seed-skills/checkly-monitoring-as-code/SKILL.md
Teach agents to build synthetic monitoring as code with Checkly, including Playwright browser checks, API checks, alerting, and CI deploy workflows.
npx skillsauth add PramodDutta/qaskills Checkly Monitoring as CodeInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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You are a synthetic monitoring engineer who defines Checkly browser and API checks as code, keeps them close to product journeys, and deploys monitors through reviewable CI workflows.
Install the Checkly CLI and Playwright dependency.
npm create checkly@latest synthetic-monitoring
cd synthetic-monitoring
npm install
npm install --save-dev @playwright/test
npx checkly --version
Authenticate locally only when needed.
npx checkly login
npx checkly test
npx checkly deploy
Use a structure that separates checks, groups, snippets, and utilities.
checkly/
checks/
browser/
checkout.check.ts
login.check.ts
api/
health.check.ts
search.check.ts
groups/
production.group.ts
snippets/
auth.ts
runbook.ts
checkly.config.ts
package.json
Keep browser checks short and user-centered.
// checkly/checks/browser/login.check.ts
import { BrowserCheck, Frequency } from 'checkly/constructs';
new BrowserCheck('login-browser-check', {
name: 'Login journey',
activated: true,
frequency: Frequency.EVERY_10M,
locations: ['us-east-1', 'eu-west-1'],
code: {
entrypoint: './login.spec.ts',
},
environmentVariables: [
{ key: 'BASE_URL', value: 'https://example.com' },
],
});
// checkly/checks/browser/login.spec.ts
import { expect, test } from '@playwright/test';
test('user can reach dashboard after login', async ({ page }) => {
await page.goto(process.env.BASE_URL || 'https://example.com');
await page.getByRole('link', { name: 'Sign in' }).click();
await page.getByLabel('Email').fill(process.env.CHECKLY_USER || '[email protected]');
await page.getByLabel('Password').fill(process.env.CHECKLY_PASSWORD || 'change-me');
await page.getByRole('button', { name: 'Sign in' }).click();
await expect(page.getByRole('heading', { name: 'Dashboard' })).toBeVisible();
});
Use API checks for fast service-level confidence.
// checkly/checks/api/health.check.ts
import { ApiCheck, AssertionBuilder, Frequency } from 'checkly/constructs';
new ApiCheck('api-health-check', {
name: 'API health',
activated: true,
frequency: Frequency.EVERY_1M,
request: {
method: 'GET',
url: 'https://api.example.com/health',
assertions: [
AssertionBuilder.statusCode().equals(200),
AssertionBuilder.jsonBody('status').equals('ok'),
AssertionBuilder.responseTime().lessThan(500),
],
},
});
Route alerts to the right owner.
Deploy checks after code review.
name: checkly
on:
push:
branches: [main]
pull_request:
jobs:
checks:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with:
node-version: 20
- run: npm ci
- run: npx checkly test
env:
CHECKLY_API_KEY: ${{ secrets.CHECKLY_API_KEY }}
CHECKLY_ACCOUNT_ID: ${{ secrets.CHECKLY_ACCOUNT_ID }}
- run: npx checkly deploy --force
if: github.ref == 'refs/heads/main'
env:
CHECKLY_API_KEY: ${{ secrets.CHECKLY_API_KEY }}
CHECKLY_ACCOUNT_ID: ${{ secrets.CHECKLY_ACCOUNT_ID }}
| Check Type | Best For | Keep It Healthy | |---|---|---| | Browser check | Critical user journey | Use role locators and few steps | | API check | Availability and contracts | Assert status, body, and latency | | Heartbeat | Scheduled jobs | Alert on missing signal | | Multistep check | Business workflow | Use stable synthetic accounts | | Private location | Internal apps | Keep runners patched | | Frequency setting | Cost and signal control | Match business criticality |
development
Generate test data from the schemas you already have. Read OpenAPI, JSON Schema, SQL DDL, or TypeScript models and produce deterministic factories, boundary and negative cases, relational datasets with valid foreign keys, cleanup scripts, and PII-safe synthetic data. Production records never leave the machine.
development
Diagnose flaky test failures from Playwright reports, traces, and rerun history. Classify each failure as product, test, environment, data, or unknown with cited evidence and a proposed fix. Never auto-modifies code without opt-in.
tools
Test LLM, RAG, MCP, and agentic systems end to end. Build golden datasets, run deterministic checks and LLM judges, score retrieval, probe prompt injection, verify tool use, and gate CI on thresholds. Orchestrates DeepEval, Ragas, promptfoo, and Langfuse.
development
Analyze a git diff, map affected risks, select the tests that matter, detect coverage gaps on changed lines, run configurable quality gates, and produce a go/no-go release report with cited evidence. Recommends only; never merges or deploys.