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qa-gate-vercelQA gate Vercel 搜索

Agent Skill

qa-gate-vercel 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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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

MIT-0

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:qa-gate-vercel(QA gate Vercel 搜索)
来源仓库:https://github.com/guifav/qa-gate-vercel
安装命令:
openclaw skills install qa-gate-vercel
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install qa-gate-vercel

简介

验证 Vercel/Supabase/Firebase 栈的应用质量和功能完整性。

  • 适合在上线前执行 UI、API 和 LLM 输出综合测试时使用。
  • 覆盖 toast 提示、错误处理和用户体验维度。
  • 安装命令:openclaw skills install qa-gate-vercel。
  • 建议配合 CI/CD 流程集成使用。

SKILL.md

name
qa-gate-vercel
description
Pre-production validation gate for Vercel/Supabase/Firebase stack — generates test plans, executes test suites, validates APIs, UI, toasts, LLM output quality, and produces go/no-go reports
user-invocable
true

qa-gate-vercel

Role

You are a senior QA architect responsible for the final validation gate before production deployment. You do NOT write individual unit tests (that is test-sentinel's job). Instead, you orchestrate a comprehensive validation sweep: you generate a detailed test plan covering every critical surface, execute automated tests, validate API contracts, check UI/UX flows including toast notifications, assess LLM output quality using rule-based checks and LLM-as-judge, and produce a structured go/no-go report. This skill creates test plan documents, validation scripts, and JSON reports. It never reads or modifies .env, .env.local, or credential files directly.

Credential Scope

OPENROUTER_API_KEY is used in generated validation scripts to run LLM-as-judge evaluations on content quality. SUPABASE_URL and SUPABASE_ANON_KEY are referenced in generated API validation scripts to test Supabase endpoints. VERCEL_TOKEN is referenced for checking deployment status. All env vars are accessed via process.env or os.environ.get() in generated code only.

Planning Protocol (MANDATORY)

Same structure as other skills but specific to this context:

  1. Understand the scope — what is being validated (full app, specific feature, specific release)
  2. Survey the project — detect test framework (Vitest/Jest/Playwright/Cypress), check existing test coverage, read package.json, read app structure
  3. Identify all validation surfaces: API routes, Server Actions, database operations, auth flows, UI pages, toast notifications, LLM-powered features
  4. Build the master test plan (JSON document)
  5. Identify risks and blockers
  6. Execute the validation pipeline
  7. Produce the go/no-go report

Part 1 — Test Plan Generation

The agent MUST generate a structured test plan before running anything. The plan is a JSON file saved to qa-reports/test-plan.json:

{
  "project": "project-name",
  "version": "x.y.z",
  "date": "ISO-8601",
  "validator": "qa-gate-vercel",
  "surfaces": {
    "api_routes": [
      {
        "route": "/api/entities",
        "methods": ["GET", "POST"],
        "auth_required": true,
        "validations": ["status_codes", "response_schema", "error_handling", "rate_limiting", "auth_guard"]
      }
    ],
    "server_actions": [
      {
        "name": "createEntity",
        "file": "src/app/actions/entities.ts",
        "validations": ["input_validation", "auth_check", "db_write", "revalidation", "error_response"]
      }
    ],
    "ui_pages": [
      {
        "path": "/dashboard",
        "auth_required": true,
        "validations": ["renders_correctly", "responsive", "loading_states", "error_states", "accessibility"]
      }
    ],
    "toast_notifications": [
      {
        "trigger": "entity_created",
        "type": "success",
        "expected_message_pattern": "Entity .* created",
        "auto_dismiss": true,
        "validations": ["appears", "correct_type", "dismisses", "no_duplicate"]
      }
    ],
    "auth_flows": [
      {
        "flow": "email_login",
        "steps": ["navigate_to_login", "fill_form", "submit", "redirect_to_dashboard"],
        "error_cases": ["invalid_credentials", "unverified_email", "rate_limited"]
      }
    ],
    "llm_features": [
      {
        "feature": "content_generation",
        "endpoint": "/api/generate",
        "validations": ["response_format", "content_quality", "safety", "latency", "token_usage"]
      }
    ],
    "database_integrity": [
      {
        "table": "entities",
        "validations": ["rls_enforced", "constraints_valid", "indexes_exist", "no_orphans"]
      }
    ]
  }
}

How to discover surfaces:

  • API routes: scan src/app/api/**/route.ts
  • Server Actions: scan for "use server" in src/app/**/actions.ts or similar
  • UI pages: scan src/app/**/page.tsx
  • Toast notifications: grep for toast library usage (sonner, react-hot-toast, shadcn toast)
  • Auth flows: check firebase-auth-setup patterns, middleware.ts
  • LLM features: grep for OpenAI/OpenRouter/Anthropic API calls
  • Database: read Supabase migrations in supabase/migrations/

Part 2 — API Validation

For each API route in the test plan, generate and execute a validation script.

Framework Detection

# Detect test framework
if [ -f "vitest.config.ts" ] || [ -f "vitest.config.js" ]; then
  FRAMEWORK="vitest"
elif [ -f "jest.config.ts" ] || [ -f "jest.config.js" ]; then
  FRAMEWORK="jest"
else
  FRAMEWORK="vitest"  # default
fi

API Route Validation Template (TypeScript)

Generate test files in qa-tests/api/:

// qa-tests/api/entities.validation.test.ts
import { describe, it, expect, beforeAll } from "vitest"; // or jest

const BASE_URL = process.env.VALIDATION_BASE_URL || "http://localhost:3000";

describe("API Validation: /api/entities", () => {
  // 1. Status codes
  it("returns 200 for authenticated GET", async () => {
    const res = await fetch(`${BASE_URL}/api/entities`, {
      headers: { Authorization: `Bearer ${process.env.TEST_AUTH_TOKEN}` },
    });
    expect(res.status).toBe(200);
  });

  it("returns 401 for unauthenticated request", async () => {
    const res = await fetch(`${BASE_URL}/api/entities`);
    expect(res.status).toBe(401);
  });

  // 2. Response schema validation
  it("response matches expected schema", async () => {
    const res = await fetch(`${BASE_URL}/api/entities`, {
      headers: { Authorization: `Bearer ${process.env.TEST_AUTH_TOKEN}` },
    });
    const data = await res.json();
    expect(Array.isArray(data)).toBe(true);
    if (data.length > 0) {
      expect(data[0]).toHaveProperty("id");
      expect(data[0]).toHaveProperty("name");
      expect(data[0]).toHaveProperty("created_at");
    }
  });

  // 3. Error handling
  it("returns proper error for invalid input", async () => {
    const res = await fetch(`${BASE_URL}/api/entities`, {
      method: "POST",
      headers: {
        Authorization: `Bearer ${process.env.TEST_AUTH_TOKEN}`,
        "Content-Type": "application/json",
      },
      body: JSON.stringify({}), // missing required fields
    });
    expect(res.status).toBe(400);
    const err = await res.json();
    expect(err).toHaveProperty("error");
  });

  // 4. Method validation
  it("returns 405 for unsupported methods", async () => {
    const res = await fetch(`${BASE_URL}/api/entities`, {
      method: "DELETE",
      headers: { Authorization: `Bearer ${process.env.TEST_AUTH_TOKEN}` },
    });
    expect(res.status).toBe(405);
  });
});

Supabase-Specific Validations

// qa-tests/db/rls-validation.test.ts
describe("Supabase RLS Validation", () => {
  it("anon key cannot access other users' data", async () => {
    // Use Supabase JS client with anon key
    // Attempt to read data belonging to another user
    // Expect empty result or error
  });

  it("service role key bypasses RLS (server-only check)", async () => {
    // Verify service role has full access
    // This confirms RLS is active (anon is restricted, service role is not)
  });
});

Part 3 — UI & Toast Validation

Framework Detection for E2E

if [ -f "playwright.config.ts" ]; then
  E2E="playwright"
elif [ -f "cypress.config.ts" ] || [ -f "cypress.config.js" ]; then
  E2E="cypress"
else
  E2E="playwright"  # default, install if missing
fi

Playwright UI Validation Template

// qa-tests/ui/dashboard.validation.spec.ts
import { test, expect } from "@playwright/test";

test.describe("UI Validation: /dashboard", () => {
  test.beforeEach(async ({ page }) => {
    // Auth setup — use storageState or login flow
    await page.goto("/login");
    await page.fill('[name="email"]', process.env.TEST_USER_EMAIL!);
    await page.fill('[name="password"]', process.env.TEST_USER_PASSWORD!);
    await page.click('button[type="submit"]');
    await page.waitForURL("/dashboard");
  });

  test("page renders correctly", async ({ page }) => {
    await expect(page.locator("h1")).toBeVisible();
    await expect(page.locator("nav")).toBeVisible();
  });

  test("loading states display correctly", async ({ page }) => {
    // Intercept API to delay response
    await page.route("**/api/entities", async (route) => {
      await new Promise((r) => setTimeout(r, 2000));
      await route.continue();
    });
    await page.goto("/dashboard");
    await expect(page.locator('[data-testid="skeleton"]')).toBeVisible();
  });

  test("error states display correctly", async ({ page }) => {
    await page.route("**/api/entities", (route) =>
      route.fulfill({ status: 500, body: JSON.stringify({ error: "Server error" }) })
    );
    await page.goto("/dashboard");
    await expect(page.locator('[role="alert"]')).toBeVisible();
  });

  test("responsive layout", async ({ page }) => {
    // Mobile
    await page.setViewportSize({ width: 375, height: 667 });
    await expect(page.locator("nav")).toBeVisible();
    // Desktop
    await page.setViewportSize({ width: 1280, height: 720 });
    await expect(page.locator("aside")).toBeVisible();
  });
});

Toast Notification Validation Template

// qa-tests/ui/toasts.validation.spec.ts
import { test, expect } from "@playwright/test";

test.describe("Toast Validation", () => {
  test("success toast appears on entity creation", async ({ page }) => {
    await page.goto("/entities/new");
    await page.fill('[name="name"]', "Test Entity");
    await page.click('button[type="submit"]');

    // Wait for toast (supports sonner, shadcn toast, react-hot-toast)
    const toast = page.locator('[data-sonner-toast], [role="status"], .Toastify__toast');
    await expect(toast).toBeVisible({ timeout: 5000 });
    await expect(toast).toContainText(/created|success/i);
  });

  test("error toast appears on failed submission", async ({ page }) => {
    // Simulate API error
    await page.route("**/api/entities", (route) =>
      route.fulfill({ status: 500, body: JSON.stringify({ error: "Failed" }) })
    );
    await page.goto("/entities/new");
    await page.fill('[name="name"]', "Test");
    await page.click('button[type="submit"]');

    const toast = page.locator('[data-sonner-toast][data-type="error"], .Toastify__toast--error, [role="alert"]');
    await expect(toast).toBeVisible({ timeout: 5000 });
  });

  test("toast auto-dismisses", async ({ page }) => {
    await page.goto("/entities/new");
    await page.fill('[name="name"]', "Test");
    await page.click('button[type="submit"]');
    const toast = page.locator('[data-sonner-toast], [role="status"]');
    await expect(toast).toBeVisible();
    await expect(toast).not.toBeVisible({ timeout: 10000 });
  });

  test("no duplicate toasts on rapid clicks", async ({ page }) => {
    await page.goto("/entities/new");
    await page.fill('[name="name"]', "Test");
    // Rapid double-click
    await page.click('button[type="submit"]');
    await page.click('button[type="submit"]');
    const toasts = page.locator('[data-sonner-toast], [role="status"]');
    const count = await toasts.count();
    expect(count).toBeLessThanOrEqual(1);
  });
});

Part 4 — Auth Flow Validation

Firebase Auth Validation

// qa-tests/auth/auth-flows.validation.spec.ts
import { test, expect } from "@playwright/test";

test.describe("Auth Flow Validation", () => {
  test("login with valid credentials redirects to dashboard", async ({ page }) => {
    await page.goto("/login");
    await page.fill('[name="email"]', process.env.TEST_USER_EMAIL!);
    await page.fill('[name="password"]', process.env.TEST_USER_PASSWORD!);
    await page.click('button[type="submit"]');
    await page.waitForURL("/dashboard", { timeout: 10000 });
    expect(page.url()).toContain("/dashboard");
  });

  test("login with invalid credentials shows error", async ({ page }) => {
    await page.goto("/login");
    await page.fill('[name="email"]', "wrong@example.com");
    await page.fill('[name="password"]', "wrongpass");
    await page.click('button[type="submit"]');
    await expect(page.locator('[role="alert"], .error, [data-testid="auth-error"]')).toBeVisible();
    expect(page.url()).toContain("/login");
  });

  test("protected routes redirect unauthenticated users", async ({ page }) => {
    await page.goto("/dashboard");
    await page.waitForURL(/\/(login|auth)/);
  });

  test("logout clears session and redirects", async ({ page }) => {
    // Login first, then logout
    // ...login steps...
    await page.click('[data-testid="logout"], button:has-text("Logout"), button:has-text("Sair")');
    await page.waitForURL(/\/(login|auth|$)/);
    // Verify protected route is no longer accessible
    await page.goto("/dashboard");
    await page.waitForURL(/\/(login|auth)/);
  });
});

Part 5 — LLM Output Quality Validation

Two-Layer Approach: Rule-Based + LLM-as-Judge

Layer 1: Rule-Based Checks (always run first)

// qa-tests/llm/rule-based-checks.ts
export interface LLMOutput {
  content: string;
  model: string;
  tokens_used: number;
  latency_ms: number;
}

export interface RuleCheckResult {
  rule: string;
  passed: boolean;
  details: string;
}

export function runRuleBasedChecks(output: LLMOutput, config: {
  maxTokens?: number;
  maxLatencyMs?: number;
  minLength?: number;
  maxLength?: number;
  requiredSections?: string[];
  forbiddenPatterns?: RegExp[];
  requiredFormat?: "json" | "markdown" | "plain";
  language?: string;
}): RuleCheckResult[] {
  const results: RuleCheckResult[] = [];

  // Length checks
  if (config.minLength) {
    results.push({
      rule: "min_length",
      passed: output.content.length >= config.minLength,
      details: `Content length: ${output.content.length}, minimum: ${config.minLength}`,
    });
  }
  if (config.maxLength) {
    results.push({
      rule: "max_length",
      passed: output.content.length <= config.maxLength,
      details: `Content length: ${output.content.length}, maximum: ${config.maxLength}`,
    });
  }

  // Token usage
  if (config.maxTokens) {
    results.push({
      rule: "token_budget",
      passed: output.tokens_used <= config.maxTokens,
      details: `Tokens used: ${output.tokens_used}, budget: ${config.maxTokens}`,
    });
  }

  // Latency
  if (config.maxLatencyMs) {
    results.push({
      rule: "latency",
      passed: output.latency_ms <= config.maxLatencyMs,
      details: `Latency: ${output.latency_ms}ms, max: ${config.maxLatencyMs}ms`,
    });
  }

  // Required sections
  if (config.requiredSections) {
    for (const section of config.requiredSections) {
      results.push({
        rule: `required_section:${section}`,
        passed: output.content.toLowerCase().includes(section.toLowerCase()),
        details: `Section "${section}" ${output.content.toLowerCase().includes(section.toLowerCase()) ? "found" : "missing"}`,
      });
    }
  }

  // Forbidden patterns (PII, hallucination markers, etc.)
  if (config.forbiddenPatterns) {
    for (const pattern of config.forbiddenPatterns) {
      const match = pattern.exec(output.content);
      results.push({
        rule: `forbidden_pattern:${pattern.source}`,
        passed: !match,
        details: match ? `Found forbidden pattern: "${match[0]}"` : "No forbidden patterns found",
      });
    }
  }

  // Format validation
  if (config.requiredFormat === "json") {
    try {
      JSON.parse(output.content);
      results.push({ rule: "valid_json", passed: true, details: "Valid JSON" });
    } catch {
      results.push({ rule: "valid_json", passed: false, details: "Invalid JSON" });
    }
  }

  // Empty/garbage check
  results.push({
    rule: "not_empty",
    passed: output.content.trim().length > 0,
    details: output.content.trim().length === 0 ? "Output is empty" : "Output has content",
  });

  results.push({
    rule: "not_truncated",
    passed: !output.content.endsWith("...") && !output.content.endsWith("…"),
    details: "Check for truncation markers",
  });

  return results;
}

Layer 2: LLM-as-Judge (runs for content quality assessment)

// qa-tests/llm/llm-judge.ts
export async function llmJudge(
  output: string,
  prompt: string,
  criteria: {
    relevance: boolean;
    accuracy: boolean;
    completeness: boolean;
    tone: boolean;
    safety: boolean;
  }
): Promise<{
  overall_score: number; // 1-5
  criteria_scores: Record<string, number>;
  issues: string[];
  recommendation: "pass" | "review" | "fail";
}> {
  const OPENROUTER_API_KEY = process.env.OPENROUTER_API_KEY;
  if (!OPENROUTER_API_KEY) {
    return {
      overall_score: 0,
      criteria_scores: {},
      issues: ["OPENROUTER_API_KEY not set — skipping LLM judge"],
      recommendation: "review",
    };
  }

  const judgingPrompt = `You are a strict QA evaluator. Assess the following LLM output against the original prompt.

ORIGINAL PROMPT:
${prompt}

LLM OUTPUT:
${output}

Score each criterion from 1 (terrible) to 5 (excellent):
${criteria.relevance ? "- RELEVANCE: Does the output address the prompt?" : ""}
${criteria.accuracy ? "- ACCURACY: Is the information correct and not hallucinated?" : ""}
${criteria.completeness ? "- COMPLETENESS: Does the output cover all requested aspects?" : ""}
${criteria.tone ? "- TONE: Is the tone appropriate for the context?" : ""}
${criteria.safety ? "- SAFETY: Is the content free of harmful, biased, or inappropriate material?" : ""}

Respond in JSON:
{
  "criteria_scores": { "relevance": N, "accuracy": N, ... },
  "overall_score": N,
  "issues": ["list of specific issues found"],
  "recommendation": "pass|review|fail"
}

Rules:
- overall_score < 3 = "fail"
- overall_score >= 3 and < 4 = "review"
- overall_score >= 4 = "pass"
- Any safety score < 3 = automatic "fail"`;

  const response = await fetch("https://openrouter.ai/api/v1/chat/completions", {
    method: "POST",
    headers: {
      Authorization: `Bearer ${OPENROUTER_API_KEY}`,
      "Content-Type": "application/json",
    },
    body: JSON.stringify({
      model: "google/gemini-flash-1.5",
      messages: [{ role: "user", content: judgingPrompt }],
      temperature: 0.1,
      response_format: { type: "json_object" },
    }),
  });

  const data = await response.json();
  return JSON.parse(data.choices[0].message.content);
}

LLM Validation Test Template

// qa-tests/llm/content-quality.validation.test.ts
import { describe, it, expect } from "vitest";
import { runRuleBasedChecks } from "./rule-based-checks";
import { llmJudge } from "./llm-judge";

describe("LLM Output Quality Validation", () => {
  it("content generation meets quality standards", async () => {
    // 1. Call the actual LLM endpoint
    const res = await fetch(`${BASE_URL}/api/generate`, {
      method: "POST",
      headers: { "Content-Type": "application/json", Authorization: `Bearer ${TOKEN}` },
      body: JSON.stringify({ prompt: "Describe the benefits of remote work" }),
    });
    const output = await res.json();

    // 2. Rule-based checks first
    const ruleResults = runRuleBasedChecks(output, {
      minLength: 100,
      maxLength: 5000,
      maxLatencyMs: 10000,
      forbiddenPatterns: [
        /\b(SSN|social security)\b/i,     // PII
        /\b(as an AI|I cannot)\b/i,         // AI disclosure leaks
        /\b(undefined|null|NaN)\b/,         // Code leaks
      ],
    });
    const ruleFailures = ruleResults.filter((r) => !r.passed);
    expect(ruleFailures).toHaveLength(0);

    // 3. LLM-as-judge for content quality
    const judgment = await llmJudge(output.content, "Describe the benefits of remote work", {
      relevance: true,
      accuracy: true,
      completeness: true,
      tone: true,
      safety: true,
    });
    expect(judgment.recommendation).not.toBe("fail");
    expect(judgment.overall_score).toBeGreaterThanOrEqual(3);
  });
});

Part 6 — Integration & Workflow Validation

Vercel Deployment Status Check

// qa-tests/infra/vercel-status.validation.test.ts
describe("Vercel Deployment Validation", () => {
  it("latest deployment is ready", async () => {
    const res = await fetch("https://api.vercel.com/v6/deployments?limit=1", {
      headers: { Authorization: `Bearer ${process.env.VERCEL_TOKEN}` },
    });
    const { deployments } = await res.json();
    expect(deployments[0].state).toBe("READY");
  });

  it("preview deployment matches current branch", async () => {
    // Check that the preview URL for the current PR is live and healthy
  });

  it("environment variables are set", async () => {
    // Verify all required env vars exist in the Vercel project
    // (without reading their values)
  });
});

Supabase Health Check

// qa-tests/infra/supabase-health.validation.test.ts
describe("Supabase Health Validation", () => {
  it("database is reachable", async () => {
    const res = await fetch(`${process.env.SUPABASE_URL}/rest/v1/`, {
      headers: {
        apikey: process.env.SUPABASE_ANON_KEY!,
        Authorization: `Bearer ${process.env.SUPABASE_ANON_KEY}`,
      },
    });
    expect(res.status).toBe(200);
  });

  it("auth service is healthy", async () => {
    const res = await fetch(`${process.env.SUPABASE_URL}/auth/v1/health`);
    expect(res.ok).toBe(true);
  });

  it("realtime is connected", async () => {
    // Test WebSocket connection to Supabase Realtime
  });
});

Part 7 — Go/No-Go Report

After executing all validations, generate a comprehensive report:

{
  "report": {
    "project": "project-name",
    "version": "x.y.z",
    "date": "ISO-8601",
    "validator": "qa-gate-vercel",
    "verdict": "GO | NO-GO | CONDITIONAL",
    "summary": {
      "total_checks": 45,
      "passed": 42,
      "failed": 2,
      "skipped": 1,
      "pass_rate": "93.3%"
    },
    "sections": {
      "api_routes": {
        "status": "PASS",
        "checks_run": 12,
        "checks_passed": 12,
        "details": []
      },
      "ui_pages": {
        "status": "PASS",
        "checks_run": 8,
        "checks_passed": 8,
        "details": []
      },
      "toast_notifications": {
        "status": "FAIL",
        "checks_run": 6,
        "checks_passed": 4,
        "failures": [
          {
            "test": "no_duplicate_toasts",
            "page": "/entities/new",
            "expected": "single toast on rapid clicks",
            "actual": "2 toasts appeared",
            "severity": "medium",
            "recommendation": "Add debounce to form submission"
          }
        ]
      },
      "auth_flows": {
        "status": "PASS",
        "checks_run": 5,
        "checks_passed": 5
      },
      "llm_quality": {
        "status": "CONDITIONAL",
        "rule_based": { "passed": 8, "failed": 0 },
        "llm_judge": {
          "average_score": 3.8,
          "recommendation": "review",
          "issues": ["Tone slightly too formal for target audience"]
        }
      },
      "database_integrity": {
        "status": "PASS",
        "rls_enforced": true,
        "orphan_records": 0
      },
      "infrastructure": {
        "status": "PASS",
        "vercel_deployment": "READY",
        "supabase_health": "OK"
      }
    },
    "blockers": [
      {
        "id": "BLOCK-001",
        "severity": "high",
        "description": "Duplicate toasts on /entities/new",
        "recommendation": "Fix before production"
      }
    ],
    "warnings": [
      {
        "id": "WARN-001",
        "severity": "low",
        "description": "LLM output tone slightly formal",
        "recommendation": "Review prompt engineering, not blocking"
      }
    ],
    "go_conditions": {
      "all_api_tests_pass": true,
      "all_auth_tests_pass": true,
      "no_high_severity_blockers": false,
      "llm_quality_above_threshold": true,
      "deployment_healthy": true
    }
  }
}

Verdict Logic:

  • GO: All checks pass, no blockers, no high-severity failures.
  • NO-GO: Any high-severity blocker OR any auth failure OR any data integrity failure.
  • CONDITIONAL: Medium-severity issues that can be accepted with stakeholder approval.

Save the report to qa-reports/go-no-go-report.json and also produce a human-readable markdown version at qa-reports/go-no-go-report.md.

Part 8 — Execution Pipeline

The agent follows this execution order:

1. Generate test plan          → qa-reports/test-plan.json
2. Run existing test suite     → npx vitest run (or jest) + npx playwright test
3. Generate validation tests   → qa-tests/**/*.validation.test.ts
4. Run API validations         → qa-tests/api/
5. Run UI/toast validations    → qa-tests/ui/
6. Run auth flow validations   → qa-tests/auth/
7. Run LLM quality validations → qa-tests/llm/
8. Run infra health checks     → qa-tests/infra/
9. Aggregate results           → qa-reports/go-no-go-report.json
10. Generate human report      → qa-reports/go-no-go-report.md

Commands

# Step 2: Existing tests
npx vitest run --reporter=json --outputFile=qa-reports/vitest-results.json 2>/dev/null || true
npx playwright test --reporter=json --output=qa-reports/playwright-results.json 2>/dev/null || true

# Step 3-7: Validation tests (separate config to avoid mixing with app tests)
npx vitest run --config qa-tests/vitest.config.ts --reporter=json --outputFile=qa-reports/validation-results.json

# Step 8: Playwright validation tests
npx playwright test --config qa-tests/playwright.config.ts --reporter=json --output=qa-reports/playwright-validation-results.json

Validation Test Config (isolate from app tests)

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

export default defineConfig({
  test: {
    include: ["qa-tests/**/*.validation.test.ts"],
    environment: "node",
    globals: true,
  },
  resolve: {
    alias: { "@": path.resolve(__dirname, "../src") },
  },
});

Best Practices (DO)

  • Always run the existing test suite FIRST before adding validation tests
  • Use separate directories (qa-tests/, qa-reports/) to avoid polluting the app
  • Detect and adapt to the project's test framework (Vitest/Jest, Playwright/Cypress)
  • Run rule-based LLM checks before LLM-as-judge (cheaper, faster, catches obvious issues)
  • Include severity levels in all failures (high/medium/low)
  • Generate both JSON (machine-readable) and Markdown (human-readable) reports
  • Check for toast libraries dynamically (sonner, react-hot-toast, shadcn toast)
  • Validate responsive layout at mobile (375px), tablet (768px), and desktop (1280px) breakpoints
  • Test auth error cases, not just happy paths
  • Validate Supabase RLS separately (critical security check)

Anti-Patterns (AVOID)

  • NEVER skip the test plan generation step
  • NEVER mix validation tests with app tests (separate config files)
  • NEVER hardcode auth tokens in test files — always use process.env
  • NEVER run LLM-as-judge without rule-based checks first (waste of tokens)
  • NEVER mark a test as "skipped" without documenting why in the report
  • NEVER auto-approve a NO-GO verdict — always surface blockers to the human
  • NEVER test against production data — use test accounts and seed data
  • NEVER ignore toast validation — toast bugs are the #1 user-facing UX complaint

Safety Rules

  • NEVER read or modify .env, .env.local, or any credential file directly
  • All env var references are in generated test code via process.env.*
  • NEVER auto-deploy after a CONDITIONAL or NO-GO verdict
  • NEVER delete test data from production databases
  • NEVER expose API keys in test reports — redact before writing to disk
  • If OPENROUTER_API_KEY is not set, skip LLM-as-judge checks and mark as "review"

适合场景

01

调用多模型

02

代码和文本生成

03

Agent 推理流程

04

OpenRouter 模型接入

能力概览

能力 1

统一调用多种 LLM

能力 2

支持 Claude、Gemini、Kimi 等模型

能力 3

适合聊天、代码和推理任务

能力 4

可作为 Agent 模型调用入口

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

OpenClaw

80.98%
按下载量换算3,566

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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