# AI Development 🤖

## Overview

We're big fans of using AI tools for development - when done safely. We've created two context files to help AI coding assistants understand our API and generate accurate code.

## Context Files

[**llms.txt**](https://docs.cardscan.ai/llms.txt) - Table of contents for quick navigation\
[**llms-full.txt**](https://docs.cardscan.ai/llms-full.txt) - Complete API documentation and examples

Use `llms.txt` when you need to find something quickly. Use `llms-full.txt` when implementing features or debugging.

## Additional Resources

* [**OpenAPI Spec**](https://github.com/CardScan-ai/api-clients/blob/main/openapi.yaml) - For generating clients in any language
* [**API Clients**](https://github.com/CardScan-ai/api-clients) - Official client libraries for TypeScript, Python, Swift, Kotlin, and Dart

{% hint style="success" %}
**AI in Production:** Check out [Claude Code Watchdog](https://github.com/CardScan-ai/claude-code-watchdog) - a 100% AI-generated tool we use daily. It filters out flaky test noise so we can focus on real bugs.
{% endhint %}


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.cardscan.ai/ai-and-automation/ai-development.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.