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prep-interview

prep-interview is a skill for Claude Code from jain777/jobclaw-skills. It costs 67 tokens per session (1,403 once invoked), scanned A, original, MIT.

An interview-preparation brief containing likely questions, profile-based STAR talking points, a checklist, and questions to ask the employer. STAR is a way to structure an answer around a situation, task, action, and result.

In plain words
What is it for?
Use it to prepare for screening, technical, hiring-manager, panel, or final interviews, including stories based on real experience.
Why use it?
It turns a job and company context into a focused preparation plan instead of leaving the candidate to guess what to practise.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Part of the jobclaw-skills plugin — 20 skills shipped together

not rated 5repo 3mo ago A scan 67 tokens original MIT

Good fit Use it to prepare for screening, technical, hiring-manager, panel, or final interviews, including stories based on real experience.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/jain777/jobclaw-skills/prep-interview
View source ↗ jain777/jobclaw-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.

Any agent
npx skills add jain777/jobclaw-skills --skill prep-interview
Clone the repo
git clone --depth 1 https://github.com/jain777/jobclaw-skills

Made for: Claude Code.

Or install jobclaw-skills, the plugin that ships this one along with the rest of its 20 skills.

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/skills/jain777/jobclaw-skills/prep-interview/github.svg)](https://agentmods.dev/skills/jain777/jobclaw-skills/prep-interview)
Your own site
<a href="https://agentmods.dev/skills/jain777/jobclaw-skills/prep-interview"><img src="https://agentmods.dev/badge/skills/jain777/jobclaw-skills/prep-interview/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 prep-interview

Your own site · 80×15
<a href="https://agentmods.dev/skills/jain777/jobclaw-skills/prep-interview"><img src="https://agentmods.dev/badge/skills/jain777/jobclaw-skills/prep-interview.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 67 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,403 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00067 $0.01403
Opus 5 $0.00034 $0.00701
Sonnet 5 $0.00013 $0.00281
Haiku 4.5 $0.00007 $0.00140

Measured 10d ago against content hash 14199e6a3707, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, 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 10d 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.

skills/prep-interview/SKILL.md · 118 lines

How it starts

The opening of the file, as written. The whole thing — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.

prep-interview

Walk into the room ready. Hard rules: ../_shared/RULES.md. Question quality bar: reference/prep-rubric.md. Verb sourcing per tailor-resume/reference/action-verbs.md.

Inputs

  1. company + role (required).
  2. Profile — profile/master-profile.md (Notes / voice for tone; experience for STAR stories).
  3. Optional company brief — companies/<slug>.json from a prior /research-company run. If present, use it heavily; if absent, run a thin sweep here (≠ a full research pass).
  4. Optional round — --round screen | technical | hiring-manager | panel | final. If omitted, generate questions across the whole likely loop.

Method

  1. Region pack. Read knowledge/regions/<code>.md — US: behavioral often STAR-formal; IN: more credential-led at large MNCs. Note tone adjustments.

  2. Hydrate the company. If companies/<slug>.json exists, harvest:

    • jobSummary.dayToDayResponsibilities → likely "what would your first 30/60/90 look like" / "walk me through how you'd ..." Qs.
    • news.recentNews → 1–2 "saw the X announcement — how would you think about Y" Qs.
    • red_flags → honest concerns the user should diplomatically raise back.

    If absent, run a thin sweep: 3–5 WebSearch hits about the role + product + any recent news; no Reddit / Blind pass (that's research-company's job, not this one).

  3. Identify the loop. Map target.tracks to the canonical rounds from ../mock-interview/reference/report-schema.md:

    • software → coding · system-design · behavioral
    • product → product-sense · execution · strategy · behavioral
    • design → portfolio-review · whiteboard/app-critique · behavioral
    • data → coding/SQL · ML/stats · case · behavioral
    • quant → math-stats · research · coding · behavioral
    • finance → technical · case · fit
    • marketing → case · craft · behavioral
    • founders-office → case · ops · behavioral
    • sales → discovery/role-play · pitch/demo · behavioral
    • operations → case · execution · behavioral
    • customer-success → scenario/role-play · case · behavioral
    • content → portfolio/clips-review · writing-exercise · behavioral
    • hr → case · craft · behavioral

Read the full file on GitHub · 118 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 10d ago First seen · 118 lines · 67 tokens per session scan A 14199e6a3707

Subscribe to this mod's changes

prep-interview is a skill published in the GitHub repository jain777/jobclaw-skills (5 stars, last pushed 3mo ago), licensed MIT. It adds 67 tokens to every session and 1,403 once invoked, about $0.0003 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.

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