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Galactic Reverse Interview

Community
GuidoPenta
galactic-reverse-interview

Picks the questions to ask interviewers (Galactic reverse-interview guide), then records answers and red flags. Use when the user asks what to ask at an interview or debriefs one.

Overview

PublisherGuidoPenta
Repositorythe-candidates-guide-to-the-galaxy
Skill namegalactic-reverse-interview
Stars
50
Forks
3
Bundled files
1
Links
Skill sourceRepository
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by GuidoPenta on GitHub. Read the source before you install it.

Installation

Install the Galactic Reverse Interview AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/GuidoPenta/the-candidates-guide-to-the-galaxy/tree/main/.claude/skills/galactic-reverse-interview
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/GuidoPenta/the-candidates-guide-to-the-galaxy.git /tmp/the-candidates-guide-to-the-galaxy
mkdir -p .claude/skills
cp -r /tmp/the-candidates-guide-to-the-galaxy/.claude/skills/galactic-reverse-interview .claude/skills/galactic-reverse-interview
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Galactic Reverse Interview in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Galactic Reverse Interview on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Galactic Reverse Interview is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Galactic Reverse Interview

Knowledge: references/reverse-interview-guide.md, the question bank and advice from galactic-reverse-interview-guide-for-developers. Workspace layout: .claude/skills/galactic-job-search/references/workspace.md.

Before the interview → workspace/applications/<app>/questions.md

  1. Read profile.md (must-haves, deal-breakers), company.md (what's already known) and fit.md.
  2. Ask who the interviewer is (role) and how much time there will be for questions, if unknown.
  3. Pick 3–5 questions per round, plus 1–2 spares, from the bank (a [pack] rule in the reference; the guide only says don't ask them all). Prioritise the user's must-haves and deal-breakers (they must be answered before any offer), then what the research couldn't answer, then questions this interviewer type is best placed to answer. Prefer questions the company's site doesn't already answer (the guide: much can be found online).
  4. Adapt the wording to this company, for example by referencing something specific from company.md. Keep the core of each question from the guide, and cite its category.
  5. Order them: must-ask first, in case time runs out. For each, note what a good answer and a red flag would look like. This part is the skill pack's guidance (see the reference), not Guido's text, so don't attribute it to him.
  6. Agency or external recruiter (e.g. a Welyk recruiter screening for a client): they answer second-hand. Prefer questions about the process (next steps, who's in the technical round and what it covers, timing, salary range confirmed by the client) and the client's must-haves. Save culture and team questions for the company's own interviewers. The process questions are general practice; label them as such.

After the interview

Ask the user what they heard for each question and record it in questions.md. Flag worrying answers using the reference's §4.2 ([pack] guidance, plus the negotiation guide's warnings on "senza orari" and fake P.IVA), and questions left unanswered, to ask in the next round. Log a summary line with galactic-tracker.

Comparing companies

When the user has several processes open, build a side-by-side table from all the questions.md files: must-haves met / unmet / unknown per company. This feeds straight into galactic-negotiation when offers arrive.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Galactic Reverse Interview AI skill do?

Picks the questions to ask interviewers (Galactic reverse-interview guide), then records answers and red flags. Use when the user asks what to ask at an interview or debriefs one.

Why use Galactic Reverse Interview on TypingMind?

Because you install it once and use it with any model. Galactic Reverse Interview is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Galactic Reverse Interview in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/GuidoPenta/the-candidates-guide-to-the-galaxy/tree/main/.claude/skills/galactic-reverse-interview. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Galactic Reverse Interview?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Galactic Reverse Interview?

As many as you like. As long as a model supports skills, you can use Galactic Reverse Interview with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Galactic Reverse Interview AI skill free?

It is published on GitHub by GuidoPenta. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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