automation-browser
Skill26 starsChanged 32 days agoMITView on GitHub
Drive a real browser against an in-scope web app with Playwright / agent-browser: automated login, form and payload submission through the UI, scraping JS-rendered pages, request/response interception, and evidence screenshots. Load on "browser automation", "fill this form", "submit payload", "screenshot this page", automated login, headless crawling, or UI-driven XSS testing. Signals: Playwright, agent-browser, headless, @e1 element refs, networkidle, DOM interaction.
- Installs packages
2 other projects use a version of this.
Adopted by
Most recently taken up by
- NoorQureshi/roninword for word, first seen Oct 11, 2026
- NoorQureshi/security-skillsword for word, first seen Oct 11, 2026
Other versions2 projects use a version of this.
Word for word · 2
- NoorQureshi/security-skills★ 27100% same
- NoorQureshi/ronin★ 26100% same
Edited · 0
None found.
Wrote their own version · 0
None found.
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository207 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- ad-adcsSkill
- ad-dacl-abuseSkill
- ad-delegation-abuseSkill
- ad-kerberoastingSkill
- ad-pivot-arsenalSkill
- ai-agent-tool-abuseSkill
- ai-insecure-output-handlingSkill
- ai-jailbreakSkill
- ai-llm-dosSkill
- ai-mcp-securitySkill
- ai-model-extractionSkill
- ai-prompt-injectionSkill
- ai-rag-poisoningSkill
- ai-sensitive-data-disclosureSkill
- ai-supply-chainSkill
- ai-system-prompt-leakageSkill
- api-auth-attacksSkill
- api-bolaSkill
- api-fuzzingSkill
- api-graphqlSkill
- api-grpcSkill
- api-mass-assignmentSkill
- api-mongo-agg-facet-bypassSkill
- api-testing-checklistSkill
- api-versioningSkill
- automation-nuclei-templatesSkill
- automation-recon-pipelineSkill
- cloud-azureSkill
- cloud-container-escapeSkill
- cloud-docker-api-abuseSkill
- cloud-docker-registrySkill
- cloud-gcpSkill
- cloud-iam-privescSkill
- cloud-imds-ssrfSkill
- cloud-kubernetesSkill
- cloud-s3-exposureSkill
- code-review-cicdSkill
- code-review-cppSkill
- code-review-dangerous-sinksSkill
- code-review-dotnetSkill
- code-review-goSkill
- code-review-iacSkill
- code-review-javaSkill
- code-review-methodologySkill
- code-review-nodejsSkill
- code-review-phpSkill
- code-review-pythonSkill
- code-review-rubySkill
- code-review-rustSkill
- code-review-secrets-detectionSkill
- code-review-soliditySkill
- crypto-oracle-attacksSkill
- crypto-rsa-attacksSkill
- ctf-cryptoSkill
- ctf-forensicsSkill
- ctf-methodologySkill
- ctf-pwnSkill
- ctf-revSkill
- The first 60 shown.
The file
We split this skill into the rules it gives an agent
3 rules. About 0 are common, 1 is distinctive, and 2 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 48
Always snapshot before acting — refs are per-page-state, never guess them.
- Very specific: line 49
Drop to the Playwright Node API: when you need cookies/localStorage extraction, request interception or response tampering (e.g.
- Distinctive: line 55
Adjacent: desktop GUI automation: If the target is a Windows desktop app (thick client, IDA, x64dbg) rather than a web page, the same …
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Browser automation (Playwright / agent-browser)
When it applies
The in-scope target (scope.txt, tradecraft-scope-roe) needs a real browser, not raw HTTP:
multi-step or JS-heavy login flows, pages that render client-side, payloads that must go through
the UI (XSS into a live DOM, CSRF flows), evidence screenshots, or scraping behind a session. For
pure request replay use Burp/curl instead; honor bug-bounty rate limits in roe.md — automation
multiplies request volume.
Why it works
A scripted browser executes the app's JavaScript, holds cookies/session like a real user, and sees
the post-render DOM — so guards that defeat raw HTTP (JS challenges, dynamic forms) just work. The
agent-browser CLI exposes the accessibility tree as stable @eN element refs, which survive
layout changes better than CSS selectors; the Playwright Node API adds network interception,
storage extraction, and screenshots for everything the CLI can't do.
Method
- Install once:
npm install -g playwright agent-browser && npx playwright install. - Core CLI loop — open, snapshot, act, verify, close:
Alwaysagent-browser open "https://target.com/login" agent-browser snapshot -i # interactive elements only → @e1, @e2... agent-browser fill @e2 "admin" agent-browser type @e3 "password" # type, not fill, when JS listens for input events agent-browser click @e4 agent-browser wait --load networkidle agent-browser get url # did we land in the authenticated area? agent-browser close # mandatory — leaked processes hang later runssnapshotbefore acting — refs are per-page-state, never guess them. - Drop to the Playwright Node API when you need cookies/localStorage extraction, request
interception or response tampering (e.g. flip
role: user → adminto test client-side authorization), orfullPagescreenshots for evidence. Full command and API reference, plus pentest patterns (auto-login, XSS injection, batch payload loops):cheatsheet.md. - Route through Burp (
proxy: { server: 'http://127.0.0.1:8080' }+ignoreHTTPSErrors: true) so every automated request lands in your proxy history for manual follow-up. - Adjacent: desktop GUI automation. If the target is a Windows desktop app (thick client, IDA,
x64dbg) rather than a web page, the same agent-driven model exists in
OpenReverse: UIA mode for standard Windows controls,
CUA (vision-driven) mode for custom-rendered GUIs, plus a built-in mitmproxy lane for observing
the app's traffic. Install and command shapes are in the cheatsheet; pair it with
reverse-eng-thick-client.
Gotchas
- Leaked processes — a missing
agent-browser closeleaves a browser that breaks the nextopen; close first when a session wedges. - Stale element refs — any navigation or re-render invalidates
@eN; re-snapshot -iafter every page change instead of reusing old refs. fillsilently no-ops on inputs with JS listeners — usetype(per-character events).- Timing — after submits wait on
networkidle(or a specific selector/response), not fixed sleeps; usedomcontentloadedfor slow heavy pages. - Headless detection — some apps behave differently headless (anti-bot); run headed or tune the user agent when behavior diverges from manual testing.
Verify success
The flow completed end-to-end (final URL/DOM confirms the authenticated or post-submit state) and evidence is on disk: screenshot, captured response, or extracted storage — reproducible from the commands you ran.
References
Playwright docs (playwright.dev); agent-browser CLI; OpenReverse (github.com/zhexulong/openreverse).
Portions adapted from reverse-skill by zhaoxuya520, MIT License.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

