BeClaude

llm-intern-skill

New
95GitHub TrendingGeneralby couragec

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.

First seen 6/1/2026

Overview

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.

  1. 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.

  1. Audit the materials folder when present

- Use skill-references/materials-audit.md. - Extract projects, claims, evidence, missing evidence, and unclear ownership.

  1. 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.

  1. Build the evidence contract

- Use skill-references/evidence-contract.md. - Every strong claim needs evidence, risk, safe wording, and interview proof.

  1. 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.

  1. Generate interview grilling

- Use skill-references/interview-grilling.md. - Ask interviewer-style questions based on JD gaps and resume claims.

  1. Generate answer cards

- Use skill-references/answer-cards.md. - For high-risk questions, produce dangerous / passable / strong answers.

  1. Create upgrade plan

- Use skill-references/upgrade-plan.md. - Split into half-day, 1-day, 3-day, and 1-week evidence upgrades.

  1. 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.

  1. 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.

Install & Usage

1
Create the skills directory
mkdir -p .claude/skills
2
Download the skill file
mkdir -p .claude/skills && curl -o .claude/skills/llm-intern-skill.md https://raw.githubusercontent.com/couragec/llm-intern-skill/main/SKILL.md
3
Invoke in Claude Code
/llm-intern-skill
View source on GitHub
agent

Security Audits

LicenseUnknownSourceWarnRepositoryPass

Frequently Asked Questions

What is llm-intern-skill?

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.

How to install llm-intern-skill?

To install llm-intern-skill: create the skills directory (mkdir -p .claude/skills), then run: mkdir -p .claude/skills && curl -o .claude/skills/llm-intern-skill.md https://raw.githubusercontent.com/couragec/llm-intern-skill/main/SKILL.md. Finally, /llm-intern-skill in Claude Code.

What is llm-intern-skill best for?

llm-intern-skill is a skill categorized under General. It is designed for: agent. Created by couragec.