Skip to content

Restructure AI integrations docs with Skills and Rules pages #177

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
stefanjudis merged 11 commits into from
Feb 11, 2026
Merged

Restructure AI integrations docs with Skills and Rules pages #177

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
11 commits
Select commit Hold shift + click to select a range
34939aa
Restructure AI integrations docs with Skills and Rules pages
stefanjudis Feb 10, 2026
d577a86
Update snippets/agent-example.mdx
stefanjudis Feb 10, 2026
b28f866
Update integrations/ai/skills.mdx
stefanjudis Feb 10, 2026
1b0d796
Update AI integrations section in sitemap to match docs.json
stefanjudis Feb 10, 2026
8fead3d
Add quotes around example prompts in AI docs
stefanjudis Feb 10, 2026
29c1c3c
Update CLI overview to reference Skills and Rules pages
stefanjudis Feb 10, 2026
db298a0
Update cli/overview.mdx
stefanjudis Feb 11, 2026
e48c2d8
Update cli/overview.mdx
stefanjudis Feb 11, 2026
5a40baf
Update integrations/ai/overview.mdx
stefanjudis Feb 11, 2026
bd1ed44
Update integrations/ai/skills.mdx
stefanjudis Feb 11, 2026
076b527
Merge branch 'main' into document-agent-skill-1
stefanjudis Feb 11, 2026
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
25 changes: 11 additions & 14 deletions cli/overview.mdx
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -7,7 +7,7 @@ sidebarTitle: 'Overview'
import MainCicdCards from "/snippets/main-cicd-cards.mdx"

The Checkly CLI gives you a JavaScript/TypeScript-native workflow for coding, testing and deploying synthetic
monitoring at scale, from your code base. The Checkly CLI comes with **native `@playwright/test` support.** No lock-in,
monitoring at scale, from your code base. The Checkly CLI comes with **native `@playwright/test` support.** No lock-in,
just write standard `*.spec.ts` files.

## Starting your first project
Expand All @@ -31,7 +31,7 @@ After this, let's dry run the Checks in your new project against the global Chec
npx checkly test
```

This should report the following output to your terminal
This should report the following output to your terminal

```
Running 4 checks in eu-west-1.
Expand All @@ -53,25 +53,22 @@ Lastly, you deploy your Checks and related alert channels to Checkly, so we run
npx checkly deploy
```

You just created your entire synthetic monitoring setup with API and Playwright-based Browser Checks from your code base!
You just created your entire synthetic monitoring setup with API and Playwright-based Browser Checks from your code base!
Open up [your Checkly dashboard](https://app.checklyhq.com) and you should see your check, ready to start monitoring around the clock.

For a custom installation check out [our installation docs](/cli/installation/).

## Using AI IDEs and Copilots
## Using Agents, AI IDEs and Copilots

Checkly is designed to work with AI IDEs and Copilots. You can use your preferred provider to generate code for API
Checkly is designed to work with Agents, AI IDEs, and Copilots. You can use your preferred provider to generate code for API
Checks, Browser Checks and all other constructs.

<Columns cols={3}>
<Card title="GitHub Copilot" icon="/images/github-copilot-icon.svg" href="/integrations/ai/copilot">
Download the Checkly instructions file and let copilot generate Checkly CLI code for you.
<Columns cols={2}>
<Card title="Checkly Skills" href="/integrations/ai/skills">
Install Checkly Skills and let AI agents generate Checkly monitoring code for you.
</Card>
<Card title="Cursor" icon="/images/cursor-icon.svg" href="/integrations/ai/cursor">
Download the Checkly `.mdc` rules file and let Cursor generate Checkly CLI code for you.
</Card>
<Card title="Claude Code" icon="/images/claude-icon.svg" href="/integrations/ai/claude">
Download the Checkly rules file and let Claude generate Checkly CLI code for you.
<Card title="Checkly Rules" href="/integrations/ai/rules">
Include the Checkly Rules in your conversations to generate Checkly monitoring code for you.
</Card>
</Columns>

Expand All @@ -80,4 +77,4 @@ Checks, Browser Checks and all other constructs.
After kicking the tires, you should delegate the testing and deploying of your checks to your CI/CD pipeline. Check our
docs on [setting up the Checkly CLI with your favourite CI/CD platform](/integrations/ci-cd/overview).

<MainCicdCards />
<MainCicdCards />
8 changes: 3 additions & 5 deletions docs.json
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -351,13 +351,11 @@
"group": "Integrations",
"pages": [
{
"group": "AI coding asssistants",
"group": "AI Agents & Coding Assistants",
"pages": [
"integrations/ai/overview",
"integrations/ai/claude",
"integrations/ai/cursor",
"integrations/ai/copilot",
"integrations/ai/windsurf"
"integrations/ai/skills",
"integrations/ai/rules"
]
},
{
Expand Down
37 changes: 0 additions & 37 deletions integrations/ai/claude.mdx
View file
Open in desktop

This file was deleted.

29 changes: 0 additions & 29 deletions integrations/ai/copilot.mdx
View file
Open in desktop

This file was deleted.

35 changes: 0 additions & 35 deletions integrations/ai/cursor.mdx
View file
Open in desktop

This file was deleted.

52 changes: 21 additions & 31 deletions integrations/ai/overview.mdx
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -5,9 +5,11 @@ sidebarTitle: 'Overview'
keywords: ['mcp', 'ai', 'rules', 'generate checks', 'agents', 'context']
---

import { YoutubeEmbed } from "/snippets/youtube-embed.jsx"
import AgentExamples from "/snippets/agent-example.mdx"

From the beginning, Checkly has bet on [Monitoring as Code](/concepts/monitoring-as-code) which lets you create and control your monitoring infrastructure entirely using code. [Checkly constructs](/constructs/overview) can reflect all your monitoring properties.
From the beginning, Checkly has bet on [Monitoring as Code](/concepts/monitoring-as-code) which lets you create and control your monitoring infrastructure entirely using code.

By default, [Checkly constructs](/constructs/overview) reflect all your monitoring properties.

```ts api.check.ts
import { ApiCheck, AssertionBuilder } from "checkly/constructs"
Expand Down Expand Up @@ -36,51 +38,39 @@ npx checkly deploy

**The Monitoring as Code workflow is by default AI-native** because LLMs are excellent at writing and editing Checkly constructs code and modern AI agents can execute CLI commands easily.

You only need to provide the necessary context about Checkly and your monitoring setup to your AI agent of choice.

## Add custom Checkly rules to your AI conversation
Provide the necessary Checkly context and let your AI agent of choice do the rest.

The [`checkly.rules.md` file](https://www.checklyhq.com/docs/ai/checkly.rules.md) includes best practices, example code and required CLI commands to give your AI workflow enough context to perform Checkly-related tasks.
<AgentExamples />

Once the Checkly rules are included in your AI context window, your agent can effectively assist you in managing your monitoring setup.
## Add Checkly context to your AI agent conversation

It will be able to:

<Card title="Create new checks, alert channels or other constructs" horizontal>
"Can you create a new `BrowserCheck` monitoring `example.com`"
</Card>
Install [Checkly Skills](/integrations/ai/skills) or add the [Checkly Rules](/integrations/ai/rules) to your AI conversation to give your AI agent enough context to perform Checkly-related tasks.

<Card title="Gather information about the current monitoring setup" horizontal>
"What are the currently used monitoring locations?"
<Columns cols={2}>
<Card title="Checkly Skills" href="/integrations/ai/skills" cta="Get started">
Let your agents pull in all required Checkly context on demand.
</Card>

<Card title="Bulk-update your monitoring resources" horizontal>
"Can you change all checks to run every 5 minutes instead of every 10 minutes?"
<Card title="Checkly Rules" href="/integrations/ai/rules" cta="Get started">
Include the entire Checkly context in commands or documentation.
</Card>
</Columns>

With enough application context you can even create checks for your specific use cases.
### Skills vs Rules

<Card title="Analyze application code and create the monitoring setup" horizontal>
"Can you create new API Checks for the application API endpoints?"
</Card>

Find a live session explaining how to automate Checkly monitoring with AI below and [read the "Agentic Workflows" guide](/guides/agentic-workflows) for more details.
**Use Skills** when your AI agent supports the [Agent Skills](https://agentskills.io) standard. Skills load context on demand, keeping your agent's context window lean until Checkly-related tasks arise. This is the recommended approach for compatible agents.

<YoutubeEmbed id="WqTXa7GCk-k" title="No Coding! Just Prompting! Getting the most out of AI for Application Reliability." />
**Use Rules** when your agent doesn't support skills or when you want the Checkly context always available. Rules files are loaded at session start and provide consistent context throughout your conversation.


## Why is there no Checkly MCP server?
## Why is there no Checkly MCP server (yet)?

The MCP concept is often used to enable LLMs to interact with external systems. It acts as a bridge between the AI model and the target system, translating natural language commands into actionable API calls or code snippets.

**With Monitoring as Code, Checkly already provides a native way to control your monitoring infrastructure via code and the command line.**

Whether you need to create new resources or update existing ones, AI can write and update the necessary construct files and execute the Checkly CLI commands autonomously.

## Additional Resources

Follow these guides if you use one of the popular AI coding tools:

- [Claude Code](/integrations/ai/claude)
- [Cursor](/integrations/ai/cursor)
- [GitHub Copilot](/integrations/ai/copilot)
<Tip>
We are researching additional AI-native workflows. [Let us know in the public roadmap](https://feedback.checklyhq.com/p/checkly-mcp) if you are interested in more agent-friendly integrations.
</Tip>
125 changes: 125 additions & 0 deletions integrations/ai/rules.mdx
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,125 @@
---
title: 'Checkly Rules'
description: 'Use the provided Checkly rules to control, update and deploy your monitoring.'
sidebarTitle: 'Checkly Rules'
---

import AgentExamples from "/snippets/agent-example.mdx"
import { YoutubeEmbed } from "/snippets/youtube-embed.jsx"

The [`checkly.rules.md` file](https://www.checklyhq.com/docs/ai/checkly.rules.md) includes best practices, example code and required CLI commands to give your AI workflow enough context to perform Checkly-related tasks.

Once the Checkly rules are included in your AI context window, your agent can effectively assist you in managing your monitoring setup.

It will be able to:

<AgentExamples />

With enough application context, you can even create checks for your specific use cases.

<Card title="Analyze application code and create the monitoring setup" horizontal>
"Can you create new API Checks for the application API endpoints?"
</Card>

Find a live session explaining how to automate Checkly monitoring with AI below and [read the "Agentic Workflows" guide](/guides/agentic-workflows) for more details.

<YoutubeEmbed id="WqTXa7GCk-k" title="No Coding! Just Prompting! Getting the most out of AI for Application Reliability." />

## Claude Code

Claude Code reads instructions from `CLAUDE.md` files. You can place these files globally (in your home directory) or locally (in your project root). Claude Code automatically includes these files in its context.

To use Checkly rules with Claude Code, download the rules file and reference it in your `CLAUDE.md`:

<Tabs>
<Tab title="Mac and Linux">

```bash
mkdir -p .claude &&
curl -o .claude/checkly.rules.md https://www.checklyhq.com/docs/ai/checkly.rules.md -L
echo "- examine checkly.rules.md for code generation rules" >> .claude/CLAUDE.md
```

</Tab>
<Tab title="Windows">

```powershell
New-Item -ItemType Directory -Path ".claude" -Force
Invoke-WebRequest -Uri "https://www.checklyhq.com/docs/ai/checkly.rules.md" -OutFile ".claude\checkly.rules.md"
Add-Content -Path ".claude\CLAUDE.md" -Value "- examine checkly.rules.md for code generation rules"
```

</Tab>
</Tabs>

Restart your Claude Code session to load the instructions.

## GitHub Copilot

GitHub Copilot reads project-level instructions from `.github/copilot-instructions.md`. This file is automatically included in Copilot's context for all chat interactions.

<Tabs>
<Tab title="Mac and Linux">

```bash
mkdir -p .github && curl -o .github/copilot-instructions.md "https://www.checklyhq.com/docs/ai/checkly.rules.md" -L
```

</Tab>
<Tab title="Windows">

```powershell
New-Item -ItemType Directory -Path ".github" -Force
Invoke-WebRequest -Uri "https://www.checklyhq.com/docs/ai/checkly.rules.md" -OutFile ".github\copilot-instructions.md"
```

</Tab>
</Tabs>

## Cursor

Cursor uses `.mdc` (Markdown Cursor) files stored in `.cursor/rules/` for project-specific instructions. These rules are automatically included in Cursor's context.

<Tabs>
<Tab title="Mac and Linux">

```bash
mkdir -p .cursor/rules && curl -o .cursor/rules/checkly.mdc "https://www.checklyhq.com/docs/ai/checkly.rules.md" -L
```

</Tab>
<Tab title="Windows">

```powershell
New-Item -ItemType Directory -Path ".cursor\rules" -Force
Invoke-WebRequest -Uri "https://www.checklyhq.com/docs/ai/checkly.rules.md" -OutFile ".cursor\rules\checkly.mdc"
```

</Tab>
</Tabs>

You can reference the rules file explicitly using `@checkly.mdc` in your Cursor chats.

## Windsurf

Windsurf stores rules in `.windsurf/rules/` as Markdown files. These are included in the AI context when you interact with Windsurf's assistant.

<Tabs>
<Tab title="Mac and Linux">

```bash
mkdir -p .windsurf/rules && curl -o .windsurf/rules/checkly.md "https://www.checklyhq.com/docs/ai/checkly.rules.md" -L
```

</Tab>
<Tab title="Windows">

```powershell
New-Item -ItemType Directory -Path ".windsurf\rules" -Force
Invoke-WebRequest -Uri "https://www.checklyhq.com/docs/ai/checkly.rules.md" -OutFile ".windsurf\rules\checkly.md"
```

</Tab>
</Tabs>

You can reference the rules file using `@checkly.md` in your Windsurf chats.
Loading