LLMInternSkill is an evidence-bound toolkit for LLM internship and AI job seekers. It polishes resumes, tailors them to job descriptions, prepares users for rigorous interviews, and scouts projects to build missing experience, ensuring claims are verifiable.

How It Works

This toolkit moves beyond superficial resume polishing by enforcing an "evidence-bound" approach. It analyzes provided materials (code, logs, papers) to validate resume claims, downgrades unsupported statements, and generates interview-ready responses. Its core differentiator is ensuring every resume line withstands technical scrutiny, recommending specific open-source projects to build necessary evidence when gaps exist.

Quick Start & Requirements

• Installation: Use directly via prompts or install as a Codex Skill: mkdir -p ~/.codex/skills && git clone https://github.com/couragec/llm-intern-skill.git ~/.codex/skills/llm-intern-skill.
• Usage: Process raw resumes/JDs with provided materials or invoke the skill within Codex.
• Prerequisites: Requires user-provided materials (resume, JD, project files, code, notes). Underlying LLM execution may require appropriate hardware.
• Links: README serves as primary documentation.

Highlighted Details

• Evidence Guard: Audits claims against source materials, establishing truth boundaries and downgrading unsubstantiated statements.
• Interview Drill: Generates detailed interview questions, potential answers, and follow-up chains based on resume content.
• Project Scout: Recommends open-source projects for skill development, outlining minimum run paths and evidence collection strategies.
• JD Tailoring: Assesses job description fit, reorders experiences, and generates a customized resume draft.
• LaTeX Export: Produces PDF-ready resume drafts using a Chinese version of the Bill Ryan elegant LaTeX template.

Maintenance & Community

Welcomes contributions via issues/PRs for expanding JD examples and role references. No specific community channels or contributor details are listed.

Licensing & Compatibility

Licensed under MIT. The bundled LaTeX resume template retains its original upstream license and attribution. Generally permissive for commercial use.

Limitations & Caveats

Strictly prohibits fabricating experience; learning from open-source projects requires genuine replication, understanding, and evidence collection before presentation. Effectiveness hinges on input material quality. Project is in "final MVP" status.