Agent skill

Internship-to-Resume Toolkit

by Sunanzhe2004 in Sunanzhe2004/shushu-internship-resume-optimizer

Turns internship code repos, project summaries and business documents into resume-ready bullets, JD-matched rankings, and interview-ready STAR material.

Custom licenceAuto-check passedBusiness, Finance & HR

Install Internship-to-Resume Toolkit

skills CLI
$ npx skills add Sunanzhe2004/shushu-internship-resume-optimizer --skill shushu-internship-tool -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Sunanzhe2004/shushu-internship-resume-optimizer shushu-internship-tool --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Sunanzhe2004/shushu-internship-resume-optimizer.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/shushu-internship-tool .claude/skills/shushu-internship-tool && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
shushu-internship-tool
GitHub stars
123
Token cost
~1.6k tokens
SKILL.md length
745 words
Files
24 (incl. scripts, references)
Skills in repo
1
Repo updated
First seen
Licence
Custom licence

At a glance

Turns internship code repos, project summaries and business documents into resume-ready bullets, JD-matched rankings, and interview-ready STAR material.

  • Works in 5 steps: Gather Inputs → Normalize Into sources.json → Achievement Audit → …
  • Turning internship code and documents into resume bullets
  • SKILL.md covers Goal, Core Principle, Preferred Workflow and Model-First Extraction Guidance, plus 2 more sections
  • Runs Python scripts from its folder; calls python

What it does

This skill turns messy internship materials - code repositories, project summaries, business documents, PRs, notes and retrospectives - into resume-ready achievements, JD-oriented bullet points, evidence-backed project summaries, and interview-ready STAR and Q&A material. It favors model understanding for the judgment-heavy parts, like grouping projects, extracting contributions, and judging value, and reserves scripts for the stable mechanical parts: loading files, normalizing them, validating schemas, deduplicating, ranking and formatting output.

The preferred workflow gathers the target job description, role direction, current internship scope, available materials and any confidentiality constraints, normalizes everything into a sources file, then runs an achievement-audit script that checks whether project blocks are split correctly, whether each achievement has real business context, and whether wording sounds AI-generated or lacks evidence. A resume-ranking script then scores which achievements are worth keeping for the target role, whether bullets should merge or stay separate, and orders them along a causal flow of setup, mechanism and result.

It explicitly avoids growing a fixed keyword-to-title lookup as its main extraction strategy, treating any fixture materials as regression checks rather than the source of its domain rules, and any added rule is meant to express a broad pattern - such as structure, causality or evidence quality - rather than a one-off mapping.

When your agent uses it

  • Turning internship code and documents into resume bullets
  • Ranking which achievements fit a target job description
  • Preparing STAR-format interview answers from real project work

Example prompts

  • “Turn my internship repo and project summary into resume bullets.”
  • “Rank my achievements against this backend job description.”
  • “Build interview-ready STAR answers from my internship retrospective.”

Requirements

  • Python

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Gather Inputs
  2. Normalize Into sources.json
  3. Achievement Audit
  4. Resume Ranking
  5. Interview Pack

What it can do on your machine

Read from SKILL.md and the folder at commit eaf11d5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 9 files in scripts/ (Python, from the files we listed), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Internship-to-Resume Toolkit loads about 1.6k tokens when it runs, and up to ~6.3k if it reads all its reference files. Until then it costs about 49 tokens; SKILL.md has 745 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~49
When it runs · the whole SKILL.md, loaded when a task matches
~1.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~6.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 745 words (~1,579 tokens).

“Default output is Chinese, while preserving English technical terms, commands, and repository names.”

— opening of SKILL.md by Sunanzhe2004, Custom licence
name
shushu-internship-tool

Read the full SKILL.md on GitHub

Files

SKILL.md and 23 other files (scripts, references) in skills/shushu-internship-tool of Sunanzhe2004/shushu-internship-resume-optimizer.

  • SKILL.md
  • agents/openai.yaml
  • references/internship-project-resume-template.md
  • references/interview-pack-template.md
  • references/model-first-extraction.md
  • references/modification-playbook.md
  • references/remote-compute-checklist.md
  • references/repo-selection-rubric.md
  • scripts/achievement_audit.py
  • scripts/candidate_score.py
  • scripts/doc_knowledge.py
  • scripts/interview_pack.py
  • scripts/repo_audit.py
  • scripts/resume_rank.py
  • scripts/shushu_internship_tool/__init__.py
  • scripts/shushu_internship_tool/achievement_audit.py
  • scripts/shushu_internship_tool/candidate_score.py
  • … and 7 more

Open the folder on GitHubat commit eaf11d5

Compare with similar skills

Internship-to-Resume Toolkit next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Internship-to-Resume Toolkit compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Internship-to-Resume Toolkit this skillSunanzhe2004/shushu-internship-resume-optimizer123—~1.6kAutomated safety check: PassCustom licence
Career-Ops Job Search Centercareer-ops-hq/career-ops74k—~3.6kAutomated safety check: PassMIT
Internship Project Preparation ToolLiuMengxuan04/shushu-internship-tool2.1k—~2.3kAutomated safety check: PassCustom licence
Job Application AssistantMadsLorentzen/ai-job-search45k—~1.2kAutomated safety check: NotesMIT
Backend and Agent Project Selectorlishuangqiang/backend-agent-resume-scout349—~1.4kAutomated safety check: PassApache-2.0
LLM Intern Skillwanyichen06/LLMInternSkill325—~1.2kAutomated safety check: PassMIT

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Works with

Questions about Internship-to-Resume Toolkit

What does Internship-to-Resume Toolkit do?

Turns internship code repos, project summaries and business documents into resume-ready bullets, JD-matched rankings, and interview-ready STAR material. This skill turns messy internship materials - code repositories, project summaries, business documents, PRs, notes and retrospectives - into resume-ready achievements, JD-oriented bullet points, evidence-backed project summaries, and interview-ready STAR and Q&A material. It favors model understanding for the judgment-heavy parts, like grouping projects, extracting contributions, and judging value, and reserves scripts for the stable mechanical parts: loading files, normalizing them, validating schemas, deduplicating, ranking and formatting output.

When should I use Internship-to-Resume Toolkit?

Internship-to-Resume Toolkit fits situations like: turning internship code and documents into resume bullets; ranking which achievements fit a target job description; preparing STAR-format interview answers from real project work.

How do I install Internship-to-Resume Toolkit in Claude Code?

Run `npx skills add Sunanzhe2004/shushu-internship-resume-optimizer --skill shushu-internship-tool -a claude-code`. Or copy the skill folder (skills/shushu-internship-tool in Sunanzhe2004/shushu-internship-resume-optimizer) into .claude/skills/shushu-internship-tool in your project. Claude Code loads it when a task matches its description.

How do I install Internship-to-Resume Toolkit in Codex?

Run `npx skills add Sunanzhe2004/shushu-internship-resume-optimizer --skill shushu-internship-tool -a codex`. Or copy the skill folder (skills/shushu-internship-tool in Sunanzhe2004/shushu-internship-resume-optimizer) into .agents/skills/shushu-internship-tool in your project. Codex loads it when a task matches its description.

Can I use Internship-to-Resume Toolkit in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Sunanzhe2004/shushu-internship-resume-optimizer --skill shushu-internship-tool -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/shushu-internship-tool, .gemini/skills/shushu-internship-tool, .github/skills/shushu-internship-tool and .opencode/skills/shushu-internship-tool in your project.

What does Internship-to-Resume Toolkit need to run?

Going by SKILL.md and its folder, Internship-to-Resume Toolkit needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python.

Does Internship-to-Resume Toolkit access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Internship-to-Resume Toolkit safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Internship-to-Resume Toolkit use?

Internship-to-Resume Toolkit has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.

How many tokens does Internship-to-Resume Toolkit use?

About 1.6k tokens (SKILL.md is roughly 6.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 4.7k tokens, read only when the agent opens those files.

What are the alternatives to Internship-to-Resume Toolkit?

Skills that share tags, products or a category with Internship-to-Resume Toolkit: Career-Ops Job Search Center (career-ops-hq/career-ops, 74k stars), Internship Project Preparation Tool (LiuMengxuan04/shushu-internship-tool, 2.1k stars), Job Application Assistant (MadsLorentzen/ai-job-search, 45k stars) and Backend and Agent Project Selector (lishuangqiang/backend-agent-resume-scout, 349 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Internship-to-Resume Toolkit?

Sunanzhe2004 (a GitHub user) maintains it in Sunanzhe2004/shushu-internship-resume-optimizer, which has 123 GitHub stars. The repository was last updated on July 14, 2026.

Source: Sunanzhe2004/shushu-internship-resume-optimizer on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.