Markdownify Token Modifier

Introduction

The Markdownify Token Modifier module provides a deterministic, efficient, and abstracted way to convert HTML field tokens into Markdown format.

While Large Language Models (LLMs) can convert HTML to Markdown, doing so via an AI prompt is inherently non-deterministic, introduces API latency, and incurs unnecessary costs. This module solves the problem by providing a local, CPU-bound conversion layer using the established Markdownify ecosystem.

This module was created specifically to address a current limitation affecting AI Automators.

Why use this module?

• Determinism: Unlike LLM-based conversion, this provides consistent output every time.
• Performance: Conversions happen locally on your server, avoiding network round trips to AI providers.
• Abstraction: By leveraging Markdownify's pluggable system, the conversion logic remains opaque to the consumer. You can swap the underlying League converter implementation without changing your tokens or downstream logic.
• Efficiency: There is no need to store intermediate Markdown results in "disposable" fields; the conversion happens in-place during token replacement.

Dependencies

• Markdownify
• Token Modifier

Usage

The module integrates with the Token Modifier system to provide a markdownify modifier.

General Pattern

The syntax follows the standard token modifier format: [token-modifier:markdownify:TARGET_TOKEN]

Example: [token-modifier:markdownify:node:field_content]

Integration with AI Automator

This module is particularly useful when preparing data for the AI Automator within the Drupal AI suite:

1. Navigate to the AI Automator configuration for your desired field.
2. Set Automator Input Mode to Advanced Mode (Token).
3. In the Automator Prompt (Token) field, identify the token you wish to convert (e.g., [node:body]).
4. Wrap the token with the modifier: [token-modifier:markdownify:node:body]
5. The AI will now receive a clean, structured Markdown version of your HTML content, reducing token usage and improving prompt clarity.