Use a secondary prompt to rewrite and clarify user requests before execution.
01 The Concept
Users often write vague prompts. Rephraser loops use a lightweight model to rephrase the user's intent into a structured, descriptive prompt, check if the user agrees, and then route the refined instructions to the main model, significantly improving success rates.
02 Weak vs. Strong
EX 01Rephraser Pipeline Setup
# 1. Expand query
expanded = call_llm(model="gpt-3.5-turbo", prompt="Expand query 'make logo' into a detailed graphic brief listing style, subject, and color scheme.")
# 2. Confirm description
user_approved = ask_user("Is this what you want? " + expanded)
# 3. Execute generator
if user_approved:
call_llm(model="midjourney-agent", prompt=expanded)
→ Why it works
Vague instructions yield generic outputs. Expanding the brief first ensures the specialist model receives high-quality parameters.
03 Key Points
01Query Expansion: Turning short queries into descriptive task descriptions.
02Intent Refinement: Identifying implicit parameters (target audience, length) in short prompts.
03Verification Loop: Showing the expanded query to the user for confirmation.
04Specialist Routing: Selecting the best templates based on the expanded intent.
05Bypassing Vague Inputs: Preventing garbage-in-garbage-out failures in pipelines.
04 Model-Specific Notes
Claude is highly descriptive and makes an excellent query expander, generating detailed templates for downstream tasks.
05 For Your Role
It's like a translator who takes your short, casual requests and writes a polite, formal letter on your behalf.