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interview-prep

interview-prep is a command for Claude Code from s4nec4ke/hr-agent-ru. It costs 124 tokens per session (4,410 once invoked), scanned A, original, MIT.

A command that prepares interview materials for job applications marked as having an interview scheduled.

In plain words
What is it for?
Use it to create an interview brief, an interview script, and an empty transcript notebook for each matching vacancy.
Why use it?
It puts company context, domain notes, difficult questions, prepared answers, and questions for human-resources staff in one place.

Command for Claude Code

Written for Claude Code: installed under .claude/.

not rated 2 3mo ago A scan 124 tokens original MIT
View the source file s4nec4ke/hr-agent-ru
Install

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.

agentmods
npx agentmods add commands/s4nec4ke/hr-agent-ru/interview-prep
Clone the repo
git clone --depth 1 https://github.com/s4nec4ke/hr-agent-ru

Made for: Claude Code.

Wrote 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.

agentmods badge for interview-prep

README.md
[![agentmods](https://agentmods.dev/badge/commands/s4nec4ke/hr-agent-ru/interview-prep.svg)](https://agentmods.dev/commands/s4nec4ke/hr-agent-ru/interview-prep)
Your own site
<a href="https://agentmods.dev/commands/s4nec4ke/hr-agent-ru/interview-prep"><img src="https://agentmods.dev/badge/commands/s4nec4ke/hr-agent-ru/interview-prep.svg" alt="Measured on agentmods" height="20"></a>
Per session 124 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 4,410 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00124 $0.04410
Opus 5 $0.00062 $0.02205
Sonnet 5 $0.00025 $0.00882
Haiku 4.5 $0.00012 $0.00441

Measured 5d ago against content hash c4c18a74f130, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

interview-prep 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.

.claude/commands/interview-prep.md · 308 lines

How it starts

The opening of the file, as written. The whole thing — 308 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Interview Prep Generator

Принципы

  • Обработка строк по одной по очереди в основном потоке.
  • Один проход. Генерируем всё, что выводимо из source.md / card.md / correspondence.md / профиля / playbook.md. Факты, которых нет ни в одном источнике (дата/время звонка, формат/ссылка, состав команды, устные вопросы HR — если о них не написано в переписке), оставляем как явные плейсхолдеры [ … ] — кандидат дописывает руками. Команда их не ждёт и второго прохода под них не делает.
  • Никакого WebFetch и Agent-вызовов. Доменные знания (рынок, конкуренты, регуляции, unit-экономика) пишем из общих знаний. Конкретные факты 2026 года, которые нельзя проверить (свежие раунды, оценки, сделки, назначения, новости), помечаем ⚠️.
  • interview_transcript.md — ручной блокнот кандидата. Команда создаёт его пустым один раз и больше никогда не читает и не перезаписывает.

Storage layout (важно)

  • vacancies/vacancies.csv — CSV-индекс (10 колонок: id, Роль, Компания, Зарплата, Формат, Совпадение, Статус, Вакансия, Дата добавления, язык). Безопасно читать целиком.
  • vacancies/items/{id} {short_role} {company}/ — папка вакансии. Уже содержит source.md, (обычно) card.md и — если была переписка с HR — correspondence.md (лог диалога, создаёт /feedback-update). Эта команда добавляет в неё:
    • interview_brief.md — контекст + доменка + tricky-вопросы. Читается за день и ещё раз за час до звонка.
    • interview_script.md — оперативный лист на втором экране во время звонка.
    • interview_transcript.md — пустой блокнот для записи звонка.
  • vacancies/interviews/playbook.md — общая база (STAR-кейсы, стандартные ответы, цифры, мантра). НЕ дублируем её в папку вакансии — ссылаемся на разделы.
  • vacancies/interviews/progress_log.md — лог прогресса по интервью. Из него берём системные провалы, чтобы прицельно подобрать tricky-вопросы.
  • Лукап папки по id: glob vacancies/items/{id} * — ровно один матч (пробел после id защищает 1 от 10).
  • Контакт / Тип контакта / Канал / Комментарий в CSV отсутствуют — читаем их из шапки card.md.

Read the full file on GitHub · 308 lines

Changes

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.

  1. 5d ago First seen · 308 lines · 124 tokens per session scan A c4c18a74f130

Subscribe to this mod's changes

interview-prep is a command published in the GitHub repository s4nec4ke/hr-agent-ru (2 stars, last pushed 3mo ago), licensed MIT. It adds 124 tokens to every session and 4,410 once invoked, about $0.0006 per session on Opus 5. 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 2026-08-31.

Learning and teachingagent-skillsai-agentanthropicautomationclaudeclaude-code
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