resumePolice: an AI tool to review and optimize resumes based on Dify deployments

resumePolice is an open source project on GitHub that leverages the power of large-scale language models to help job seekers analyze, review, and optimize their resumes. The core of the project is a "critique - analysis - recommendations" model , designed to directly point out the problems in the resume , analyze the negative impact of these problems may bring , and give specific , actionable recommendations for modification . In addition to resume review, the project also extends its functionality to simulate the perspective of a senior technology officer (CTO), generating systematic and in-depth interview questions based on the content of the resume to help job seekers prepare for the real world. For the convenience of non-technical users, resumePolice provides pre-packaged Dify workflow files. Users simply import these files into Dify, an AI application development platform, to quickly build a resume optimization or interview simulation tool of their own, with no code required throughout the process.

Function List

• Resume review and revisionCritique-Analyze-Suggest: A three-stage model that evaluates the content of a resume, identifies problems with formatting, wording, project descriptions, etc., and provides options for optimization.
• Generate interview questionsThe built-in two different styles of interviewer prompts can be used to generate a series of in-depth and potentially "catchy" interview questions based on resume content from the perspective of the legendary CTO.
• Dify Workflow Integration: Provides multiple versions of.ymlWorkflow files, including text-generated, conversational (Chat), and other modes, allow users to import and use them with one click on the Dify platform.
• Conversational Resume Revision: Supports the ability to pass a file named简历警察Chat's conversational workflow with multiple rounds of communication with AI to enable follow-up questions and iterative revisions to resumes.
• Open Cue Thesaurus: The project provides all the core functionality directly with hint word text for developers or advanced users to use in other platforms or customized environments.

Using Help

resumePoliceThe service is mainly provided through the Dify platform, which encapsulates complex AI calls into a tool that ordinary users can easily get started with. The following is a detailed description of the usage process and features.

Core concepts

Before you start using it, you need to understand how it works. resumePoliceFollow the "Critique-Analyze-Suggest" model:

1. criticize: AI will act like a strict "policeman" and point out the problems in your resume, such as "vague project description", "improperly listed technology stack", etc..
2. analyzeIt then explains why this is a problem, such as "Vague descriptions can make recruiters doubt the authenticity of your program."
3. suggestion: At the end, it will give specific suggestions for changes, such as "The project description should follow the STAR principles, specifying your role and contribution.

Installation and Configuration Process

utilizationresumePoliceNo local installation or programming is required; the key is to configure the Dify platform.

Step 1: Get the workflow file
interviewsresumePoliceThe GitHub repository for theworkflowdirectory to find the required.ymlfile and download it.

• 简历警察V3.yml: Recommended version for generating comprehensive resume review reports.
• 简历警察Chat.yml: A conversational version that allows you to iterate on your resume as if you were chatting.
• 简历警察(笔录版)V1.yml / V2.yml: Used to generate interview questions.

Step 2: Importing Workflows in Dify

1. Log in to your Dify platform account.
2. On the application creation page, there are two ways to import a workflow:
   • Mode 1Click on the "Import DSL file" button and select the file you just downloaded..ymlDocumentation.
   • Mode 2: Directly download the.ymlThe file is dragged and dropped into Dify's application page.

Step 3: Select Model and Configure API Key

1. After the workflow is imported, you need to configure a Large Language Model (LLM) as the backend engine for it.
2. In Dify's configuration interface, select an available model, such as Google'sGeminiSeries.
3. In the API Key configuration area, fill in the valid API key for your selected model. If you don't have one, you need to go to the official website of the corresponding big model (e.g. Google AI Platform) to apply for it.
4. When the configuration is complete, save the settings. At this point, the application is ready.

Main Functions Operation Guide

1. How to Review a Resume
   • utilization简历警察V3Workflow.
   • Go to the application runtime screen and you will see a text input box.
   • Paste your full resume into the input box.
   • Click Run, wait a moment, the AI will output a detailed review report on the right side, including the full content of "Criticize - Analyze - Recommend".
2. How to Talk to AI to Revise Your Resume
   • utilization简历警察ChatWorkflow.
   • This workflow creates a chatbot.
   • You can send your resume and then ask for changes as if you were talking to a real person, such as "Help me make my project experience more appealing" or "Is this job description too wordy?" .
   • The AI will keep providing new modified versions based on your follow up questions.
3. How to Generate Interview Questions
   • utilization简历警察(笔录版)V1maybeV2Workflow.
   • Again, a resume is used as input.
   • The AI will simulate as an experienced CTO and generate a list of interview questions based on this resume's work history, tech stack, and project details.
   • V1version of the question focuses more on scenario-based and hypothetical expansion, while theV2The version is more direct, focusing on the technology and the project itself.

application scenario

1. Resume Optimization for Job Seekers
   Whether you're a recent graduate or a senior citizen in the workplace, before you submit your resume you can use theresumePoliceConduct a comprehensive "medical checkup". It can identify presentation gaps and formatting issues that are difficult to detect, and optimize your resume with AI recommendations to make it more competitive among applicants.
2. Interview Preparation
   Candidates can input their resumes into the "transcribed" workflow and anticipate the questions the interviewer may ask in advance. This not only helps you organize the details of your project, but also simulates the stress of a real interview, so you can be prepared.
3. Recruiter assistance
   For inexperienced interviewers or HR who need to quickly screen a large number of resumes, the tool can automatically generate a set of in-depth and targeted technical interview questions based on the candidate's resume, which can be used as a reference in the interview session to improve the recruitment efficiency and quality.
4. AI Applied Learning
   For developers or AI enthusiasts who want to learn how to build LLM applications (LLMOps).resumePoliceis an excellent example. By examining its open source cue words and Dify workflow configuration, one can quickly understand and grasp how to turn an idea into an actual usable AI application.

QA

1. resumePoliceWhat is it?
   It is an AI tool open-sourced on GitHub that provides a set of Prompts and Dify workflows for reviewing and revising resumes and generating mock interview questions.
2. Do I have to pay to use this tool?
   resumePoliceThe project itself is completely free and open source. However, it relies on the Dify platform and a large language model (such as Gemini or GPT) to run, and the use of these third-party services may incur costs depending on their respective pricing strategies.
3. I'm completely tech savvy, can I use it?
   Can. The best feature of the tool is the Dify workflow documentation for non-technical users. All you need to do is to follow the guidelines of the usage help and perform click, drag and drop and import operations on the Dify platform without writing any code to use it.
4. What is Dify?
   Dify is an LLM application development platform that helps developers and non-developers alike to more easily create and operate AI applications based on large language models.resumePoliceIt is this platform that is utilized to encapsulate complex technologies into simple products.
5. What was the quality of the review results and interview questions?
   The quality depends heavily on the design of the cue words at its core.resumePoliceThe prompts mimic the thinking of senior human resources and technology officers, using the Critique-Parsing-Recommendation (C-PR) model and exploration models such as P.O.S.E.R., which are designed to provide professional, in-depth feedback.