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interview-prep

interview-prep is a skill for Claude Code, Codex from khalilbenaz/claude-skills-collection. It costs 84 tokens per session (1,550 once invoked), scanned A, original, MIT.

A job-interview preparation guide covering common, behavioural, technical, management, and business-case interviews. It explains STAR, a method for structuring answers around the situation, task, action, and result.

In plain words
What is it for?
Use it to practise introductions, behavioural answers, technical discussions, coding or system-design interviews, and mock interviews.
Why use it?
It turns a vague preparation process into likely questions and organised answers. It also helps identify weak points before the interview.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

not rated 22repo 19d ago A scan SkillSpector: pass 84 tokens original MIT

Good fit Use it to practise introductions, behavioural answers, technical discussions, coding or system-design interviews, and mock interviews.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/khalilbenaz/claude-skills-collection/interview-prep
View source ↗ khalilbenaz/claude-skills-collection khalilbenaz.github.io
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.

Any agent
npx skills add khalilbenaz/claude-skills-collection --skill interview-prep
Clone the repo
git clone --depth 1 https://github.com/khalilbenaz/claude-skills-collection

Made for: Claude Code, Codex.

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/skills/khalilbenaz/claude-skills-collection/interview-prep/github.svg)](https://agentmods.dev/skills/khalilbenaz/claude-skills-collection/interview-prep)
Your own site
<a href="https://agentmods.dev/skills/khalilbenaz/claude-skills-collection/interview-prep"><img src="https://agentmods.dev/badge/skills/khalilbenaz/claude-skills-collection/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.

agentmods 80×15 button for interview-prep

Your own site · 80×15
<a href="https://agentmods.dev/skills/khalilbenaz/claude-skills-collection/interview-prep"><img src="https://agentmods.dev/badge/skills/khalilbenaz/claude-skills-collection/interview-prep.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 84 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,550 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00084 $0.01550
Opus 5 $0.00042 $0.00775
Sonnet 5 $0.00017 $0.00310
Haiku 4.5 $0.00008 $0.00155

Measured 9d ago against content hash 9632dccdcea0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, 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 9d 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.

career-skills/interview-prep/SKILL.md · 143 lines

How it starts

The opening of the file, as written. The whole thing — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Interview Prep

Étape 1 — Collecte du contexte

Demander (toujours en une seule fois) :

  • Intitulé du poste + niveau (junior / confirmé / lead / manager)
  • Entreprise (taille, secteur, produit)
  • Type d'entretien : RH screening | technique (coding / system design / live coding) | manager | panel | cas business
  • Stack / domaine technique si applicable
  • Point faible à anticiper (gap de compétence, départ précédent, changement de secteur)

Étape 2 — Cartographie des questions probables

Générer 15-20 questions réparties en 4 catégories :

2a. Questions classiques (ouverture/clôture)

  • "Présentez-vous en 2 minutes."
  • "Pourquoi quittez-vous votre poste actuel ?"
  • "Où vous voyez-vous dans 3 ans ?"
  • "Quels sont vos points forts / axes de progression ?"

2b. Questions comportementales (méthode STAR)

Template STAR à appliquer pour chaque réponse :

Situation  : contexte bref (1-2 phrases)
Tâche      : votre rôle / responsabilité
Action     : ce que VOUS avez fait (verbes d'action, pas "on a")
Résultat   : mesurable si possible (%, €, délai, NPS...)

Exemples fréquents :

  • "Décrivez un conflit avec un collègue et comment vous l'avez résolu."
  • "Parlez d'un projet raté et ce que vous en avez tiré."
  • "Donnez un exemple où vous avez dû prioriser sous pression."

2c. Questions techniques (adapter au poste)

Dev backend / fullstack :

- Expliquez-moi la différence entre PUT et PATCH.
- Comment gérez-vous la cohérence dans une architecture microservices ?
- Quelle stratégie de retry utilisez-vous côté API ?

System design :

- Concevez un système de notification à 10M d'utilisateurs.
- Comment scaler une API de paiement avec une contrainte d'idempotence ?

Data / BI :

- Différence entre OLAP et OLTP — exemple concret ?
- Comment optimisez-vous une requête SQL lente ?

2d. Questions pièges (à désamorcer)

  • "Quel est votre salaire actuel ?" — répondre par la fourchette attendue, pas l'historique.
  • "Vous êtes surqualifié, non ?" — montrer l'alignement projet / long terme.
  • "Pourquoi avez-vous mis 8 mois sans travailler ?" — préparer une réponse factuelle, sans sur-justifier.
  • "Votre plus grande faiblesse ?" — choisir une vraie faiblesse avec le plan d'amélioration concret.

Read the full file on GitHub · 143 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. 9d ago First seen · 143 lines · 84 tokens per session scan A 9632dccdcea0

Subscribe to this mod's changes

interview-prep is a skill published in the GitHub repository khalilbenaz/claude-skills-collection (22 stars, last pushed 19d ago), licensed MIT. It adds 84 tokens to every session and 1,550 once invoked, about $0.0004 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 2026-09-03.

Learning and teachingPlanningai-skillsanthropicclaudefrench
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