What the RTF Framework Is
The RTF Framework is a three-part prompt pattern that tells the model who it is, what to do, and exactly how the answer should look. Instead of sending a loose question, you specify Role, Task, and Format explicitly. This works across GPT-4o, Claude 4.6 Sonnet, Gemini 2.5 Pro, and local models you run via Ollama or LM Studio.
RTF is intentionally minimal. With only three fields, it is easy to remember, fast to fill in, and flexible enough for many day-to-day tasks. You can treat it as a "default prompt skeleton" whenever you are not sure which specialized framework to use.
The Three RTF Components
A strong RTF prompt clearly defines each of the three components so the model has no ambiguity about its job. You can write them as labeled lines or as one sentence that still contains all three parts.
Typical definitions:
- Role: The perspective or expertise the model should adopt (for example "You are a senior data analyst").
- Task: The concrete action you want, described in one or two sentences.
- Format: The structure, length, and style of the output (for example "3 bullet points plus a 2-sentence summary").
Why the RTF Framework Is Useful
The RTF Framework is useful because it gives you most of the benefits of more complex frameworks with almost no overhead. It forces you to make three decisions—who, what, and how—before sending a prompt.
Practical advantages include:
- Faster prompt writing than multi-section frameworks for routine work.
- Better consistency across models and runs, since the format is always explicit.
- Easy onboarding for teammates who can learn RTF in a few minutes and reuse it everywhere.
Example: Bad vs Good RTF Prompt
The difference between an unstructured request and an RTF-based prompt becomes clear when you look at the same task written both ways. Here is an example for summarizing a meeting.
Bad Prompt
"Summarize this meeting."
Good Prompt
"Role: You are an operations manager summarizing a project status meeting for senior leadership. Task: Read the transcript and identify the key decisions, open risks, and next steps discussed in the meeting. Format: Output a Markdown summary with three sections (`Decisions`, `Risks`, `Next steps`). Under each section, use 3–5 bullet points. Keep the total summary under 250 words."
The RTF version tells the model exactly how to think about the content and how to package the result so others can use it immediately.
When to Use the RTF Framework
You should use the RTF Framework when you want a simple, reusable pattern that still enforces clarity and structure. It is a strong default whenever you do not need long specifications or multi-step reasoning traces.
Typical use cases include:
- Short reports, recaps, and summaries for emails or chat.
- Drafting responses to customers or internal stakeholders with clear structure.
- Generating small code snippets or refactors with a specified output format.
- Quick content pieces like product blurbs, FAQ entries, or simple checklists.
How PromptQuorum Implements the RTF Framework
PromptQuorum is a multi-model AI dispatch tool that includes the RTF Framework as one of its built-in prompt structures so users can apply Role–Task–Format prompting in a consistent way. When you choose the RTF option inside PromptQuorum, the interface exposes fields for Role, Task, and Format and assembles them into a single well-formed instruction.
In PromptQuorum, the RTF Framework lets you:
- Fill in Role, Task, and Format once and send the same structured prompt to multiple models such as GPT-4o, Claude 4.6 Sonnet, Gemini 2.5 Pro, and local models configured through Ollama or LM Studio.
- Save RTF prompts as templates for recurring workflows—for example "weekly status summary," "customer reply draft," or "bug report recap."
- Share RTF templates across your team so that even non-experts can create prompts that produce consistent, structured outputs.
Combining RTF With Other Frameworks
You should combine the RTF Framework with other frameworks by treating RTF as your lightweight default and switching to heavier frameworks when constraints increase. A practical pattern is:
- Start with RTF for most new tasks where you just need clear structure quickly.
- Move to SPECS when you need strict schemas, examples, and constraints.
- Use TRACE or APE when you want explicit reasoning steps before the final answer.
- Use creative frameworks like CRAFT when audience and tone are central.