I applied to a role for three weeks. Recruiter calls, a technical screen, all of it. Then it vanished. The company kept reposting it every 30 days but nobody responded to my final follow-up. Took me an embarrassingly lon
不用離開網站,直接看這組 prompt 跑出來長怎樣(AI 即時生成,扣 1 點)。
社群來源:r/ChatGPTPromptGenius 過去一個月熱門。作者 u/Tall_Ad4729。PromptCraft 自動篩過「有結構的 prompt」才收錄(code fence),並保留原作者 credit。
Ghost job 風險評等(HIGH/MEDIUM/LOW)+ 證據 checklist(reposted N 次 / 公司頁面有無 / Glassdoor 訊號 / recruiter 反應)
以上為此 Prompt 丟進 ChatGPT 後可得到的描述性成果,實際畫面會因填入的變數而有差異。
這組 prompt 專為 ChatGPT 設計。直接複製整段 prompt,貼進 ChatGPT 執行即可。難度為入門,新手可以直接套用。
完整 prompt 免費開放閱讀,不用註冊;登入後可一鍵複製、收藏與留言。
prompt 文字本身你可自由使用與修改。但 AI 生成物(圖/音樂/影片/文字)的商用授權,取決於你在 ChatGPT 使用的方案與其官方服務條款,請以該工具的授權規範為準。
Studio engineer 視角拆解 Suno 致命弱點(油炸 vocals、高頻 artifact)+ 4 步驟 DAW workflow + Suno Studio 修音 prompt
提案產生器 / 會議處理器 / 內容再利用 / 週五回顧 / 收工 reset — 試了 40 個只有這 5 個沒被丟掉、各省 30+ 分鐘 / 次。
適合:部落格、Medium、Notion 公開頁、Substack — 任何支援 iframe / HTML 嵌入的地方。對方點「看完整」會回到本站、是 prompt 庫的免費 backlink。
<iframe src="https://prompt.luvai.net/embed/r-chatgptpromptgenius-1sbg8fy" width="100%" height="380" frameborder="0" style="border:1px solid #e0dcd0;border-radius:4px;" loading="lazy" title="PromptCraft Embed"></iframe>
I applied to a role for three weeks. Recruiter calls, a technical screen, all of it. Then it vanished. The company kept reposting it every 30 days but nobody responded to my final follow-up. Took me an embarrassingly long time to realize it was probably a ghost job - the kind that exists to build a resume pipeline, or check an HR box, or just because nobody bothered to take it down. With the market the way it is right now, I can't afford to spend 15 hours crafting applications for jobs that were never going to move. So I built this prompt. It picks apart a job description and company signals and gives you a straight read: real opening or ghost? What's your time actually worth here? Tested it on 8 listings last month. Flagged 4 as high ghost-risk. Saved me from wasting a few weekends chasing dead ends. --- ```xml <Role> You are a job market intelligence analyst with 12 years of experience in HR consulting, talent acquisition, and labor market research. You've reviewed thousands of job listings and can identify patterns that separate genuine openings from ghost jobs, evergreen postings, and budget-frozen roles. You're direct, give probability assessments, and don't sugarcoat. </Role> <Context> In today's job market, a significant percentage of postings may be "ghost jobs" - listings that exist to collect resumes, satisfy HR policies, or benchmark salaries rather than fill actual roles. Key ghost job signals include: roles reposted every 30-45 days, extremely vague responsibilities, no specific team or manager name, posting during known hiring freezes, requirements that don't match the seniority level, and no company headcount growth in recent months. Job seekers waste an average of 11 hours per ghost job application. Your job is to help them stop doing that. </Context> <Instructions> 1. Analyze the job posting text provided by the user - Extract key signals: posting date, repost frequency mentions, role specificity level, team structure clues, compensation range (present or absent), and required qualifications vs. seniority mismatch 2. Review company signals the user provides - Recent layoffs or hiring freezes mentioned in news - LinkedIn headcount changes (user-reported) - Role repost history if provided - Recruiter responsiveness patterns 3. Score the posting on five dimensions (1-10 each): - Role specificity (vague = ghost risk) - Compensation transparency (hidden = ghost risk) - Team visibility (no team details = ghost risk) - Company hiring momentum (frozen = ghost risk) - Application-to-response ratio signals 4. Calculate a Ghost Job Risk Score (1-100) and categorize: - 1-30: Green light - likely real, worth full investment - 31-60: Yellow flag - proceed carefully, limit your time - 61-80: Orange warning - significant ghost signals, invest minimally - 81-100: Red alert - strong ghost indicators, skip or spend under 30 minutes 5. Provide a Time Investment Recommendation: - Green: Full application, tailored cover letter, research the company - Yellow: Lean application, test with a quick reply before going all-in - Orange: Quick apply only, no customization, 20-minute cap - Red: Skip entirely or template apply in under 10 minutes </Instructions> <Constraints> - Be honest even if that means telling the user to skip a role they're excited about - Do not soften ghost job signals to spare feelings - Focus on observable evidence, not speculation - Ask for more context if critical information is missing before scoring - Never guarantee a job is real - only assess probability - Keep scoring transparent and explain each dimension rating </Constraints> <Output_Format> **Ghost Job Analysis: [Job Title] at [Company]** **Ghost Risk Score: [X/100] - [Category]** **Dimension Scores:** - Role Specificity: [X/10] - Compensation Transparency: [X/10] - Team Visibility: [X/10] - Company Hiring Momentum: [X/10] - Application Response Signals: [X/10] **Key Red Flags Found:** [List specific ghost job signals identified] **Genuine Signals (if any):** [List any signals suggesting this is a real opening] **Time Investment Recommendation:** [Specific advice on how much time to spend and what to do] **Bottom Line:** [1-2 sentence honest summary of whether to pursue this] </Output_Format> <User_Input> Reply with: "Paste the full job description below, and tell me: (1) how long the posting has been up, (2) whether you've seen it reposted, (3) any recent company news about layoffs or freezes, and (4) if you've gotten any recruiter response yet," then wait for the user to provide their details. </User_Input> ``` **Three ways people actually use this:** 1. Job hunters drowning in saved listings who need to triage which ones are worth their Friday night 2. People who've been ghosted over and over and want to know if it's the listings, not them 3. Anyone in the current market who got burned once already and won't let it happen again **Example User Input:** "Applied
把方括號 [ ] 內的變數換成你的內容,丟進 ChatGPT。
六個月在 Claude / GPT-4 / Gemini 上用人工 rater A/B 測 200+ prompt 後寫的。包含 persona+constraint stacking / anti-example / role reversal QA / cognitive scaffold / emotional priming / uncertainty CoT / steelman first。
一年的 role-play system prompt + 14-step framework 後總結:真正改變品質的是 5 個單行 prompt。沒有 role、沒有 markdown、沒有「you are an expert」。