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ai-regression-testingAI 回归测试

Agent Skill

用于辅助测试设计、自动化测试、用例整理和回归验证。它适合让 Agent 编写单元测试、端到端测试、测试计划或根据失败日志定位问题。使用时需要确认项目测试框架、运行命令和夹具数据,避免为了通过测试而改坏真实逻辑;涉及浏览器或外部服务时,应区分本地模拟、测试环境和生产环境。

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CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:ai-regression-testing(AI 回归测试)
来源仓库:https://github.com/affaan-m/everything-claude-code
仓库路径:skills/ai-regression-testing
安装命令:
npx skills add https://github.com/affaan-m/everything-claude-code --skill ai-regression-testing
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/affaan-m/everything-claude-code --skill ai-regression-testing

简介

用于防止 AI 生成代码引入回归缺陷的专项测试。

  • 适合 API 变更后自动验证功能一致性。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。
  • 可结合沙箱环境实现无数据库依赖的测试执行。
  • 需区分生产环境与测试环境的执行边界与夹具数据。
  • ai-regression-testing 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

AI Regression Testing

Testing patterns specifically designed for AI-assisted development, where the same model writes code and reviews it — creating systematic blind spots that only automated tests can catch.

When to Activate

  • AI agent (Claude Code, Cursor, Codex) has modified API routes or backend logic
  • A bug was found and fixed — need to prevent re-introduction
  • Project has a sandbox/mock mode that can be leveraged for DB-free testing
  • Running /bug-check or similar review commands after code changes
  • Multiple code paths exist (sandbox vs production, feature flags, etc.)

The Core Problem

When an AI writes code and then reviews its own work, it carries the same assumptions into both steps. This creates a predictable failure pattern:

AI writes fix → AI reviews fix → AI says "looks correct" → Bug still exists

Real-world example (observed in production):

Fix 1: Added notification_settings to API response
  → Forgot to add it to the SELECT query
  → AI reviewed and missed it (same blind spot)

Fix 2: Added it to SELECT query
  → TypeScript build error (column not in generated types)
  → AI reviewed Fix 1 but didn't catch the SELECT issue

Fix 3: Changed to SELECT *
  → Fixed production path, forgot sandbox path
  → AI reviewed and missed it AGAIN (4th occurrence)

Fix 4: Test caught it instantly on first run PASS:

The pattern: sandbox/production path inconsistency is the #1 AI-introduced regression.

Sandbox-Mode API Testing

Most projects with AI-friendly architecture have a sandbox/mock mode. This is the key to fast, DB-free API testing.

Setup (Vitest + Next.js App Router)

// vitest.config.ts
import { defineConfig } from "vitest/config";
import path from "path";

export default defineConfig({
  test: {
    environment: "node",
    globals: true,
    include: ["__tests__/**/*.test.ts"],
    setupFiles: ["__tests__/setup.ts"],
  },
  resolve: {
    alias: {
      "@": path.resolve(__dirname, "."),
    },
  },
});
// __tests__/setup.ts
// Force sandbox mode — no database needed
process.env.SANDBOX_MODE = "true";
process.env.NEXT_PUBLIC_SUPABASE_URL = "";
process.env.NEXT_PUBLIC_SUPABASE_ANON_KEY = "";

Test Helper for Next.js API Routes

// __tests__/helpers.ts
import { NextRequest } from "next/server";

export function createTestRequest(
  url: string,
  options?: {
    method?: string;
    body?: Record<string, unknown>;
    headers?: Record<string, string>;
    sandboxUserId?: string;
  },
): NextRequest {
  const { method = "GET", body, headers = {}, sandboxUserId } = options || {};
  const fullUrl = url.startsWith("http") ? url : `http://localhost:3000${url}`;
  const reqHeaders: Record<string, string> = { ...headers };

  if (sandboxUserId) {
    reqHeaders["x-sandbox-user-id"] = sandboxUserId;
  }

  const init: { method: string; headers: Record<string, string>; body?: string } = {
    method,
    headers: reqHeaders,
  };

  if (body) {
    init.body = JSON.stringify(body);
    reqHeaders["content-type"] = "application/json";
  }

  return new NextRequest(fullUrl, init);
}

export async function parseResponse(response: Response) {
  const json = await response.json();
  return { status: response.status, json };
}

Writing Regression Tests

The key principle: write tests for bugs that were found, not for code that works.

// __tests__/api/user/profile.test.ts
import { describe, it, expect } from "vitest";
import { createTestRequest, parseResponse } from "../../helpers";
import { GET, PATCH } from "@/app/api/user/profile/route";

// Define the contract — what fields MUST be in the response
const REQUIRED_FIELDS = [
  "id",
  "email",
  "full_name",
  "phone",
  "role",
  "created_at",
  "avatar_url",
  "notification_settings",  // ← Added after bug found it missing
];

describe("GET /api/user/profile", () => {
  it("returns all required fields", async () => {
    const req = createTestRequest("/api/user/profile");
    const res = await GET(req);
    const { status, json } = await parseResponse(res);

    expect(status).toBe(200);
    for (const field of REQUIRED_FIELDS) {
      expect(json.data).toHaveProperty(field);
    }
  });

  // Regression test — this exact bug was introduced by AI 4 times
  it("notification_settings is not undefined (BUG-R1 regression)", async () => {
    const req = createTestRequest("/api/user/profile");
    const res = await GET(req);
    const { json } = await parseResponse(res);

    expect("notification_settings" in json.data).toBe(true);
    const ns = json.data.notification_settings;
    expect(ns === null || typeof ns === "object").toBe(true);
  });
});

Testing Sandbox/Production Parity

The most common AI regression: fixing production path but forgetting sandbox path (or vice versa).

// Test that sandbox responses match the expected contract
describe("GET /api/user/messages (conversation list)", () => {
  it("includes partner_name in sandbox mode", async () => {
    const req = createTestRequest("/api/user/messages", {
      sandboxUserId: "user-001",
    });
    const res = await GET(req);
    const { json } = await parseResponse(res);

    // This caught a bug where partner_name was added
    // to production path but not sandbox path
    if (json.data.length > 0) {
      for (const conv of json.data) {
        expect("partner_name" in conv).toBe(true);
      }
    }
  });
});

Integrating Tests into Bug-Check Workflow

Custom Command Definition

<!-- .claude/commands/bug-check.md -->
# Bug Check

## Step 1: Automated Tests (mandatory, cannot skip)

Run these commands FIRST before any code review:

    npm run test       # Vitest test suite
    npm run build      # TypeScript type check + build

- If tests fail → report as highest priority bug
- If build fails → report type errors as highest priority
- Only proceed to Step 2 if both pass

## Step 2: Code Review (AI review)

1. Sandbox / production path consistency
2. API response shape matches frontend expectations
3. SELECT clause completeness
4. Error handling with rollback
5. Optimistic update race conditions

## Step 3: For each bug fixed, propose a regression test

The Workflow

User: "バグチェックして" (or "/bug-check")
  │
  ├─ Step 1: npm run test
  │   ├─ FAIL → Bug found mechanically (no AI judgment needed)
  │   └─ PASS → Continue
  │
  ├─ Step 2: npm run build
  │   ├─ FAIL → Type error found mechanically
  │   └─ PASS → Continue
  │
  ├─ Step 3: AI code review (with known blind spots in mind)
  │   └─ Findings reported
  │
  └─ Step 4: For each fix, write a regression test
      └─ Next bug-check catches if fix breaks

Common AI Regression Patterns

Pattern 1: Sandbox/Production Path Mismatch

Frequency: Most common (observed in 3 out of 4 regressions)

// FAIL: AI adds field to production path only
if (isSandboxMode()) {
  return { data: { id, email, name } };  // Missing new field
}
// Production path
return { data: { id, email, name, notification_settings } };

// PASS: Both paths must return the same shape
if (isSandboxMode()) {
  return { data: { id, email, name, notification_settings: null } };
}
return { data: { id, email, name, notification_settings } };

Test to catch it:

it("sandbox and production return same fields", async () => {
  // In test env, sandbox mode is forced ON
  const res = await GET(createTestRequest("/api/user/profile"));
  const { json } = await parseResponse(res);

  for (const field of REQUIRED_FIELDS) {
    expect(json.data).toHaveProperty(field);
  }
});

Pattern 2: SELECT Clause Omission

Frequency: Common with Supabase/Prisma when adding new columns

// FAIL: New column added to response but not to SELECT
const { data } = await supabase
  .from("users")
  .select("id, email, name")  // notification_settings not here
  .single();

return { data: { ...data, notification_settings: data.notification_settings } };
// → notification_settings is always undefined

// PASS: Use SELECT * or explicitly include new columns
const { data } = await supabase
  .from("users")
  .select("*")
  .single();

Pattern 3: Error State Leakage

Frequency: Moderate — when adding error handling to existing components

// FAIL: Error state set but old data not cleared
catch (err) {
  setError("Failed to load");
  // reservations still shows data from previous tab!
}

// PASS: Clear related state on error
catch (err) {
  setReservations([]);  // Clear stale data
  setError("Failed to load");
}

Pattern 4: Optimistic Update Without Proper Rollback

// FAIL: No rollback on failure
const handleRemove = async (id: string) => {
  setItems(prev => prev.filter(i => i.id !== id));
  await fetch(`/api/items/${id}`, { method: "DELETE" });
  // If API fails, item is gone from UI but still in DB
};

// PASS: Capture previous state and rollback on failure
const handleRemove = async (id: string) => {
  const prevItems = [...items];
  setItems(prev => prev.filter(i => i.id !== id));
  try {
    const res = await fetch(`/api/items/${id}`, { method: "DELETE" });
    if (!res.ok) throw new Error("API error");
  } catch {
    setItems(prevItems);  // Rollback
    alert("削除に失敗しました");
  }
};

Strategy: Test Where Bugs Were Found

Don't aim for 100% coverage. Instead:

Bug found in /api/user/profile     → Write test for profile API
Bug found in /api/user/messages    → Write test for messages API
Bug found in /api/user/favorites   → Write test for favorites API
No bug in /api/user/notifications  → Don't write test (yet)

Why this works with AI development:

  1. AI tends to make the same category of mistake repeatedly
  2. Bugs cluster in complex areas (auth, multi-path logic, state management)
  3. Once tested, that exact regression cannot happen again
  4. Test count grows organically with bug fixes — no wasted effort

Quick Reference

AI Regression PatternTest StrategyPriority
Sandbox/production mismatchAssert same response shape in sandbox modeHigh
SELECT clause omissionAssert all required fields in responseHigh
Error state leakageAssert state cleanup on errorMedium
Missing rollbackAssert state restored on API failureMedium
Type cast masking nullAssert field is not undefinedMedium

DO / DON'T

DO:

  • Write tests immediately after finding a bug (before fixing it if possible)
  • Test the API response shape, not the implementation
  • Run tests as the first step of every bug-check
  • Keep tests fast (< 1 second total with sandbox mode)
  • Name tests after the bug they prevent (e.g., "BUG-R1 regression")

DON'T:

  • Write tests for code that has never had a bug
  • Trust AI self-review as a substitute for automated tests
  • Skip sandbox path testing because "it's just mock data"
  • Write integration tests when unit tests suffice
  • Aim for coverage percentage — aim for regression prevention

适合场景

01

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02

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03

需要对比不同来源的安装命令和来源信息时

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能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

35.32%
按下载量换算6,646

Claude

29.34%
按下载量换算5,521

Cursor

20.48%
按下载量换算3,854

Gemini CLI

10.89%
按下载量换算2,049

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

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