CLEAR Framework
Clavix applies the CLEAR framework to evaluate and improve every prompt and PRD it touches. CLEAR was developed by Dr. Leo Lo and published in the Journal of Academic Librarianship (July 2023). The acronym stands for Concise, Logical, Explicit, Adaptive, and Reflective.
Components
| Component | Focus | Typical improvements |
|---|---|---|
| Concise | Reduce noise and pleasantries | Remove filler, tighten language, emphasize action verbs |
| Logical | Improve flow and ordering | Restructure prompts into context → requirements → constraints → outputs |
| Explicit | Clarify expectations | Specify persona, tone, output format, success criteria, examples |
| Adaptive | Offer alternative approaches | Provide variations, alternative structures, temperature suggestions |
| Reflective | Encourage validation | Add checklists, edge cases, fact-checking steps, risk mitigation |
How Clavix uses CLEAR
clavix fastscores Concise, Logical, and Explicit, producing a single improved prompt and a list of labeled changes.clavix deepunlocks Adaptive and Reflective components, delivering alternative phrasings, structures, and validation checklists.clavix prdvalidates generated quick PRDs for the C/L/E components unless validation is explicitly skipped.clavix summarizecan optionally re-run CLEAR on extracted prompts to give you an optimized variant ready for AI agents.
Further reading
- Framework guide: https://guides.library.tamucc.edu/prompt-engineering/clear
- Research paper (PDF): https://digitalrepository.unm.edu/cgi/viewcontent.cgi?article=1214&context=ulls_fsp
Refer back to the Command reference for details on how each command surfaces CLEAR insights.