5C Prompt Contracts: A Minimalist, Creative-Friendly, Token-Efficient Design Framework for Individual and SME LLM Usage
Ugur Ari

TL;DR
The paper introduces the 5C Prompt Contract, a minimalist and systematic framework for prompt design that enhances token efficiency and creative flexibility in LLM applications, especially for SMEs.
Contribution
It presents the 5C framework, a simple five-component schema that improves prompt reliability, interpretability, and efficiency compared to complex existing methods.
Findings
Achieves superior token efficiency across multiple LLMs
Maintains rich, consistent outputs with minimal prompt components
Suitable for resource-limited users and SMEs
Abstract
The progression from traditional prompt engineering to a more rigorous discipline of prompt design marks a pivotal shift in human-LLM interaction. As Large Language Models (LLMs) become increasingly embedded in mission-critical applications, there emerges a pressing need for frameworks that are not only explicit and systematic but also minimal enough to remain practical and broadly accessible. While many existing approaches address prompt structuring through elaborate Domain-Specific Languages (DSLs) or multi-layered templates, such methods can impose significant token and cognitive overhead, potentially constraining the model's creative capacity. In this context, we propose the 5C Prompt Contract, a framework that distills prompt design into five intuitive components: Character, Cause, Constraint, Contingency, and Calibration. This minimal cognitive schema explicitly integrates…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
