What is Prompt Template?
Prompt Template is a reusable prompt structure that combines fixed instructions with variable inputs to produce consistent LLM requests.
How It Works
A prompt template turns prompt writing from ad hoc text into an application artifact. It usually contains fixed instructions, variable placeholders, examples, retrieved context, tool schemas, and output requirements. Good templates separate user input from instructions, escape or delimit untrusted content, and make versioned behavior easier to test. Poor templates mix data and directives, invite prompt injection, and make failures difficult to reproduce.
Key Characteristics
- Combines fixed prompt text with runtime variables
- Supports consistent behavior across requests and product surfaces
- Can include examples, schemas, retrieved context, and formatting rules
- Should clearly separate instructions from untrusted user or retrieved content
- Benefits from versioning, tests, and structured rendering
Common Use Cases
- Generating consistent summaries from different documents
- Rendering RAG prompts with retrieved context blocks
- Passing structured user inputs into a classification prompt
- Maintaining few-shot examples across model versions
- Testing prompt changes in CI before release
Example
Loading code...Frequently Asked Questions
Why use a prompt template instead of plain strings?
Templates make prompt behavior repeatable, reviewable, testable, and safer when runtime variables change.
Can prompt templates prevent prompt injection?
They help by separating instructions from data, but they do not replace retrieval controls, tool permissions, and safety checks.
What should be versioned in a prompt template?
Version fixed instructions, examples, variable schema, output schema, and model-specific rendering rules.
How should variables be inserted into templates?
Use explicit delimiters, escaping, schema validation, and clear labels so user data is not confused with instructions.