LLMInternSkill: LLM internship resume and job-search Codex Skill for resume polish, JD tailoring, evidence guard, interview

by couragec · Codex Skill · ★ 173

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install LLMInternSkill

git clone https://github.com/couragec/llm-intern-skill.git ~/.codex/skills/llm-intern-skill

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 66/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agentai-careeraigcchinesecodex-skillinterview-prepjd-tailoringjob-searchlatex-resumellm

Quick Facts

Stars173
Forks5
LanguageMarkdown
CategoryCodex Skill
LicenseMIT
Quality Score66/100
Last Updated2026-06-04
Created2026-06-01
Platformscodex
Est. Tokens~96k

About LLMInternSkill

LLMInternSkill / LLM Intern Skill 大模型实习简历与求职工具箱：LLM internship resume polish, JD tailoring, RAG / Agent / Post-training 项目包装、面试拷打、开源项目补强。 一个面向大模型实习、AI 求职和 Codex Skill 工作流的 evidence-bound resume toolkit：不只是把简历写好听，而是让每一行都能扛住面试追问。 Keywords: LLM internship resume, 大模型实习简历, Codex Skill, resume polish, JD tailoring, interview prep, RAG, Agent, post-training, pretraining, search ranking, AIGC,...

Compatible Skills

These tools work well together with LLMInternSkill for enhanced workflows:

  • get-job.skill — semantic(0.64)+complementary+rare_topics+similar_pop (61%)
  • boss-agent-cli — semantic(0.36)+complementary+rare_topics+similar_pop (57%)
  • ResumeSkills — semantic(0.52)+complementary+similar_pop (53%)
  • jobpilot — semantic(0.39)+complementary+rare_topics+similar_pop (53%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

View on GitHub → Browse Codex Skill tools