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Dev Scenario Test

Organization
devcodex-labs
dev-scenario-test

场景测试子类型规范 — 端到端/集成测试 + artillery 负载测试

Overview

Publisherdevcodex-labs
Repositorydevcodex
Skill namedev-scenario-test
Stars
433
Forks
44
Bundled files
1
LicenseAGPL-3.0
Links
Skill sourceRepositoryHomepage
  • 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.

  • 1 bundled files

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

  • Open source

    Published by devcodex-labs on GitHub. Read the source before you install it.

Installation

Install the Dev Scenario Test 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/devcodex-labs/devcodex/tree/main/content/skills/dev-scenario-test
  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/devcodex-labs/devcodex.git /tmp/devcodex
mkdir -p .claude/skills
cp -r /tmp/devcodex/content/skills/dev-scenario-test .claude/skills/dev-scenario-test
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dev Scenario Test 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 Dev Scenario Test 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 Dev Scenario Test 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.

Dev Scenario Test Skill

触发条件

用户要求编写/完善端到端测试、集成测试、场景测试、负载测试，或 TestRoute 判定需要 LeakRiskStabilityPressureTest 泄漏风险稳定性压测 / MethodLevelLeakPressureProbe 方法级泄漏压测。

若由 test-router 触发，本 Skill 只承接 TestRoute 中的场景/负载/E2E 路线；当 TestRoute 追加 LeakRiskStabilityPressureTest 或 MethodLevelLeakPressureProbe 时，本 Skill 同时承接泄漏稳定性路线。测试路线之外的接口双产物仍交由 api-verification，静态/单元/集成覆盖标准仍以 dev-testing 为准。

前置条件

项要求
api-verification（条件）仅场景存在对外 HTTP/API 边界时，要求 .http + .cjs 已验证；纯 UI、CLI、worker、消息消费或方法级生命周期场景写 N/A + boundary evidence
TestRoute 已确认（条件）由 test-router 触发时，先确认场景/负载/E2E 路线与范围
测试环境就绪数据库/依赖服务可在测试环境访问
ServiceLifecycleCleanup若 AI 启动 dev server、文档站、本地 API/mock、数据库代理、SSH 隧道、Playwright/Cypress server 或压测 target，必须记录 PID/job/端口并在验证完成后主动关闭

工具规范

负载测试候选工具：artillery。优先复用项目既有场景/负载脚本或已安装的本地依赖；缺失时可选择不修改项目/用户环境的轻量替代探针，或在用户确认后使用隔离临时工具。npm i -g artillery 及其他全局安装必须独立说明目标、影响、恢复方式并取得当前明确授权，TestRoute、Auto、Profile 或“工具缺失”本身均不授权全局环境 mutation。

yaml
# artillery.yml 基础模板
config:
  target: "http://localhost:3000"
  phases:
    - duration: 60
      arrivalRate: 10
scenarios:
  - flow:
      - get:
          url: "/api/target"

测试类型覆盖

类型工具产物路径
项目端到端测试Playwright / Cypress项目测试目录，如 tests/e2e/
项目集成测试Vitest / Jest项目测试目录，如 tests/integration/
项目负载测试artillery项目测试目录，如 tests/load/
泄漏风险稳定性压测artillery / k6 / autocannon / 项目既有压测工具 / 轻量采样脚本项目测试目录，如 tests/load/、tests/scenario/ 或关联任务目录
方法级泄漏压测Vitest/Jest 循环测试 / 项目压测工具 / 轻量采样脚本项目测试目录，如 tests/unit/、tests/scenario/、tests/load/ 或关联任务目录
DevCodex 场景测试归档artillery / .http / .cjs.devcodex/scenario-tests/<场景>/ 或关联任务目录
归档级 API 场景验证.http + .cjs 双产物任务目录根 *-接口验证.http + *-接口验证.cjs

执行规则

  • CP1：确认测试场景清单（覆盖关键业务路径）
  • CP2：确认测试工具/框架 + 数据准备策略
  • CP3：确认执行顺序 + 环境准备/回收方式 + 风险点
  • 测试数据：使用 fixtures，禁止依赖生产数据
  • 若 TestRoute 的 leakRiskPressure 为 required，必须执行泄漏风险稳定性压测：记录 heap/RSS、active handles、监听器、连接数、缓存规模或项目等价指标的基线、压力过程、冷却后回落、清理证据和失败阈值；若项目无法采集某项指标，写 N/A + skipReason 并选择可观测替代指标
  • 若 TestRoute 的 methodLevelLeakPressure 为 required，必须围绕公开方法、生命周期入口或资源创建/释放路径设计重复调用/重复挂载卸载/重复 open-close 场景，记录基线、结束、冷却后的资源指标和清理断言；不能观测的指标写 N/A + skipReason
  • 泄漏稳定性压测不要求所有项目安装新工具；优先复用项目已有压测/监控/测试脚本，必要时用最小轻量采样脚本补足证据
  • 场景/负载/E2E 执行后必须完成 ServiceLifecycleCleanup：停止仅由 AI 本轮启动的服务，核验端口释放；用户要求保留时记录 PID/端口/关闭方式；不得杀用户既有进程
  • 测试完成后输出场景测试报告到 .devcodex/scenario-tests/<场景>/reports/<agent>/YYYYMMDD/；项目自身覆盖率报告仍按项目测试框架约定输出

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 Dev Scenario Test AI skill do?

场景测试子类型规范 — 端到端/集成测试 + artillery 负载测试

Why use Dev Scenario Test on TypingMind?

Because you install it once and use it with any model. Dev Scenario Test 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 Dev Scenario Test in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/devcodex-labs/devcodex/tree/main/content/skills/dev-scenario-test. 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 Dev Scenario Test?

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 Dev Scenario Test?

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

Is the Dev Scenario Test AI skill free?

Yes. It is published on GitHub by devcodex-labs under the AGPL-3.0 license. 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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