Chinese resume prompt builder: target role, skills, quantified achievements, document type. Assembles a prompt for any LLM. In your browser.
Chinese Resume Prompt Builder
Build a clean, structured Chinese-language prompt that asks an LLM to write or polish your 简历 (resume), 求职信 (cover letter) or 自我介绍 (self-introduction). Fill in the target role, your background, core skills, quantified results, document type, tone and length — then copy the prompt straight into DeepSeek, Qwen (通义千问), Doubao, Kimi, ERNIE or Zhipu. Everything is built in your browser; nothing is sent to a server and no model is called.
Tip: this builder only assembles text. Copy the result into DeepSeek / Qwen / Doubao / Kimi yourself — no model is called and nothing is sent anywhere. Do not include sensitive personal data such as ID numbers or addresses.
How the Chinese resume prompt builder works
Enter the target role and document type
In the first box, name the role you are applying for (e.g. "internet product manager"), then choose the document type — resume bullet points, a cover letter, a self-introduction or an interview self-introduction. These two fields set the direction so the model knows from the start who and what it is writing for.
Fill in background, core skills and results
Next, give your years of experience and background, your core skills, and — most important — your key results. Quantify them ("led a team of 5 and lifted conversion 23% in six months"): quantified results are what separate a forgettable resume from a strong one, and they are exactly the raw material the model needs.
Set tone and length
Specify the tone ("professional and steady" or "sincere and warm") and a length limit ("keep the cover letter under 300 字"). This keeps the generated text on-brand for your industry without rambling, so you can use it almost as-is or make light edits.
Copy the prompt into a model
Click Copy and paste the assembled prompt into DeepSeek, Qwen, Doubao, Kimi, ERNIE or Zhipu, and the model will write or polish your text. Everything is assembled locally in your browser — and please do not put sensitive personal data such as ID numbers or home addresses into a third-party model.
How the Chinese resume prompt builder works
A great resume starts with a structured brief, not a clever phrase
When you ask a Chinese large language model — DeepSeek, Qwen (通义千问), Doubao, Kimi, ERNIE or Zhipu — to write your resume, cover letter or self-introduction, the quality of what comes back depends far more on the brief you give it than on any magic wording. A model cannot know which of your experiences matter, which numbers prove your impact, or what tone the role expects unless you tell it. This builder turns that brief into a clean, structured prompt: you fill in the target role, your years of experience and background, your core skills, your key results, the document type you need, the tone, and a length limit — and it assembles them into a prompt the model can act on immediately. The result is the kind of request a careful career coach would phrase for you, only built in seconds and entirely in your browser.
The single most important field is your results, and the rule is simple: quantify everything. "Responsible for marketing" tells a recruiter nothing; "ran a 6-person team and grew monthly active users from 20,000 to 80,000 in six months" tells them exactly what you can do. Numbers are the raw material a model needs to write a resume that stands out, so spend your effort there. The target role matters almost as much: naming it lets the model select the experience most relevant to that job and phrase your skills in the employer's language, instead of dumping your entire history onto the page. Match your core skills to what the job ad asks for, and your draft clears the first screen far more often.
"A weak AI-written resume is usually a weak brief — not a weak model. Give it your target role and your quantified results, and the same model writes something a recruiter actually notices."
Quantified results and the right document type do the heavy lifting
Choosing the right document type changes everything, which is why this tool keeps it as its own field. A resume leads with quantified results; a cover letter argues why you, specifically, fit this role and this company; a written self-introduction lands your three best highlights fast; and an interview self-introduction should sound spoken — conversational, rhythmic, about a minute long. Tell the model which one you need and set the tone — "professional and steady" for a finance role, "sincere and warm" for a startup — and the wording adjusts accordingly. A length limit keeps the output tight enough to use almost as-is, instead of a wall of text you have to trim by hand.
Two cautions make the difference between a helpful draft and a risky one. First, privacy: this builder runs entirely in your browser and stores nothing, but the moment you paste the prompt into a third-party model you are sharing that text with their service — so keep ID numbers, home addresses, phone numbers and bank details out of it. The role, your skills and your results are all the model needs. Second, accuracy: treat the output as a strong draft, never a finished document. The model organises language well, but you must verify every figure, company name and date, and you must never let it exaggerate or invent experience you do not have. Run the prompt, read the draft critically, tighten one field, and copy again — two or three rounds usually turn a generic reply into a resume that genuinely sounds like you, and a clean, reusable prompt you can keep.
About Chinese Resume & Job-Application Prompts — 10 Key Points
The core of a good resume is quantified results: numbers showing what you achieved are far more persuasive than a list of "responsible for…" duties.
Give the model a clear target role before it writes, so it can pick the experience most relevant to that role instead of reciting your entire history.
Cover letters, self-introductions and resumes are written differently — a cover letter argues "why me", a self-introduction lands the highlights in 30 seconds; this tool lets you build a prompt for each.
An interview self-introduction should be conversational and rhythmic, around one minute; tell the model it is "for a spoken interview" and the phrasing comes out more natural.
Aligning your core skills with the job ad (if the role wants SQL, foreground your data analysis) markedly improves the odds of clearing the first screen.
Chinese resumes value restraint and concision over vague adjectives; asking the model to "use more verbs and numbers, fewer adjectives" usually reads better.
You can have the model rewrite a single experience in STAR form (Situation–Task–Action–Result) for clearer logic that matches how interviewers read.
This tool only builds the prompt; it does not call a model — you copy the prompt into DeepSeek, Qwen or another LLM yourself.
Privacy reminder: when drafting a resume, do not feed ID numbers, home addresses or bank card numbers into a third-party model — the role, skills and results are enough.
All assembly happens locally in your browser; your input is never uploaded, never stored, and no model is ever called.
Frequently Asked Questions
- Not directly — it builds a high-quality "write my resume" prompt for you. Fill in your target role, background, core skills and key results, and the tool assembles a structured prompt. Copy that into DeepSeek, Qwen, Doubao or another model, and the model will write or polish your resume, cover letter or self-introduction.
- Via the document-type field you can build a prompt for resume bullet points, a cover letter, a self-introduction or an interview self-introduction. Each emphasises something different — resumes stress results, cover letters stress motivation, self-introductions stress highlights — so choosing the right type keeps the output on point.
- DeepSeek, Qwen (通义千问), Doubao, Kimi, ERNIE and Zhipu all work, as do ChatGPT, Claude and Gemini. Because the output is structured plain text, it is vendor-neutral — paste it into the chat box or the system prompt.
- Because a duty like "responsible for operations" says nothing about your level, while a result like "grew monthly actives from 20k to 80k in six months" lets a recruiter see your value at a glance. Phrase results as sentences with numbers and the model expands them into a far more professional resume.
- No. All assembly happens locally in your browser with plain JavaScript; nothing you type is sent to a server or third party, and nothing is stored. But when you copy the generated prompt into a third-party model, follow the privacy advice in the next answer.
- Career details like role, skills and results are usually fine — but do not put sensitive personal data such as ID numbers, home address, phone number or bank card numbers into a third-party model. This tool deliberately does not ask for any of that; it is not needed to write a good resume.
- No. Empty fields are omitted automatically. A target role and key results alone give you a usable prompt; adding skills, tone and length makes the model output fit your needs more closely.
- Treat it as a strong first draft. The model is good at organising language and structure, but you must check the specific figures, company names and facts yourself before applying — and never let it exaggerate or invent any experience.
- The structure is the same: target role, background, skills, quantified results, tone and length. The difference is writing in the matching language and its conventions — a Chinese resume written in Chinese reads more naturally and fits how local recruiters scan a CV.
- Completely free, with no account or sign-up and no usage limit. It runs in your browser and collects no data.
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