--- name: llm-intern-skill description: Use when polishing, diagnosing, tailoring, or exporting resumes for LLM, RAG, Agent, Agentic RL, post-training, pretraining, AIGC, search/ranking, multimodal, AI backend, or LLM algorithm internships from raw resume text, a materials folder, and/or a target job description. Audits evidence, maps JD fit, enforces truth boundaries, writes polished and targeted resumes, generates interviewer-style grilling questions, answer cards, evidence-upgrade plans, and optional open-source project recommendations without fabricating experience. --- # LLMInternSkill Use this Skill when the user wants resume polish, resume diagnosis, JD tailoring, project packaging, interview preparation, or final resume export for LLM-related internship applications. Core rule: ```text Do not fabricate. Diagnose first, polish second. ``` ## Inputs Preferred input folder: ```text materials/ ├── target_jd.txt ├── resume.md / resume.pdf ├── projects/ ├── code/ ├── notes/ ├── papers/ ├── awards/ └── other/ ``` If the user only provides a JD and no materials, ask the intake questions from `templates/intake.md`. If the user only asks for resume polish, run a lightweight version: ```text raw resume line -> claim extraction -> evidence/risk check -> polished wording -> interview risk ``` ## Main Workflow 1. **Decide the mode** - Resume polish only: use `skill-references/resume-polish.md`. - JD tailoring: use `skill-references/jd-analysis.md` and `skill-references/resume-tailoring.md`. - Full materials folder: run the complete workflow below. - Interview prep only: use `skill-references/interview-grilling.md` and `skill-references/answer-cards.md`. - Project Scout only: use `skill-references/project-scout.md`. 2. **Read the target JD when present** - Use `skill-references/jd-analysis.md`. - Detect role type: RAG, Agent, Agentic RL, post-training, pretraining, LLM app, LLM algorithm, search/ranking, AIGC, multimodal, backend AI, infra, or mixed. - Load the matching role file under `skill-references/roles/` when relevant. 3. **Audit the materials folder when present** - Use `skill-references/materials-audit.md`. - Extract projects, claims, evidence, missing evidence, and unclear ownership. 4. **Set truth boundaries** - Use `skill-references/truth-boundary.md`. - Classify content as `可以写`, `谨慎写`, `补证据后写`, `不能写`, or `无法判断`. 5. **Build the evidence contract** - Use `skill-references/evidence-contract.md`. - Every strong claim needs evidence, risk, safe wording, and interview proof. 6. **Generate polished / targeted resume** - Use `skill-references/resume-polish.md` for line-level polish. - Use `skill-references/resume-tailoring.md`. - Produce conservative, standard, and stronger-after-evidence bullets. - Generate a targeted full resume draft when enough information exists. - If the user wants a PDF-ready resume, use `templates/resume-latex/bill-ryan-elegant-zh_CN/resume-zh_CN.tex` as the LaTeX base. 7. **Generate interview grilling** - Use `skill-references/interview-grilling.md`. - Ask interviewer-style questions based on JD gaps and resume claims. 8. **Generate answer cards** - Use `skill-references/answer-cards.md`. - For high-risk questions, produce dangerous / passable / strong answers. 9. **Create upgrade plan** - Use `skill-references/upgrade-plan.md`. - Split into half-day, 1-day, 3-day, and 1-week evidence upgrades. 10. **Optional Project Scout** - Use `skill-references/project-scout.md` when the user's evidence is weak or they ask for projects to learn. - Recommend projects only as learning/reproduction/modification opportunities, not as fake experience. 11. **Assemble final pack** - Use `templates/final-pack.md`. ## Output Files When writing files, prefer this structure: ```text output/ ├── 01_jd_analysis.md ├── 02_materials_audit.md ├── 03_truth_boundary.md ├── 04_evidence_contract.md ├── 05_resume_polish.md ├── 06_targeted_resume.md ├── 07_interview_grilling.md ├── 08_answer_cards.md ├── 09_upgrade_plan.md ├── 10_project_scout.md └── 11_final_pack.md ``` If the user wants only an answer in chat, still follow the same section order. ## Fit Verdict Always give one: ```text strong fit weak fit risky fit not recommended ``` Explain the verdict with: - JD must-haves. - User evidence. - Gaps. - Highest interview risk. - Fastest useful upgrade. ## Non-Negotiables - Never invent internships, production status, metrics, user scale, model training, ranking gains, or ownership. - Do not write "主导" when evidence only supports "参与". - Do not write "上线" when evidence only supports demo, local run, or internal trial. - Do not write open-source learning as work experience unless the user actually reproduced, modified, and documented it. - If materials are insufficient, ask questions or produce a conservative report instead of polished fiction.