AI Job Search Assistant
For job seekers, a full-stack AI assistant providing a one-stop closed loop for job matching, resume and cover letter customization, interview preparation, and application tracking.
AI Job Search Assistant
For job seekers, a full-stack AI assistant providing a one-stop closed loop for job matching, resume and cover letter customization, interview preparation, and application tracking.
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Description
Full-stack job search assistant covering the complete closed loop from profile creation, job search, fit assessment, CV/cover letter customization, interview preparation, to result tracking. Based on the AFP architecture, it employs a draft-review dual-agent adversarial mechanism, with built-in honesty guardrails (no fabricated skills/experience), ATS keyword compliance checks, relevance-weighted CV trimming, and supports back-calibrating the evaluation framework from actual application outcomes.
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ResearchOffer Toolkit
A job search system backed by 10 years of experience at a major Silicon Valley company, packaging genuine hiring insights and job search methodologies into AI. Offer Toolkit | AI Job Search Assistant From "discovering your dream job" to "landing the offer," it breaks down the entire job search process into three smart modules: ① JD Decoder Deeply analyze the job description and generate a personalized Offer Strategy Report: - Whether it's worth applying - Role fit assessment - Core strengths and skill gaps - Interview focus and high-probability question predictions ② Resume Builder Transform your experience from a "job description" into a compelling impact story that recruiters recognize: - Automatically structure your personal experience - Optimize project descriptions and quantify achievements - Generate ATS-friendly, high-quality resumes - Supports 11+ print-ready professional templates ③ Behavioral Story Library Mine your real experiences to build reusable interview story assets: - Extract key projects and growth experiences - Automatically convert to STAR Framework - Build a personal Behavioral Interview Story Bank - Efficiently handle "Tell me about a time..." questions Whether you're debating "should I apply for this job," want to "optimize your resume," need to "analyze a JD," or are preparing for your next behavioral interview, Offer Toolkit will automatically identify your needs and route you to the most suitable AI module. Keywords: Job Search, Offer, Career, Job Hunt, JD, Job Description, Resume, CV, Behavioral Interview, STAR, Tell me about a time, Interview Preparation ------------------------------------- job-description-skill: Paste a JD and your resume, and you'll get an HTML report telling you: whether you should apply for this job, how well you match, what gaps exist, what the interview will likely ask, whether the salary is reasonable, and what to do in the next 6 weeks. resume-skill: Helps you polish your existing resume, import from LinkedIn, or write one from scratch through conversation. Provides 11 print-ready templates (Classic-ATS, Ledger, Tech Compact, Modern Sidebar, Pillar, Elegant Serif, Atelier, Timeline, Swiss, Executive, Color-block). Each time, it provides two files: one directly printable as PDF, and one you can edit by clicking words in the browser. bq-skill: It doesn't give you ready-made answers; instead, it helps you dig out things you've actually done and organize them into a reusable story library. It will ask about your experiences step by step, help you clarify your thinking using STAR/CAR, and tag them with labels like "decision-making" and "overcoming adversity." It saves one copy in Chinese and one in English, so you can use the same story for different behavioral questions next time. It can also look at a JD and predict 20 questions the company might ask, helping you prepare one by one. Three shared rules: 1. No fabrication. All experiences, responsibilities, and numbers come from what the user has actually said. It can help rephrase weak expressions, but it will never invent companies, positions, achievements, or quantified numbers. Numbers must be verified with the user. 2. Ask only one question at a time. Digging stories, building resumes, and preparing BQs are conversations, not questionnaires. 3. Structure first, then output. First convert to a standard data model, confirm it's correct, then render HTML or generate answers.
Interview Practice Coach
Helps job seekers prepare for the full interview process: review existing materials, break down the role, uncover STAR stories, predict tailored questions, and prepare follow-up strategies. Produces a structured interview prep document, then conducts modular mock interviews with feedback.
Research Proposal Assistant
Designed for university faculty and researchers, this assistant turns an initial research idea into an executable, fundable project plan. It covers national- and provincial-level humanities and social sciences projects, teaching reform projects, and other research project types. Provide the project type and application guidelines or template, research direction, existing成果, and personal and institutional information. The assistant helps clarify the topic, focus the research question, and build a complete foundation for the proposal around the research problem, application requirements, and review logic. As the project develops, the assistant can support academic searches, literature reviews, research gap analysis, feasibility assessments for data and methods, comparable project matching, and research design adjustments. It helps ensure that literature, data, and funding information are authentic and verifiable, while incorporating AI, contemporary relevance, and methodological innovation into the topic and innovation points. Once the research plan is mature, it can draft an initial proposal based on the application guidelines or blank template you provide, simulate different reviewer perspectives, and suggest revisions through to the final draft. The project retains stage outputs, version records, and the basis for changes. It can ultimately organize a proposal, technical roadmap, research framework diagram, innovation logic diagram, progress Gantt chart, and other research visuals. For tasks requiring an external environment, such as full-text PDF analysis, code execution, web scraping, or large-scale data processing, the assistant clearly identifies handoff tasks and supports filling in results and continuing the work, helping move the project from preparation through a properly formatted final proposal.
Information
- Version
- v2
- Last updated
- Runtime credits
- Usage-based
- Models
- Auto
