-labs/agent-browser --skill dogfood -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install vercel-labs/agent-browser dogfood --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/vercel-labs/agent-browser.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skill-data/dogfood .claude/skills/dogfood && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "dogfood" agent skill from https://github.com/vercel-labs/agent-browser/tree/main/skill-data/dogfood into .claude/skills/dogfood/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dogfood", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/vercel-labs/agent-browser/tree/main/skill-data/dogfoodType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add vercel-labs/agent-browser --skill dogfood -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install vercel-labs/agent-browser dogfood --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/vercel-labs/agent-browser.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skill-data/dogfood .agents/skills/dogfood && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "dogfood" agent skill from https://github.com/vercel-labs/agent-browser/tree/main/skill-data/dogfood into .agents/skills/dogfood/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dogfood", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add vercel-labs/agent-browser --skill dogfood -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install vercel-labs/agent-browser dogfood --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/vercel-labs/agent-browser.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skill-data/dogfood .cursor/skills/dogfood && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "dogfood" agent skill from https://github.com/vercel-labs/agent-browser/tree/main/skill-data/dogfood into .cursor/skills/dogfood/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dogfood", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/vercel-labs/agent-browser.git --path skill-data/dogfood--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add vercel-labs/agent-browser --skill dogfood -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install vercel-labs/agent-browser dogfood --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/vercel-labs/agent-browser.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skill-data/dogfood .gemini/skills/dogfood && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "dogfood" agent skill from https://github.com/vercel-labs/agent-browser/tree/main/skill-data/dogfood into .gemini/skills/dogfood/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dogfood", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install vercel-labs/agent-browser dogfoodInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add vercel-labs/agent-browser --skill dogfood -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/vercel-labs/agent-browser.git skills-src && mkdir -p .github/skills && cp -r skills-src/skill-data/dogfood .github/skills/dogfood && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "dogfood" agent skill from https://github.com/vercel-labs/agent-browser/tree/main/skill-data/dogfood into .github/skills/dogfood/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dogfood", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add vercel-labs/agent-browser --skill dogfood -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install vercel-labs/agent-browser dogfood --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/vercel-labs/agent-browser.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skill-data/dogfood .opencode/skills/dogfood && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "dogfood" agent skill from https://github.com/vercel-labs/agent-browser/tree/main/skill-data/dogfood into .opencode/skills/dogfood/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dogfood", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
dogfoodExplores a web app with the agent-browser CLI to find bugs and UX problems, then writes a report with screenshots, repro videos and step-by-step reproduction for each issue.
You give the agent a target URL, the only required input; the session name, output directory, scope and authentication all have defaults. It sets up an output folder with screenshot and video subfolders and a report copied from a template, starts a named agent-browser session, signs in if the app needs it and saves the auth state, then takes an annotated screenshot and a snapshot to map the app's main sections before visiting them.
The skill insists on calling the agent-browser binary directly, because the direct binary uses a fast Rust client while going through npx is noticeably slower, and it allows Bash calls to agent-browser for that reason. When login needs a one-time code sent by email, the agent asks you and waits for your reply. Findings go into a structured report that carries full reproduction evidence for every issue, and an issue-taxonomy reference file defines how problems are categorized.
6 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit d957091. It shows what the files ask for, not the result of running them.
Pre-approves these tools, so the agent can use them without asking each time:
Bash(agent-browser:*)Bash(npx agent-browser:*)From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
npxFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use npx, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Dogfood Exploratory QA loads about 2.7k tokens when it runs, and up to ~3.6k if it reads all its reference files. Until then it costs about 117 tokens; SKILL.md has 1,114 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from vercel-labs/agent-browser at commit d957091, republished under its Apache-2.0 licence (© vercel-labs). 1,114 words, ~2,711 tokens.
.claude/skills/dogfood/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.Systematically explore a web application, find issues, and produce a report with full reproduction evidence for every finding.
Only the Target URL is required. Everything else has sensible defaults -- use them unless the user explicitly provides an override.
| Parameter | Default | Example override |
|---|---|---|
| Target URL | (required) | vercel.com, http://localhost:3000 |
| Session name | Slugified domain (e.g., vercel.com -> vercel-com) | --session my-session |
| Output directory | ./dogfood-output/ | Output directory: /tmp/qa |
| Scope | Full app | Focus on the billing page |
| Authentication | None | Sign in to user@example.com |
If the user says something like "dogfood vercel.com", start immediately with defaults. Do not ask clarifying questions unless authentication is mentioned but credentials are missing.
Always use agent-browser directly -- never npx agent-browser. The direct binary uses the fast Rust client. npx routes through Node.js and is significantly slower.
1. Initialize Set up session, output dirs, report file
2. Authenticate Sign in if needed, save state
3. Orient Navigate to starting point, take initial snapshot
4. Explore Systematically visit pages and test features
5. Document Screenshot + record each issue as found
6. Wrap up Update summary counts, close sessionmkdir -p {OUTPUT_DIR}/screenshots {OUTPUT_DIR}/videosCopy the report template into the output directory and fill in the header fields:
cp {SKILL_DIR}/templates/dogfood-report-template.md {OUTPUT_DIR}/report.mdStart a named session:
agent-browser --session {SESSION} open {TARGET_URL}
agent-browser --session {SESSION} wait --load domcontentloadedIf the app requires login:
agent-browser --session {SESSION} snapshot -i
# Identify login form refs, fill credentials
agent-browser --session {SESSION} fill @e1 "{EMAIL}"
agent-browser --session {SESSION} fill @e2 "{PASSWORD}"
agent-browser --session {SESSION} click @e3
# Replace this with the target app's post-login URL, text, or JS condition:
agent-browser --session {SESSION} wait --url "{POST_LOGIN_URL_PATTERN}"
# Or:
# agent-browser --session {SESSION} wait --text "{POST_LOGIN_TEXT}"
# agent-browser --session {SESSION} wait --fn "{POST_LOGIN_CONDITION}"For OTP/email codes: ask the user, wait for their response, then enter the code.
After successful login, save state for potential reuse:
agent-browser --session {SESSION} state save {OUTPUT_DIR}/auth-state.jsonTake an initial annotated screenshot and snapshot to understand the app structure:
agent-browser --session {SESSION} screenshot --annotate {OUTPUT_DIR}/screenshots/initial.png
agent-browser --session {SESSION} snapshot -iIdentify the main navigation elements and map out the sections to visit.
Read references/issue-taxonomy.md for the full list of what to look for and the exploration checklist.
Strategy -- work through the app systematically:
At each page:
agent-browser --session {SESSION} snapshot -i
agent-browser --session {SESSION} screenshot --annotate {OUTPUT_DIR}/screenshots/{page-name}.png
agent-browser --session {SESSION} errors
agent-browser --session {SESSION} consoleUse your judgment on how deep to go. Spend more time on core features and less on peripheral pages. If you find a cluster of issues in one area, investigate deeper.
Steps 4 and 5 happen together -- explore and document in a single pass. When you find an issue, stop exploring and document it immediately before moving on. Do not explore the whole app first and document later.
Every issue must be reproducible. When you find something wrong, do not just note it -- prove it with evidence. The goal is that someone reading the report can see exactly what happened and replay it.
Choose the right level of evidence for the issue:
These require user interaction to reproduce -- use full repro with video and step-by-step screenshots:
agent-browser --session {SESSION} record start {OUTPUT_DIR}/videos/issue-{NNN}-repro.webmagent-browser --session {SESSION} screenshot {OUTPUT_DIR}/screenshots/issue-{NNN}-step-1.png
sleep 1
# Perform action (click, fill, etc.)
sleep 1
agent-browser --session {SESSION} screenshot {OUTPUT_DIR}/screenshots/issue-{NNN}-step-2.png
sleep 1
# ...continue until the issue manifestssleep 2
agent-browser --session {SESSION} screenshot --annotate {OUTPUT_DIR}/screenshots/issue-{NNN}-result.pngagent-browser --session {SESSION} record stopThese are visible without interaction -- a single annotated screenshot is sufficient. No video, no multi-step repro:
agent-browser --session {SESSION} screenshot --annotate {OUTPUT_DIR}/screenshots/issue-{NNN}.pngWrite a brief description and reference the screenshot in the report. Set Repro Video to N/A.
For all issues:
Append to the report immediately. Do not batch issues for later. Write each one as you find it so nothing is lost if the session is interrupted.
Increment the issue counter (ISSUE-001, ISSUE-002, ...).
Aim to find 5-10 well-documented issues, then wrap up. Depth of evidence matters more than total count -- 5 issues with full repro beats 20 with vague descriptions.
After exploring:
### ISSUE- block must be reflected in the totals.agent-browser --session {SESSION} closesnapshot -i — for finding clickable/fillable elements (buttons, inputs, links)snapshot (no flag) — for reading page content (text, headings, data lists)rm screenshots, videos, or the report mid-session. Do not close the session and restart. Work forward, not backward.type instead of fill -- it types character-by-character. Use fill only outside of video recording when speed matters.sleep 1 between actions and sleep 2 before the final result screenshot. Videos should be watchable at 1x speed -- a human reviewing the report needs to see what happened, not a blur of instant state changes.agent-browser commands in a single shell call when they are independent (e.g., agent-browser ... screenshot ... && agent-browser ... console). Use agent-browser --session {SESSION} scroll down 300 for scrolling -- do not use key or evaluate to scroll.| Reference | When to Read |
|---|---|
| references/issue-taxonomy.md | Start of session -- calibrate what to look for, severity levels, exploration checklist |
| Template | Purpose |
|---|---|
| templates/dogfood-report-template.md | Copy into output directory as the report file |
© vercel-labs, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 2 other files (references) in skill-data/dogfood of vercel-labs/agent-browser.
Open the folder on GitHubat commit d957091
We found 9 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 8 other GitHub owners. This page covers the copy in vercel-labs/agent-browser, which our catalogue first saw on October 7, 2026.
Dogfood Exploratory QA next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Dogfood Exploratory QA this skillvercel-labs/agent-browser | 44k | 8 repos | ~2.7k | Automated safety check: Pass | Apache-2.0 | |
| Aside Browser Drivergarrytan/gstack | 136k | — | ~8.5k | Automated safety check: Notes | MIT | |
| Hands On Testktnyt/cclsp | 675 | — | ~1.7k | Automated safety check: Pass | MIT | |
| Diff-Driven Smoke TestsSkyvern-AI/skyvern | 23k | — | ~5.2k | Automated safety check: Pass | AGPL-3.0 | |
| Dogfoodredf0x1/camofox-browser | 412 | — | ~1.2k | Automated safety check: Pass | MIT | |
| Whole-App Health Sweepreticlehq/reticle | 1.2k | — | ~1.1k | Automated safety check: Pass | Apache-2.0 |
garrytan/gstack
Drives a real browser through Aside so the agent can open a page, read it, click through a flow, take screenshots and check console errors.
ktnyt/cclsp
Performs manual hands-on testing of a web application using playwright-cli.
Skyvern-AI/skyvern
Reads your git diff, writes a handful of happy-path browser smoke tests, runs them with Skyvern or Chrome DevTools MCP and posts screenshot evidence to the PR.
redf0x1/camofox-browser
QA testing workflow for CamoFox Browser — systematic testing with console capture, error detection, and Playwright tracing.
reticlehq/reticle
Sweeps a running web app by clicking every reachable control, then reports dead buttons, console errors, failed requests and mismatches between API data and the screen.
Skyvern-AI/skyvern
Reads your git diff, decides whether the change needs browser QA, API checks or repo tests, runs that validation and reports pass or fail with evidence.
vercel-labs/agent-browser
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking…
vercel-labs/agent-browser
Automates Electron desktop apps such as VS Code, Slack or Discord by connecting agent-browser to their Chrome DevTools Protocol port.
vercel-labs/agent-browser
Drives the Slack web app with the agent-browser CLI to check unread channels, search, read channel details and extract information, with screenshots as evidence.
vercel-labs/agent-browser
Core usage guide for the agent-browser CLI: the snapshot-and-ref workflow for navigating, clicking, filling forms, extracting data and running parallel sessions.
vercel-labs/agent-browser
Records a site's browser traffic into a HAR file, then builds a standalone client or CLI that calls its internal endpoints directly with no browser.
vercel-labs/agent-browser
Builds and validates experimental WebMCP tools that expose a web page's real workflows to agents, with a manifest, init script and evals compared against accessibility-tree automation.
Categories
Explores a web app with the agent-browser CLI to find bugs and UX problems, then writes a report with screenshots, repro videos and step-by-step reproduction for each issue. You give the agent a target URL, the only required input; the session name, output directory, scope and authentication all have defaults. It sets up an output folder with screenshot and video subfolders and a report copied from a template, starts a named agent-browser session, signs in if the app needs it and saves the auth state, then takes an annotated screenshot and a snapshot to map the app's main sections before visiting them.
Dogfood Exploratory QA fits situations like: running an exploratory QA pass over a web app before release; hunting for bugs on a site and getting reproducible evidence; checking one area, such as a billing page, for UX problems; handing findings to the responsible teams with screenshots and videos.
Run `npx skills add vercel-labs/agent-browser --skill dogfood -a claude-code`. Or copy the skill folder (skill-data/dogfood in vercel-labs/agent-browser) into .claude/skills/dogfood in your project. Claude Code loads it when a task matches its description.
Run `npx skills add vercel-labs/agent-browser --skill dogfood -a codex`. Or copy the skill folder (skill-data/dogfood in vercel-labs/agent-browser) into .agents/skills/dogfood in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add vercel-labs/agent-browser --skill dogfood -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/dogfood, .gemini/skills/dogfood, .github/skills/dogfood and .opencode/skills/dogfood in your project.
Going by SKILL.md and its folder, Dogfood Exploratory QA needs the command-line tools its instructions call (npx). Our summary lists: The agent-browser CLI; A target URL the agent can open. Its frontmatter pre-approves these tools: Bash(agent-browser:*), Bash(npx agent-browser:*).
SKILL.md contains no URLs. Its commands use npx, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Dogfood Exploratory QA is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.7k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 907 tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Dogfood Exploratory QA: Aside Browser Driver (garrytan/gstack, 136k stars), Hands On Test (ktnyt/cclsp, 675 stars), Diff-Driven Smoke Tests (Skyvern-AI/skyvern, 23k stars) and Dogfood (redf0x1/camofox-browser, 412 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
vercel-labs (a GitHub organization, an official publisher) maintains it in vercel-labs/agent-browser, which has 43,789 GitHub stars. The repository holds 10 skills in this directory. The repository was last updated on October 11, 2026.
Source: vercel-labs/agent-browser on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.