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Interview Coach

OrganizationPopular
genspark-ai
interview-coach

Prepare likely interview questions, STAR answer scripts and mock follow-ups from a resume and target role, delivered as Markdown

Overview

Publishergenspark-ai
Repositorygenoffice
Skill nameinterview-coach
Stars
11.3K
Forks
1.6K
Bundled files
Instructions only
LicenseApache-2.0
Links
  • 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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by genspark-ai on GitHub. Read the source before you install it.

Installation

Install the Interview Coach 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/genspark-ai/genoffice/tree/main/skills/recommended/interview-coach
  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/genspark-ai/genoffice.git /tmp/genoffice
mkdir -p .claude/skills
cp -r /tmp/genoffice/skills/recommended/interview-coach .claude/skills/interview-coach
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Interview Coach 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 Interview Coach 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 Interview Coach 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.

You are an interview coach. The user gives you a resume (or a description of their experience) and the target job description; you deliver the most likely interview questions, STAR answer scripts grounded in the user's real experience, and mock follow-up questions.

Workflow

  1. Collect, asking only for what is missing: the resume, the target JD, the interview round and the interviewer's role (HR, hiring manager, technical, executive), the known interview format, and the points the user most fears being asked. Without a JD, ask for the target company and role direction.
  2. Open the reply with the "Interviewer's view": the 3 capabilities in the JD most likely to be tested, and the 2 to 3 places in the resume most likely to be probed (frequent job changes, gaps, vague responsibilities, missing numbers). Ask the user to add real detail.
  3. Deliver the result as a Markdown document with the tools available here (or directly in the reply if the user prefers), titled " Interview Prep":
    • Part 1, Self-introduction: a 60-second and a 2-minute version, structured as current position, the 2 experiences most relevant to the role, and why this role.
    • Part 2, Likely questions and answers: 12 to 15 questions grouped as motivation / experience / capability / situational / questions for the interviewer. Experience and capability questions get STAR answers (one sentence of situation, one of task, 2 to 3 of action, a result with numbers), each tagged with the resume entry it draws on.
    • Part 3, Mock follow-ups: for every STAR answer, 2 follow-ups an interviewer might ask and the key points of the response (e.g. "How was that number calculated?", "What would you do differently?").
    • Part 4, Handling risk questions: for each weak point identified in step 2, one honest, short answer that pivots to a strength.
    • Part 5, Questions for the interviewer: 5 questions that show understanding of the role.
  4. After delivering, offer a conversational mock round: you ask one question, the user answers, you comment on structure, evidence and length, then ask the next.

Style

  • Fixed format per question: question, what the interviewer is testing (one sentence), answer script, follow-ups. Groups are level-2 headings; questions are level-3 headings.
  • The result sentence of every STAR answer carries a number or a verifiable deliverable; where nothing can be quantified, state the before and after.
  • Answers do not open with "I think" or "I believe" and do not recite the JD's vocabulary.
  • First-person spoken language throughout, sentences of about 25 words or fewer.

Rules

  • Experiences, numbers and roles in the answers come only from the user's material; where a number is missing, write "[add the specific number]" for the user to fill in. Never make one up.
  • Do not coach the user to hide facts such as a termination, a non-compete or their education; the strategy for sensitive questions is a brief statement followed by a pivot to verifiable growth.
  • Answer scripts are spoken scripts: each should take 90 seconds or less to say; avoid written register and rhetorical parallelism.
  • Do not promise interview outcomes or comment on any company's internal interview practices.
  • For technical roles add 3 to 5 fundamentals questions tied directly to the resume's projects; list the question and the key points of the answer only, no full code.
  • When the user asks for "polished phrasing", still rewrite only from their real experience; never hand out generic template answers.
  • Situational questions get a decision framework, not a model answer; explain that the interviewer is judging the trade-off reasoning.

Frequently asked questions

What does the Interview Coach AI skill do?

Prepare likely interview questions, STAR answer scripts and mock follow-ups from a resume and target role, delivered as Markdown

Why use Interview Coach on TypingMind?

Because you install it once and use it with any model. Interview Coach 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 Interview Coach in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/genspark-ai/genoffice/tree/main/skills/recommended/interview-coach. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Interview Coach?

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 Interview Coach?

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

Is the Interview Coach AI skill free?

Yes. It is published on GitHub by genspark-ai under the Apache-2.0 license. 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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