resumePolice's "Critique-Parsing-Recommendation" model is a three-step process:
- criticize: AI will point out problems in the resume, such as "vague project descriptions" and "improperly listed technology stacks", revealing loopholes like a strict "police officer".
- analyze: Then explain the negative impact of the problem, such as "Vague descriptions can make recruiters doubt the authenticity of the program," to help users understand the root cause of the problem.
- suggestion: Finally, provide specific optimization options, for example, suggesting that "project descriptions follow the STAR principles" and clarify the role and contribution of the user in the project.
This model is implemented through predefined prompts (Prompts) driving a large-scale language model designed to provide professional, actionable feedback.
This answer comes from the articleresumePolice: an AI tool to review and optimize resumes based on Dify deploymentsThe
May not be reproduced without permission:AI productivity tools " How does resumePolice implement the Critique-Parsing-Recommendation model for resumes?
