Skill: funkeyyou/interview-question-gen (version 1.0.0)

--- name: interview-question-gen description: Generate a structured Feishu interview question document from a candidate's resume, then append a comprehensive evaluation after receiving the interview transcript. Use when: (1) given a resume/CV and asked to prepare interview questions, (2) given an interview transcript/recording and asked to write an evaluation or assessment, (3) asked to do both steps end-to-end. Triggers on phrases like "出面试题", "面试题集", "面试评价", "interview questions", "interview evaluation", "根据简历出题", "写面试评价". --- # Interview Question Generator & Evaluator Two-phase workflow for WePlay activity operations (活动运营) interviews using Feishu docs. ## Phase 1: Resume → Interview Question Document ### Step 1: Read the Resume If the resume is a PDF attachment, render each page as an image (`/tmp/resume_p{n}.png`) using PyMuPDF and read them visually: ```python import fitz doc = fitz.open("/path/to/resume.pdf") for i, page in enumerate(doc): page.get_pixmap(matrix=fitz.Matrix(1.5, 1.5)).save(f"/tmp/resume_p{i+1}.png") ``` Extract key info: work experience, skills, education, highlights. ### Step 2: Read WePlay Product Context Before generating questions, fetch the WePlay product framework doc to understand product positioning: - WePlay产品框架：https://wepie.feishu.cn/wiki/Q62TwQ3Fsi5Q8kkc0iDcINsSnno ### Step 3: Generate Interview Questions Structure the document into these sections. See `references/question-template.md` for the full question template and scoring rubrics. **Document sections:** 1. 破冰与自我介绍 (2 questions) 2. 结合简历的深挖问题 (4–6 questions, grouped by employer) 3. 活动运营能力考察 (4 questions: scenario planning, data, cross-team collaboration) 4. 日语与本地化能力 (3 questions, tailored to Japanese market) 5. WePlay 产品体验问题 (5 questions — require candidate to pre-download WePlay) 6. 价值观与潜力考察 (4 questions including open Q&A) 7. 日本語口頭試問 (6 questions, all in Japanese — no Chinese) Tailor questions to the specific candidate's background. Reference their actual projects, metrics, and employers by name. ### Step 4: Create Feishu Document Use `feishu_bot_doc.mjs` to create the document: ```bash cat /tmp/interview_questions.md | node scripts/feishu_bot_doc.mjs create \ --title "【AI生成】{候选人姓名} {岗位} 面试题集" \ --stdin \ --folder AZ3nfFtial4bHTdOFahcdcfxnub \ --collaborator ou_8b357150cff930fca19a733461a32526 ``` Reply with the document URL. Tell the user to send the interview transcript when ready. --- ## Phase 2: Interview Transcript → Evaluation ### Step 1: Read the Transcript Accept the transcript as: - A Feishu doc link → use `feishu_doc` read action - A pasted text block → read directly ### Step 2: Write Evaluation Append the evaluation to the **existing interview question document** (not a new doc). Use `feishu_doc` append action on the same `doc_token`. See `references/evaluation-template.md` for the full evaluation structure and scoring rubrics. **Evaluation structure:** 1. 总体印象 (1–2 sentences, overall rating: 优秀/良好/中等/中等偏下/不建议录用) 2. 各维度评价 with ⭐ ratings (1–5 stars each): - 过往经验匹配度 - 活动策划思维 - 数据分析能力 - 产品认知与洞察 - 日本市场理解 - 表达与沟通 3. 亮点 (bullet list) 4. 主要风险 (bullet list) 5. 结论 (录用 / 待定 / 不建议录用, with reasoning) Be specific: quote actual interview moments, not generic observations. --- ## Notes - Japanese oral exam questions (Section 7) must be written entirely in Japanese — no Chinese text. - Always add `【AI生成】` prefix to document titles. - Default save folder: `AZ3nfFtial4bHTdOFahcdcfxnub` - Default collaborator: [REDACTED_SECRET] (吴柏庆) - If the interview transcript doc is auto-generated by Feishu (智能纪要), the bot has no write permission — append to the question doc instead.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)