What is interview-prep?

An interview-preparation guide that connects a role's requirements with specific evidence from your background. It also identifies honest gaps, likely questions, questions to ask, and reasons to decline.

Use it to prepare stories, technical or system-design answers, gap explanations, questions for the interviewer, and personal decision criteria.

It replaces vague claims with concrete examples of what you personally did. It also helps you evaluate the employer instead of treating the interview as one-way screening.

interview-prep — Command for Claude Code by Amey-Thakur/AI-SKILLS

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.

Clone the repo

git clone --depth 1 https://github.com/Amey-Thakur/AI-SKILLS

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.

README.md

[![agentmods](https://agentmods.dev/badge/commands/amey-thakur/ai-skills/interview-prep/github.svg)](https://agentmods.dev/commands/amey-thakur/ai-skills/interview-prep)

Your own site

<a href="https://agentmods.dev/commands/amey-thakur/ai-skills/interview-prep"><img src="https://agentmods.dev/badge/commands/amey-thakur/ai-skills/interview-prep/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/commands/amey-thakur/ai-skills/interview-prep"><img src="https://agentmods.dev/badge/commands/amey-thakur/ai-skills/interview-prep.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 15 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 234 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

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.

Model	Per session	Once invoked
Fable 5.1	$0.00015	$0.00234
Opus 5.5	$0.00006	$0.00094
Sonnet 5.5	$0.00003	$0.00047
Haiku 4.5	$0.00002	$0.00023

Measured 2mo ago against content hash 362a707e64f3, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, 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 2mo 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.

commands/interview-prep.md · 36 lines

What it actually says

You were invoked as a slash command. The user's input:

$ARGUMENTS

Use that input to fill this prompt's variables (take the main content, topic, or task from it; ask only if a required value is missing and not supplied), then follow the prompt exactly.

Prepare for this interview:

{role}

Background: {background}

Use technical-interviews and system-design-answer.

Produce:

What the role really needs, read from the description and context.
Your strongest evidence for each requirement, as specific stories.
Gaps, and how to address them honestly.
Questions likely to be asked, and the structure of your answers.
Questions to ask them, that reveal what you need to know.
What would make you decline the role.

Rules: prepare evidence rather than claims, with specifics including what you did versus what the team did. Address gaps honestly rather than deflecting. Interviews are two-way, so include what you need to learn. Do not fabricate experience.

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.

2mo ago First seen · 36 lines · 15 tokens per session scan A 362a707e64f3

Subscribe to this mod's changes

interview-prep is a command published in the GitHub repository Amey-Thakur/AI-SKILLS (13 stars, last pushed 2mo ago), licensed MIT. It adds 15 tokens to every session and 234 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-03.

Claude Code Learning and teaching Planning agent-skills ai-agents ai-skills claude-skills cursor

interview-prep next to 6 commands from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
interview-prepAmey-Thakur/AI-SKILLS	Command	13	2mo ago	MIT	A	15	Claude Code
jtbdDragoon0x/product-skills	Command	4	8mo ago	none	A	6	Claude Code
checklistgithub/spec-kit	Command	148k	today	MIT	A	13	Claude Code
clarifygithub/spec-kit	Command	148k	today	MIT	A	27	Claude Code
specifygithub/spec-kit	Command	148k	today	MIT	A	13	Claude Code
analyzegithub/spec-kit	Command	148k	today	MIT	A	26	Claude Code
convergegithub/spec-kit	Command	148k	today	MIT	A	35	Claude Code