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intern-program

Helps your agent record internship program information. It organizes data about interns, supervisors, and learning goals.

What it does

This system helps organize and track information about interns, from the start of their internship to potential hiring.

When to use it

  • ✓To register new interns.
  • ✓To manage intern progress and evaluations.
  • ✓To decide if an intern will be converted to a full-time employee.

Example of what to ask your AI

“I want to set up my internship program from scratch.”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/sickn33/agentic-awesome-skills/blob/main/plugins/agentic-awesome-skills-claude/skills/intern-program/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/sickn33/agentic-awesome-skills/blob/main/plugins/agentic-awesome-skills-claude/skills/intern-program/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

It collects essential data about each intern and the program, like dates, supervisors, and scores. It can then generate reports or templates to help manage the process.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add sickn33/agentic-awesome-skills --skill intern-program

Or download just the file:

curl -L https://raw.githubusercontent.com/sickn33/agentic-awesome-skills/main/plugins/agentic-awesome-skills-claude/skills/intern-program/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

Intern Program

What it is: Interns from start to certificate or full-time offer.

Overview

Works out the smallest useful Intern Program setup for the business in front of it, then builds it only when asked. The default output is a short recommendation, not a spreadsheet. Artifacts - CSV, SQL DDL, JSON Schema, Notion mapping - are produced on request, from one field list so they cannot drift apart.

Layer: Layer 3: Onboard. Fits: Growth stage. Table code: n/a.

When to Use This Skill

  • intern tracker
  • internship management
  • intern program database
  • intern onboarding and conversion

Also use it when the user says "interns from start to certificate or full-time offer", or describes the same process happening in a spreadsheet, a document or someone inboxes.

Do not use it for: payroll calculation, tax filing, or legal advice. This skill produces empty templates only - it never holds or processes real employee or customer data.

How It Works

Follow the shared execution contract. The module-specific rules below define only domain fields, decisions, calculations, and safety constraints.

Step 1 - Identify intent

Read the request and pick the intent before asking anything.

  • "set up" or "build" or "create" -> the user wants artifacts; go to Step 2.
  • "our process is ..." or "it is in a sheet" -> the user wants to move an existing process; capture it, then Step 2.
  • "is this right" or "review" or "audit" -> the user wants a check, not a build; answer from what they share.
  • "how do I ..." -> advice question; answer directly and offer the build only if it helps.

Ask only if this is the highest-value missing fact; otherwise proceed without an opener:

Q: How many interns do you take at a time?

Step 2 - Ask only what is missing

Skip anything the user already answered, in any earlier message. Ask the rest one at a time, and stop as soon as the remaining answers would not change the output.

  • Volume - How many interns? / Any time of year? / Paid or unpaid?
  • Programme - Duration? / Mentor assigned? / Certificate needed?
  • Conversion - Any full-time offers? / Criteria? / Who decides?
  • Current process - How is it tracked now? / Spreadsheet or nothing? / What gets missed?
  • Outcome - What do you need? / Records, progress tracking or conversion?

Never invent an answer. If the user does not know, record it as unknown and carry on.

Step 3 - Hold the internal context

Hold the answers in this shape. It stays internal - it is not shown to the user unless they ask, and it never carries a value the user did not give.

module: intern-program
intent: null            # setup | advice | review | fix | build | convert | export
scale: null             # Starter | Growth | Scale, only if the answer changes it
areas:
  "Volume": null
  "Programme": null
  "Conversion": null
  "Current process": null
  "Outcome": null
requested_outputs: []   # csv | sql | json | notion | xlsx - requested formats only
confirmed_facts: []     # only what the user actually said
open_questions: []      # the unanswered ones, in the order worth asking

Step 4 - Recommend the smallest workflow

If an artifact was requested, build it after resolving essential missing facts. Otherwise give a short recommendation and offer the relevant artifact.

Recommended approach: Treat the intern as a light employee record plus a progress log, and only build conversion tracking if interns actually convert.

Why this one: Most intern programmes need three things: dates, a supervisor, and a mid and final score. Everything else is optional.

Workflow: Offer → Intern record → Mid review → Final review → Certificate or offer

Step 5 - Build only on request

Once the user asks for it, derive the fields from the confirmed context and emit the requested artifacts. For machine-readable text, keep prose outside the data; for files, provide a usable link. Report material validation failures or limitations separately.

A selected Notion output is rendered by notion-manual-import, so route the Notion step there. When the user selects Notion, hand that step to @notion-manual-import: it holds the CSV, the property mapping, the import steps and the verification checklist, and it renders the Field Reference below instead of defining a table of its own. Do not restate the mapping here and do not improvise the import steps. Manual CSV and mapping outputs need no

…

FAQ

What does this system do with intern data?

It organizes and tracks information but does not store real employee or customer data. It creates templates and reports.

Can I use this for payroll or tax calculations?

No, this system is not for financial calculations or legal matters. It focuses solely on managing the internship program.

What kind of information does it collect?

It collects details such as intern name, department, start and end dates, supervisor, mentor, learning goals, and evaluation scores.

Details

Original description by the author

Internship register: intern and department, supervisor and mentor, institution, start and end dates, stipend, learning goals, mid-term and final scores, conversion flags. Use for intern tracking.

repo: sickn33/agentic-awesome-skills

Popularity

GitHub stars
48k
Ranking position
#3343
License
MIT
Updated
10/15/2026

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