Skill

Master Your Job Search with an AI Coach

A persistent, adaptive coaching skill for the full job search lifecycle, from JD decoding to offer negotiation.


80
Spark score
out of 100
Updated last month
Version 13.4.0

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Why it matters

Navigate the entire job search lifecycle with a persistent, adaptive AI coach. This system analyzes your profile, prepares you for interviews, and helps you negotiate offers.

Outcomes

What it gets done

01

Decode job descriptions and identify recruiter questions.

02

Optimize your resume and LinkedIn profile for ATS.

03

Conduct mock interviews across various formats.

04

Analyze past interview transcripts to identify and address weaknesses.

Install

Add it to your toolbox

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/ag-interview-coach | bash

Overview

Interview Coach

A persistent job-search coaching skill covering JD decoding, resume and LinkedIn audits, mock interviews, transcript analysis, a story bank, and offer negotiation scripting. Use it when starting or actively running a job search; not a substitute for expert review of your actual materials.

What it does

Interview Coach is a persistent, adaptive coaching system for the full job search lifecycle - not a static question bank, but 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 every interaction picks up where the last one left off instead of starting cold.

It covers JD decoding through six lenses with a fit verdict and recruiter questions to ask, resume and LinkedIn work (ATS audit, bullet rewrites, platform-native optimization), mock interviews across behavioral, system design, case, panel, and technical formats, transcript analysis (paste a transcript from Otter, Zoom, or Grain and it auto-detects the format), a storybank system for building STAR stories with earned secrets and retrieval drills, and comp and negotiation coaching covering pre-offer scripting, offer analysis, and exact negotiation scripts. In total it exposes 23 commands spanning the search lifecycle.

When to use - and when NOT to

Use it when starting a job search and you need a structured system, when prepping for a specific interview (company research, mock interviews, hype/motivation work), when you want to analyze a past interview transcript for gaps, when negotiating an offer or handling comp questions on a recruiter screen, or when building and maintaining a storybank of interview-ready stories.

Use this skill only when the task clearly matches the scope described above - it is not a substitute for environment-specific validation, testing, or expert review of your actual materials, and you should stop and ask for clarification if required inputs, permissions, or success criteria are missing.

Inputs and outputs

Inputs include your resume, target role, timeline, and raw interview transcripts pasted from tools like Otter, Zoom, or Grain. Outputs include a prioritized action plan, role-specific prep briefs, tailored mock interview questions, transcript scores across five dimensions with a drill plan targeting your gaps, STAR stories, and negotiation scripts.

Install it with:

npx skills add dbhat93/job-search-os

Then invoke /coach and type kickoff to start - the coach asks for your resume, target role, and timeline, then builds your profile and hands back a prioritized action plan. Use prep <company> <role> to prepare for a specific opening (it runs company research and queues mock questions tailored to that company's process), analyze to score a pasted transcript, or salary to work through a compensation question with a defensible range.

Who it's for

Job seekers who want a structured, persistent coaching system across an entire search - from initial JD triage and resume tuning through mock interviews, transcript review, and final offer negotiation - rather than one-off interview tips.

FAQ

Common questions

Discussion

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