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E2e Verify

Community
jh941213
e2e-verify

API/CLI-level E2E test writing and execution after development, for E2E that needs no browser automation. Verifies actual user flows after /verify. Use the e2e-agent-browser skill when browser automation is needed. Triggers on: e2e verification, e2e-verify, E2E testing. NOT for: unit tests, type checking, build verification, browser-automation E2E.

Overview

Publisherjh941213
Repositorymy-cc-harness
Skill namee2e-verify
Stars
125
Forks
35
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by jh941213 on GitHub. Read the source before you install it.

Installation

Install the E2e Verify 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.
  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/jh941213/my-cc-harness.git /tmp/my-cc-harness
mkdir -p .claude/skills
cp -r /tmp/my-cc-harness/skills_en/e2e-verify .claude/skills/e2e-verify
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable E2e Verify 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 Verify 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 Verify 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 Feature Verification

After development + /verify completion, verifies that the implemented feature works in an actual browser via E2E tests.

Prerequisites

  • /verify passed (typecheck, lint, test, build)
  • App is runnable locally

Workflow

Step 1: Feature Analysis

Identify user flows for the implemented feature.

- What page does it start on?
- What interactions are needed? (clicks, inputs, navigation)
- What are the success conditions? (URL change, text display, state change)
- Edge cases? (empty input, error responses)

Step 2: Run the App

bash
# Check dev/start scripts in package.json
cat package.json | grep -A 5 '"scripts"'

# Run app (background)
npm run dev &

# Wait for app readiness via port polling (max 30 seconds) — no fixed sleep
for i in $(seq 1 30); do
  curl -sf http://localhost:3000 >/dev/null 2>&1 && break
  sleep 1
done
curl -sf http://localhost:3000 >/dev/null 2>&1 || echo "FAIL: app not ready within 30 seconds"

Step 3: Write E2E Tests

Create test files in the e2e/ directory.

bash
# Check for existing E2E setup
ls e2e/ 2>/dev/null || ls tests/e2e/ 2>/dev/null || ls __tests__/e2e/ 2>/dev/null

# Check existing E2E framework (Playwright, Cypress, agent-browser)
cat package.json | grep -E "playwright|cypress|agent-browser"
Writing Tests Per Framework

Using agent-browser:

bash
#!/bin/bash
set -e
cleanup() { agent-browser close 2>/dev/null || true; }
trap cleanup EXIT

agent-browser open http://localhost:3000

# Check elements via snapshot
agent-browser snapshot -i

# Execute feature flow
agent-browser fill @email-input "test@example.com"
agent-browser click @submit-btn
agent-browser wait text "Success"

echo "PASS: Feature E2E test"

Using Playwright:

typescript
import { test, expect } from '@playwright/test';

test('Feature: user flow', async ({ page }) => {
  await page.goto('/');
  await page.fill('[data-testid="email"]', 'test@example.com');
  await page.click('[data-testid="submit"]');
  await expect(page.locator('.success')).toBeVisible();
});

Using Cypress:

typescript
describe('Feature', () => {
  it('completes the user flow', () => {
    cy.visit('/');
    cy.get('[data-testid="email"]').type('test@example.com');
    cy.get('[data-testid="submit"]').click();
    cy.contains('Success').should('be.visible');
  });
});

Step 4: Run Tests

bash
# agent-browser
bash e2e/test_feature.sh

# Playwright
npx playwright test e2e/feature.spec.ts

# Cypress
npx cypress run --spec "cypress/e2e/feature.cy.ts"

Step 5: Debug on Failure

bash
# Capture screenshot
agent-browser screenshot ./e2e/debug.png

# Re-run in headed mode
agent-browser open http://localhost:3000 --headed

# Check console errors
agent-browser console --error

Test Checklist

  • Happy path (normal flow) passes
  • Error cases (invalid input, network errors) handled
  • Page navigation/routing works correctly
  • UI state changes (loading, success, failure) display correctly
  • Works in mobile viewport (if applicable)

Verification Loop

On test failure:

  1. Identify root cause via screenshots/logs
  2. Fix code
  3. Re-run /verify (prevent regressions)
  4. Re-run E2E tests
  5. Repeat until all pass

Frequently asked questions

What does the E2e Verify AI skill do?

API/CLI-level E2E test writing and execution after development, for E2E that needs no browser automation. Verifies actual user flows after /verify. Use the e2e-agent-browser skill when browser automation is needed. Triggers on: e2e verification, e2e-verify, E2E testing. NOT for: unit tests, type checking, build verification, browser-automation E2E.

Why use E2e Verify on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/jh941213/my-cc-harness/tree/main/skills_en/e2e-verify. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use E2e Verify?

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 Verify?

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

Is the E2e Verify AI skill free?

It is published on GitHub by jh941213. 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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