Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/seed-forge/harness-ai-kitnpx agentmods add skills/seed-forge/harness-ai-kit/devlab-web-test-e2eWrote 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/seed-forge/harness-ai-kit/devlab-web-test-e2e)<a href="https://agentmods.dev/skills/seed-forge/harness-ai-kit/devlab-web-test-e2e"><img src="https://agentmods.dev/badge/skills/seed-forge/harness-ai-kit/devlab-web-test-e2e/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/seed-forge/harness-ai-kit/devlab-web-test-e2e"><img src="https://agentmods.dev/badge/skills/seed-forge/harness-ai-kit/devlab-web-test-e2e.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 6 findings, 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 38 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]
- medium MCP Rug Pull · line 40 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]
- medium MCP Rug Pull · line 363 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]
- medium MCP Rug Pull · line 366 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]
- medium MCP Rug Pull · line 384 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]
- medium MCP Rug Pull · line 426 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 | $0.00061 | $0.03752 |
| Opus 5.5 | $0.00024 | $0.01501 |
| Sonnet 5.5 | $0.00012 | $0.00750 |
| Haiku 4.5 | $0.00006 | $0.00375 |
Grade A, and why
devlab-web-test-e2e 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 — 491 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Web E2E 测试专家技能
专注 Vue/React 前端项目的浏览器端到端测试能力。
基于 Playwright + AI Agent 实现从测试计划生成 → 代码生成 → 失败修复的完整闭环。
触发条件
当用户提到以下关键词时触发此 Skill:
- "Vue/React 组件测试" / "web component test"
- "浏览器自动化测试" / "browser automation"
- "Playwright 测试" / "E2E 测试"
- "视觉回归测试" / "visual regression"
- "Flaky test 治理" / "不稳定测试修复"
技术栈依赖
核心 CLI
# 必须安装
npm install -D @playwright/test
# 可选增强
npm install -D vitest # 单元测试补充
AI Agent 初始化
npx playwright init-agents --loop=claude
# 或
npx playwright init-agents --loop=codex
功能范围
Phase 1: 测试场景识别与计划生成
输入:
- 应用 URL(本地开发环境)
- (可选)PRD/User Story 描述
- (可选)现有测试代码模式参考
输出:
specs/features/*.md— 功能测试计划(Gherkin 格式)specs/regression.md— 视觉回归检查清单specs/performance.md— 性能基准要求
工作流程:
Step 1.1: UI 探索分析
// AI 自动打开浏览器扫描应用
const page = await context.newPage();
await page.goto('http://localhost:3000');
// 提取关键元素
const elements = await page.locator('button, input, a').all();
const routes = await extractRoutes(page);
输出物:
# UI Structure Analysis
- 路由表:`/, /login, /dashboard, /settings`
- 主要组件:登录表单、导航栏、数据表格、操作按钮
- 交互点:47 个可点击元素,12 个表单字段
Step 1.2: 生成测试计划
# specs/features/user-authentication.md
Feature: User Authentication
As a registered user
I want to log in securely
So that I can access my account
Scenario: Successful login with valid credentials
Given I am on the login page
When I enter valid email and password
And I click "Sign In" button
Then I should see the dashboard
And I should receive a welcome message
Scenario Outline: Login validation
When I enter "<email>" as email
And I submit the form
Then I should see error "<error_message>"
Examples:
| email | error_message |
| invalid | Invalid email format|
| empty@ | Invalid email format|
| | Email is required |
Phase 2: Playwright 测试代码生成
What ships with it
4 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 · 491 lines · 61 tokens per session scan A fb6b3ef3a1b5
devlab-web-test-e2e is a skill published in the GitHub repository seed-forge/harness-ai-kit (25 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 61 tokens to every session and 3,752 once invoked, about $0.0002 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
qa
Exercise the delivered customer journey using real runtime or browser evidence. Use for functional acceptance testing after implementation, including failure paths.
running-bug-review-board
Runs real-user QA, manual test plans, UX bug hunts, build sign-off, bug filing, and bug triage for web or iOS/iPadOS apps. Use when asked "QA this", "is this ready to ship?", or similar. Produces P0/P1/P2 bug reports, YES/NO phase sign-off, tracker sync guidance, and an HTML QA dashboard; keeps Interactive BRB triage…
plan-test-coverage
User-story-driven test coverage audit and plan — no test writing in this pass. Use when "test coverage plan", "coverage audit", "traceability matrix", "fake-green tests", "uncovered user stories", "plan tests for critical flows", or "whats not tested". Mutation score / assertion theater → test-mutation.
Playwright Test Builder
Generates robust Playwright end-to-end tests for web pages and user flows.
pre-send-qa
Pre-flight QA for an email campaign — merge tags, broken links, spam triggers, compliance, mobile rendering — before you hit send.
screen-reader-testing
Test web applications with screen readers including VoiceOver, NVDA, and JAWS. Use when validating screen reader compatibility, debugging accessibility issues, or ensuring assistive technology support.