prep-interview

prep-interview is a cursor rule for Cursor from jain777/jobclaw-skills. It costs 96 tokens per session (217 once invoked), scanned A, original, MIT.

An interview preparation brief built from likely questions, profile-based STAR talking points, a checklist, and questions to ask the interviewer. STAR is a format for describing a Situation, Task, Action, and Result.

In plain words
What is it for?
Use it before an interview to prepare 8–12 questions across the rounds and draft grounded talking points. It can use company research when available or perform a limited check itself.
Why use it?
It turns scattered preparation into a plan connected to the candidate's experience and the interview rounds.

Cursor rule for Cursor

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 rules/jain777/jobclaw-skills/prep-interview
Clone the repo
git clone --depth 1 https://github.com/jain777/jobclaw-skills

Made for: Cursor.

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 prep-interview

README.md
[![agentmods](https://agentmods.dev/badge/rules/jain777/jobclaw-skills/prep-interview.svg)](https://agentmods.dev/rules/jain777/jobclaw-skills/prep-interview)
Your own site
<a href="https://agentmods.dev/rules/jain777/jobclaw-skills/prep-interview"><img src="https://agentmods.dev/badge/rules/jain777/jobclaw-skills/prep-interview.svg" alt="Measured on agentmods" height="20"></a>
Per session 96 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 217 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 $0.00096 $0.00217
Opus 5 $0.00048 $0.00109
Sonnet 5 $0.00019 $0.00043
Haiku 4.5 $0.00010 $0.00022

Measured 5d ago against content hash a938e5cd5c45, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

prep-interview 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.

.cursor/rules/prep-interview.mdc · 11 lines

What it actually says

prep-interview

This task maps to the prep-interview skill in this repo. Read skills/prep-interview/SKILL.md and follow it exactly — it is the single source of truth for this workflow.

Before producing any output, obey the shared rules in skills/_shared/RULES.md (never fabricate, never echo the context: block, region-pack-first, no emoji, known-info gate).

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 · 11 lines · 96 tokens per session scan A a938e5cd5c45

Subscribe to this mod's changes

prep-interview is a cursor rule published in the GitHub repository jain777/jobclaw-skills (5 stars, last pushed 2mo ago), licensed MIT. It adds 96 tokens to every session and 217 once invoked, about $0.0005 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.