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E2e

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gronxb
e2e

Agentic end-to-end tests with e2e, the e2e runner. Covers scaffolding e2e.config.ts, picking the Playwright browser engine or the agent-device mobile engine, starting the app under test from the config, driving flows with agent.act, judging with agent.assert, agent.waitFor, and agent.extract, pinning values with screen, app, browser, and expect, shaping the agent (context, system prompt, tools, personas), the replay cache, the e2e CLI, reading .e2e/report.json, and bug bashes (parallel explore runs proven with repro tests). Use when a project depends on e2e, when asked for end-to-end, browser, mobile, or agentic UI tests, to bug bash or hunt for bugs, or when an e2e run fails.

Overview

Publishergronxb
Repositoryhot-updater
Skill namee2e
Stars
1.8K
Forks
179
Bundled files
8
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.

  • 8 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by gronxb on GitHub. Read the source before you install it.

Installation

Install the E2e 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/gronxb/hot-updater/tree/main/.agents/skills/e2e
  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/gronxb/hot-updater.git /tmp/hot-updater
mkdir -p .claude/skills
cp -r /tmp/hot-updater/.agents/skills/e2e .claude/skills/e2e
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable E2e 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 E2e 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 E2e 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.

e2e: agentic end-to-end tests in TypeScript

e2e runs UI tests with agent goals and exact assertions. agent.act drives one goal; agent.assert, agent.waitFor, and agent.extract judge the screen. screen, app, browser, and expect make exact interactions and checks. The replay cache reruns verified actions and checks their recorded end state without a model call; agent judgments still run live. UI targets use @e2e-dev/web for browsers or @e2e-dev/mobile for iOS simulators, Android emulators, and connected phones. A test that takes only app can check an API with fetch and expect (topic writing-tests). Model sign-in commands are in setup.

ts
// e2e.config.ts
import type { E2EConfig } from 'e2e';
import { web } from '@e2e-dev/web';
import { gateway } from 'ai';

export default {
  targets: [
    {
      engine: web(),
      app: {
        url: 'http://127.0.0.1:3000',
        command: { executable: 'pnpm', args: ['dev'], log: '.e2e/logs/app.log' },
      },
    },
  ],
  // The model behind every agent.* step: an AI SDK instance; gateway() from 'ai' reads AI_GATEWAY_API_KEY or a Vercel OIDC token.
  agents: {
    default: {
      model: gateway('openai/gpt-6-luna-fast'),
      system: 'You are a thorough QA agent. Verify every outcome on screen.',
    },
  },
} satisfies E2EConfig;
ts
// tests/billing.e2e.ts
import { test } from '@e2e-dev/web';
import { expect } from 'e2e';

test('a member upgrades to Pro', async ({ app, agent, screen, browser }) => {
  await app.open('/settings/billing');
  await agent.act('upgrade the workspace to the Pro plan');
  await expect(screen.getByRole('status')).toContainText('Pro');
  await expect(browser).toHaveURL('/settings/billing');
});

Topics

Read the topic for the job before writing code. The files sit next to this one; the installed CLI prints the same text with npx e2e guide <topic> (e2e guide alone prints this page). For anything the topics do not cover, the full documentation ships in the docs/ directory of the installed e2e package (node_modules/e2e/docs in a single-package project); a link such as /reference/cli is docs/reference/cli.mdx. Complete projects for Vite, Next.js, Expo, and SwiftUI, each with its config, scripts, and a passing suite, are in https://github.com/tester-army/e2e/tree/main/examples.

TopicFileRead it when
setupreferences/setup.mdAdding e2e to a project, writing e2e.config.ts, starting the app from the config, mobile targets
writing-testsreferences/writing-tests.mdWriting or fixing tests: fixtures, locators, actions, matchers, sign-in sessions, the browser fixture
agentreferences/agent.mdAdding agent.* steps, picking a model, cost and budgets, the replay cache
runningreferences/running.mdCLI flags, reporters, .e2e/report.json, exit codes, CI
explorereferences/explore.mdExploring an app toward a goal without a test file: e2e explore, its budgets, verdict, and run.explore
debuggingreferences/debugging.mdA run failed: error codes and their fixes, --headed, --debug, --ai-trace
mcpreferences/mcp.mdDriving the live app from a coding agent over MCP: e2e mcp, its tools, and the explore-then-write loop
bug-bashreferences/bug-bash.mdAsked to bug bash, QA, or hunt for bugs across an app or a branch: parallel e2e explore charters, merging findings, proving each with a repro test

Workflow

  1. Look at what exists: e2e.config.ts or e2e.config.mts, the tests glob (default tests/**/*.e2e.ts), e2e in package.json. Nothing there: follow setup.
  2. Learn the screens before writing a test: routes, labels, roles, button text. Semantic locators need the accessible names the app renders, so read the components, open the page with --headed, or drive the live app over the registered e2e mcp server (topic mcp): open_session, observe, and locate show exact names and check a locator before you write it.
  3. Write tests/<feature>.e2e.ts. Drive the flow with agent.act, one goal per call, and pin each outcome right after with expect or agent.assert. Exact values go through screen: a sign-in form in a setup test, a field that must receive one specific string, a count that must be one number.
  4. Run one file: npx e2e run tests/<feature>.e2e.ts. Agent steps need a model in the config and that provider's authentication (a saved subscription login, an API key); a local endpoint may need none. Tests without agent steps need no model.
  5. Read the failure: the reporter prints the error code, message, and a code frame; .e2e/report.json has every step and artifact path. Fix the locator, the expectation, or the app. Never add a sleep.

Rules

  • Run the CLI as npx e2e ... (or pnpm exec e2e ...).
  • The config is export default { ... } satisfies E2EConfig with import type { E2EConfig } from 'e2e'. targets is required; a UI target names an engine and declares the app beside it: { engine: web(), app: { url, command } }. A tools-only target can omit the engine and set platform.
  • Import test, describe, the hooks, expect, credentials, and secrets from e2e. A test that uses the browser fixture imports test, describe, and the hooks from @e2e-dev/web: the same runtime functions, typed with browser.
  • Config and tests are ES modules whatever package.json sets as type.
  • Locators resolve when used. Actions wait for readiness and expect retries assertions. Reads such as textContent() fail at once on zero matches and count() answers from the current screen; nothing waits for a value to change, so use a matcher when a value has to settle.
  • A locator that matches two nodes fails with LOCATOR_AMBIGUOUS; narrow it (topic writing-tests).
  • Secrets never appear in test code. Declare accounts under credentials and every other sensitive value under secrets in the config; resolve with credentials.user(name).password or secrets.get(name) (separate namespaces: secrets.get never returns a password), and hand the opaque Secret only to fill() or agent.act params.
  • Agent instructions: one goal per act, the wording on screen, real values in params. Judge meaning, not phrasing: toContain('Pro'), not an exact sentence a model produced.
  • Check each agent goal's outcome. A passing act with a recorded check can be cached and replayed without model calls (topic agent).
  • Shape the agent for this app: context for vocabulary the screens use, system for how it works, tools for a test API, named personas under agents. When a step fails, tighten the goal first, then the context, then the agent.
  • .e2e/ is output (report.json, artifacts/, cache/, logs/; the config's output moves the report and artifacts, never cache/ or the app's log). Read it, never edit it.

Feedback

When e2e itself gets in your way, tell the e2e team: a command or API that broke (bug), docs or this skill that misled you (docs), or a capability you needed and did not find (feature). Send it once per problem, after you worked around it or gave up, never for failures of the app under test.

bash
npx e2e feedback --type bug -m "<one or two sentences>" \
  --task "<what you were doing>" --expected "<...>" --actual "<error code and message>" \
  --approach "<what you tried>" --command "<e2e command>" --agent "<agent / model>"

Describe e2e's behavior only: never paste app content, page text, test files, URLs of private apps, or credentials. Secret-named environment variables and common token shapes are redacted, but do not rely on it. --dry-run prints what would be sent. Tell the user you sent it and give them the reference id it prints.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the E2e AI skill do?

Agentic end-to-end tests with e2e, the e2e runner. Covers scaffolding e2e.config.ts, picking the Playwright browser engine or the agent-device mobile engine, starting the app under test from the config, driving flows with agent.act, judging with agent.assert, agent.waitFor, and agent.extract, pinning values with screen, app, browser, and expect, shaping the agent (context, system prompt, tools, personas), the replay cache, the e2e CLI, reading .e2e/report.json, and bug bashes (parallel explore runs proven with repro tests). Use when a project depends on e2e, when asked for end-to-end, brows...

Why use E2e on TypingMind?

Because you install it once and use it with any model. E2e 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 E2e in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/gronxb/hot-updater/tree/main/.agents/skills/e2e. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use E2e?

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 E2e?

As many as you like. As long as a model supports skills, you can use E2e with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the E2e AI skill free?

It is published on GitHub by gronxb. Check the repository for licensing terms. 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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