Do you have trouble translating your vision for music into precise keywords? If so, this guide on how to prompt using Free Text Search is for you.
It's a more natural way to search your music catalog and discover tracks. You can use complete sentences to describe soundscapes, film scenes, daily situations, activities, or environments. Prompts can be written in different languages and can include cultural references, so you're not forced to reduce your idea to a fixed set of tags.
Before you explore what Free Text Search can do, keep in mind that prompt-based search works best when your input is specific. The clearer you are, the easier it is to find what you're looking for.
Most large catalogs contain inconsistent metadata. Many were built before modern tagging standards, then expanded over time through different workflows. New music arrives faster than metadata teams can standardize it, especially with the volume from UGC and AI-generated releases, while older tracks remain described in ways that don't always support how music is searched for today.
Traditional search relies on tags and keyword logic. This approach can be effective for many searches, but it has limits when ideas are already highly specific, like with a detailed creative brief or a particular scene description. Translating concrete, nuanced needs into tags often loses critical details and context.
That's where natural language search makes a difference. Instead of defining a specific vision in terms of available tags, you can describe what you need directly or even paste a brief into the search bar. The system interprets intent, mood, and context in ways that complement tag-based discovery.
Free Text Search lets you look for music in the way you would naturally describe it. Write detailed prompts in full sentences, and the AI interprets the meaning behind your words to match intent with how tracks actually sound in your catalog.
This type of search is designed for situations where intent doesn't translate cleanly into keywords. Tag-based searches work well when attributes are fixed and clearly defined, and Similarity Search is useful when you already have a reference track and want to find music that sounds close to it.
In real-life workflows, searches rarely begin from the same place. Sometimes you'll start with sound, sometimes with a scene, and sometimes with context.
Sound-focused prompts should name what musical elements are present, then add how those elements are played or arranged. An extra cue about character or attitude can be included when it helps clarify intent.
Examples:
Common mistakes to avoid:
It helps to think like a director. Focus on the action or moment in the scene and what the viewer is experiencing. The clearer the image you describe, the easier it is for the search to interpret what kind of music belongs there.
Examples:
Common mistakes to avoid:
Combining activity, situation, and mood helps direct discovery toward abstract or niche ideas that don't translate cleanly into tags.
Examples:
Whether you're pitching music for sync, artists, or labels, looking to underscore a film scene, or setting the mood for an activity, Free Text Search empowers you to explore music in a whole new way.
As you craft your prompts, try to be specific and objective. Use concrete details like instruments, playing styles, and specific scenes or activities. You already have the resources in your catalog; Free Text Search helps you access them more effectively.