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AI辅助开发的回归测试策略。沙盒模式API测试，无需依赖数据库，自动化的缺陷检查工作流程，以及捕捉AI盲点的模式，其中同一模型编写和审查代码。
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Basé sur la classification professionnelle SOC
Use after a complex task, failure, or when reviewing what was learned. Teaches how to write growth logs that extract reusable patterns — not diary entries.
Design a goal-oriented agent loop, and review it for the ways loops go wrong — spinning and burning tokens, Goodhart-gaming the verifier, or running a wrong answer to completion. Two actions: (1) WRITE a loop — gate whether to build it, define a machine-decidable goal, pick the loop type, pick a skeleton; (2) REVIEW a loop — run it past five failure modes plus decidability, boundaries, fallback, judge independence, and keep-judgment-with-the-human red lines. Use when designing an autonomous agent loop, or when you already have one and worry it will spin, cheat, or run a wrong answer to the end. Complements the mechanism-layer loop skills (autonomous-loops, continuous-agent-loop) by covering the judgment layer they don't. 中文触发：写 loop、设计 loop、做一个 loop、检查 loop 对不对、loop 体检、loop 会不会跑飞、可判定目标、五个崩法、plan build judge。English triggers: design an agent loop, write a loop, check a loop, loop review, prevent a runaway loop, goal-oriented loop, decidable goal, plan/build/judge.
Stop hook that blocks Claude from finishing until quality checks pass. Detects rationalization patterns (surface text heuristics), stale learning logs (filesystem mtime), and low disk space. Complements self-audit by mechanically enforcing learning capture habits.
React Native and Expo app patterns — Expo Router navigation, state separation (server/client/route/form), TanStack Query data fetching with Zod, performant lists, NativeWind/StyleSheet styling, native APIs, and secure storage. Use when building or editing React Native / Expo screens, components, navigation, or data layers.
Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents. v2.1 adds project-scoped instincts to prevent cross-project contamination.
Use this skill when writing new features, fixing bugs, or refactoring code. Enforces test-driven development with 80%+ coverage including unit, integration, and E2E tests.
| name | ai-regression-testing |
| description | AI辅助开发的回归测试策略。沙盒模式API测试，无需依赖数据库，自动化的缺陷检查工作流程，以及捕捉AI盲点的模式，其中同一模型编写和审查代码。 |
| origin | ECC |
专为 AI 辅助开发设计的测试模式，其中同一模型编写代码并审查代码——这会形成系统性的盲点，只有自动化测试才能发现。
/bug-check 或类似的审查命令当 AI 编写代码然后审查其自身工作时，它会将相同的假设带入这两个步骤。这会形成一个可预测的失败模式：
AI 编写修复 → AI 审查修复 → AI 表示“看起来正确” → 漏洞依然存在
实际示例（在生产环境中观察到）：
修复 1：向 API 响应添加了 notification_settings
→ 忘记将其添加到 SELECT 查询中
→ AI 审核时遗漏了（相同的盲点）
修复 2：将其添加到 SELECT 查询中
→ TypeScript 构建错误（列不在生成的类型中）
→ AI 审核了修复 1，但未发现 SELECT 问题
修复 3：改为 SELECT *
→ 修复了生产路径，忘记了沙箱路径
→ AI 审核时再次遗漏（第 4 次出现）
修复 4：测试在首次运行时立即捕获了问题 PASS:
模式：沙盒/生产环境路径不一致是 AI 引入的 #1 回归问题。
大多数具有 AI 友好架构的项目都有一个沙盒/模拟模式。这是实现快速、无需数据库的 API 测试的关键。
// 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 = "";
// __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 };
}
关键原则：为已发现的 bug 编写测试，而不是为正常工作的代码编写测试。
// __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);
});
});
最常见的 AI 回归问题：修复了生产环境路径但忘记了沙盒路径（或反之）。
// 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);
}
}
});
});
<!-- .claude/commands/bug-check.md -->
# Bug 检查
## 步骤 1：自动化测试（强制，不可跳过）
在代码审查前**首先**运行以下命令：
npm run test # Vitest 测试套件
npm run build # TypeScript 类型检查 + 构建
- 如果测试失败 → 报告为最高优先级 Bug
- 如果构建失败 → 将类型错误报告为最高优先级
- 只有在两者都通过后，才能继续到步骤 2
## 步骤 2：代码审查（AI 审查）
1. 沙盒/生产环境路径一致性
2. API 响应结构是否符合前端预期
3. SELECT 子句的完整性
4. 包含回滚的错误处理
5. 乐观更新的竞态条件
## 步骤 3：对于每个修复的 Bug，提出回归测试方案
User: "バグチェックして" (or "/bug-check")
│
├─ Step 1: npm run test
│ ├─ FAIL → 发现机械性错误（无需AI判断）
│ └─ PASS → 继续
│
├─ Step 2: npm run build
│ ├─ FAIL → 发现类型错误
│ └─ PASS → 继续
│
├─ Step 3: AI代码审查（考虑已知盲点）
│ └─ 报告发现的问题
│
└─ Step 4: 对每个修复编写回归测试
└─ 下次bug-check时捕获修复是否破坏功能
频率：最常见（在 4 个回归问题中观察到 3 个）
// 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 } };
用于捕获它的测试：
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);
}
});
频率：在使用 Supabase/Prisma 添加新列时常见
// 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();
频率：中等——当向现有组件添加错误处理时
// 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");
}
// 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");
}
};
不要追求 100% 的覆盖率。相反：
在 /api/user/profile 发现 bug → 为 profile API 编写测试
在 /api/user/messages 发现 bug → 为 messages API 编写测试
在 /api/user/favorites 发现 bug → 为 favorites API 编写测试
在 /api/user/notifications 没有发现 bug → 暂时不编写测试
为什么这在 AI 开发中有效：
| AI 回归模式 | 测试策略 | 优先级 |
|---|---|---|
| 沙盒/生产环境不匹配 | 断言沙盒模式下响应结构相同 | 高 |
| SELECT 子句遗漏 | 断言响应中包含所有必需字段 | 高 |
| 错误状态泄漏 | 断言出错时状态已清理 | 中 |
| 缺少回滚 | 断言 API 失败时状态已恢复 | 中 |
| 类型转换掩盖 null | 断言字段不为 undefined | 中 |
要：
不要：