Interview Coach is a Claude Code-based coaching system for the full job-search process, including job-description analysis, application materials, interview practice, answer evaluation, and offer negotiation. It is intended for job seekers who want tailored feedback and structured preparation based on their own experience and interview transcripts. Its catalogue entry consists of commands, a setting, and a skill that provide the coaching workflows.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/noamseg/interview-coach-skill/mockgit clone --depth 1 https://github.com/noamseg/interview-coach-skillWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/noamseg/interview-coach-skill/mock)<a href="https://agentmods.dev/commands/noamseg/interview-coach-skill/mock"><img src="https://agentmods.dev/badge/commands/noamseg/interview-coach-skill/mock.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00000 | $0.04224 |
| Opus 5 | $0.00000 | $0.02112 |
| Sonnet 5 | $0.00000 | $0.00845 |
| Haiku 4.5 | $0.00000 | $0.00422 |
Grade A, and why
mock scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 216 lines — stays where its author put it; the contents beside it link to each section on GitHub.
mock — Full Simulated Interview
A complete simulated interview (4-6 questions in sequence) with holistic feedback on the full arc — not just individual answers.
Setup
- Ask for format (behavioral screen, deep behavioral, panel, bar raiser, system design/case study, technical+behavioral mix — see format taxonomy in
references/commands/prep.md). For system design/case study and technical+behavioral mix: Check Interview Loops for saved format data fromprep. If format data exists for this company+round, use it. If no format data exists, run the Format Discovery Protocol (seereferences/commands/prep.md) and save the result to Interview Loops. See format-specific simulation UX sections below. - Ask for company/role context (or use existing prep data).
- Calibrate difficulty to the candidate's progression stage. Check Drill Progression in
coaching_state.md— if the candidate is at Stage 2 (pushback), the mock should be calibrated to push on credibility. If they're at Stage 6+ (panel/stress), they can handle maximum intensity. Don't run a maximum-difficulty mock for a candidate who hasn't cleared basic constraint drills. - Calibrate tone to the target company. A mock for a FAANG final round should feel very different from a Series A startup first call:
- Large tech companies: more structured, higher bar on specificity and metrics, interviewers often follow rubrics
- Startups: more conversational, care more about adaptability and scrappiness, may go off-script
- Consulting/finance: more case-study oriented, precision matters, presentation polish expected
- If prep data exists for this company, use the culture read and format analysis to shape the mock's feel.
- Set interviewer persona based on format. For panel, deploy 2-3 distinct interviewer archetypes from
references/role-drills.md. - For PM mocks: Include at least one "project deep-dive" question — hiring manager research shows the project component is consistently the most informative part of PM evaluations (Lenny's Newsletter). Probe one project end-to-end: decisions made, tradeoffs considered, metrics tracked, lessons learned. Also draw questions from the 4 high-signal themes in
prep.md(High-Signal Question Patterns) to create question variety that goes beyond standard behavioral categories.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 216 lines · 0 tokens per session scan A 177ef41df6bd
mock is a command published in the GitHub repository noamseg/interview-coach-skill (2,112 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 4,224 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
lrn
Execute the /vibeguard:learn command. $ARGUMENTS.
review
Cold re-quiz on code that already shipped — your own session commits, not the change in front of you.
annex-a-deep-dive
Deep dive analysis of ISO 27001 Annex A control domains with implementation guidance.
start-10-1
Command "start-10-1" from minicoohei/ai-agent-camp, covering 🎓 lesson 10-1: clasp基本・gasプロジェクト管理, 📍 このセッションでやること, 🎯 準備チェック, 🚀 step 1: claspのインストールと apps script api の確認 and 🚀 step 2: google認証.
start-13-4.en
Welcome to Lesson 13-4: Landing Page Implementation!
learn-story-flow
Learn story-flow concepts with interactive guidance for junior developers.