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
bysickn33
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
- Download SKILL.md from GitHub
- Place it in
.claude/skills/interview-coach/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How interview-coach Compares
| Feature / Agent | interview-coach | Standard Approach |
|---|---|---|
| Platform Support | multi | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/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