multiAI Summary Pending

interview-coach

Full job search coaching system — JD decoding, resume, storybank, mock interviews, transcript analysis, comp negotiation. 23 commands, persistent state.

28,273 stars

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/interview-coach/SKILL.md --create-dirs "https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/plugins/antigravity-awesome-skills-claude/skills/interview-coach/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/interview-coach/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How interview-coach Compares

Feature / Agentinterview-coachStandard Approach
Platform SupportmultiLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Full job search coaching system — JD decoding, resume, storybank, mock interviews, transcript analysis, comp negotiation. 23 commands, persistent state.

Which AI agents support this skill?

This skill is compatible with multi.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Interview Coach

## Overview

A persistent, adaptive coaching system for the full job search lifecycle.
Not a question bank — an opinionated system that tracks your patterns,
scores your answers, and gets sharper the more you use it. State persists
in `coaching_state.md` across sessions so you always pick up where you left off.

## Install

```bash
npx skills add dbhat93/job-search-os
```

Then type `/coach` → `kickoff`.

## When to Use This Skill

- Use when starting a job search and need a structured system
- Use when preparing for a specific interview (company research, mock, hype)
- Use when you want to analyze a past interview transcript
- Use when negotiating an offer or handling comp questions on recruiter screens
- Use when building or maintaining a storybank of interview-ready stories

## What It Covers

- **JD decoding** — six lenses, fit verdict, recruiter questions to ask
- **Resume + LinkedIn** — ATS audit, bullet rewrites, platform-native optimization
- **Mock interviews** — behavioral, system design, case, panel, technical formats
- **Transcript analysis** — paste from Otter/Zoom/Grain, auto-detected format
- **Storybank** — STAR stories with earned secrets, retrieval drills, portfolio optimization
- **Comp + negotiation** — pre-offer scripting, offer analysis, exact negotiation scripts
- **23 total commands** across the full search lifecycle

## Examples

### Example 1: Start your job search

```
/coach
kickoff
```

The coach asks for your resume, target role, and timeline — then builds
your profile and gives you a prioritized action plan.

### Example 2: Prep for a specific company

```
/coach
prep Stripe Senior PM
```

Runs company research, generates a role-specific prep brief, and queues
up mock interview questions tailored to Stripe's process.

### Example 3: Analyze an interview transcript

```
/coach
analyze
```

Paste a raw transcript from Otter, Zoom, or any tool. The coach
auto-detects the format, scores each answer across five dimensions,
and gives you a drill plan targeting your specific gaps.

### Example 4: Handle a comp question

```
/coach
salary
```

Coaches you through the recruiter screen "what are your salary
expectations?" moment with a defensible range and exact scripts.

## Source

https://github.com/dbhat93/job-search-os