Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add LambdaTest/agent-skills --skill protractor-skillgit clone --depth 1 https://github.com/LambdaTest/agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/lambdatest/agent-skills/protractor-skill)<a href="https://agentmods.dev/skills/lambdatest/agent-skills/protractor-skill"><img src="https://agentmods.dev/badge/skills/lambdatest/agent-skills/protractor-skill/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/lambdatest/agent-skills/protractor-skill"><img src="https://agentmods.dev/badge/skills/lambdatest/agent-skills/protractor-skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 138 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00083 | $0.01054 |
| Opus 5.5 | $0.00033 | $0.00422 |
| Sonnet 5.5 | $0.00017 | $0.00211 |
| Haiku 4.5 | $0.00008 | $0.00105 |
Grade A, and why
protractor-skill scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Protractor Automation Skill (Deprecated)
Protractor reached end-of-life in 2023. Angular team recommends Playwright or Cypress.
For TestMu AI cloud execution, see reference/cloud-integration.md and shared/testmu-cloud-reference.md.
Core Patterns
Basic Test
describe('Login', () => {
beforeEach(async () => {
await browser.get('/login');
});
it('should login with valid credentials', async () => {
await element(by.model('email')).sendKeys('[email protected]');
await element(by.model('password')).sendKeys('password123');
await element(by.css('button[type="submit"]')).click();
expect(await browser.getCurrentUrl()).toContain('/dashboard');
expect(await element(by.css('.welcome')).getText()).toContain('Welcome');
});
it('should show error for invalid credentials', async () => {
await element(by.model('email')).sendKeys('[email protected]');
await element(by.model('password')).sendKeys('wrong');
await element(by.css('button[type="submit"]')).click();
expect(await element(by.css('.error')).isDisplayed()).toBe(true);
});
});
Angular-Specific Locators
element(by.model('ctrl.email')); // ng-model
element(by.binding('ctrl.username')); // Angular binding
element(by.exactBinding('ctrl.name')); // Exact binding
element(by.repeater('item in items')); // ng-repeat
element.all(by.repeater('item in items')).count(); // Count repeater
element(by.cssContainingText('.item', 'Active')); // CSS + text
element(by.buttonText('Submit')); // Button text
element(by.partialButtonText('Sub')); // Partial text
Page Objects
class LoginPage {
constructor() {
this.emailInput = element(by.model('email'));
this.passwordInput = element(by.model('password'));
this.loginButton = element(by.css('button[type="submit"]'));
this.errorMessage = element(by.css('.error'));
}
async login(email, password) {
await this.emailInput.sendKeys(email);
await this.passwordInput.sendKeys(password);
await this.loginButton.click();
}
}
// Usage
const loginPage = new LoginPage();
await loginPage.login('[email protected]', 'password123');
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 144 lines · 83 tokens per session scan A 41685d06678e
protractor-skill is a skill published in the GitHub repository LambdaTest/agent-skills (378 stars, last pushed 12d ago), licensed MIT. It adds 83 tokens to every session and 1,054 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
browse
Drive a real browser through Aside: open a page, read it, click through a flow, take screenshots, check console errors. (gstack).
cua-driver
Use Cua Driver for desktop or browser tasks that are awkward or unavailable through Bash/APIs, or when the user explicitly wants GUI interaction: app testing, visual bug reproduction, form filling, calendar entry, screenshots, and demo recording. Also covers Cua setup; not OpenAI Codex Computer Use or web research.
create-verification-skill
Create a repo-local verification skill and exhaustive feature map for driving a real app through its UI, CLI, or API. Use for "create a verification skill", "make a verify skill for this repo", or "document how agents can verify this app".
browser-qa
A browser-based quality check for deployed web pages and user flows. It uses browser automation to test rendering, navigation, forms, interactions, responsive behaviour, and accessibility-related issues.
webapp-testing
Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.
test-electron-app
Drive the real running PostHog Electron app (live tRPC, workspace-server, real data) over CDP with agent-browser. Connect to the running app on port 9222, test desktop changes against a local Django stack, snapshot the accessibility tree, inspect network requests, and screenshot only when explicitly asked. Use when…