> For the complete documentation index, see [llms.txt](https://academy.pentaho.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://academy.pentaho.com/pentaho-data-integration/data-integration/enterprise-solution/metadata-injection.md).
# Metadata Injection
Metadata Injection ..
{% hint style="info" %}
#### **Introduction**
Metadata injection inserts data from various sources into a transformation at runtime. This insertion reduces repetitive ETL tasks.
For example, you might have a simple transformation to load transaction data values from a supplier, filter specific values, and output them to a file. If you have more than one supplier, you would need to run this simple transformation for each supplier. Yet, with metadata injection, you can expand this simple repetitive transformation by inserting metadata from another transformation that contains the ETL Metadata Injection step.
The step coordinates the data values from the various inputs through the metadata you define.
The repetitive transformation is known as the template transformation. The template transformation is called by the ETL Metadata Injection step.
{% endhint %}
MDI
***
---
# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.
## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.
Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:
```
GET https://academy.pentaho.com/pentaho-data-integration/data-integration/enterprise-solution/metadata-injection.md?ask=&goal=
```
`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.
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.
