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.
npx agentmods add skills/palashjain95/jobhunter/interview-prepnpx skills add palashjain95/jobhunter --skill interview-prepgit clone --depth 1 https://github.com/palashjain95/jobhunterWrote 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.
[](https://agentmods.dev/skills/palashjain95/jobhunter/interview-prep)<a href="https://agentmods.dev/skills/palashjain95/jobhunter/interview-prep"><img src="https://agentmods.dev/badge/skills/palashjain95/jobhunter/interview-prep.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00071 | $0.01346 |
| Opus 5 | $0.00036 | $0.00673 |
| Sonnet 5 | $0.00014 | $0.00269 |
| Haiku 4.5 | $0.00007 | $0.00135 |
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.
How it starts
The opening of the file, as written. The whole thing — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/interview-prep
Usage
/interview-prep <company name + role>
/interview-prep <company name + role> recruiter-screen
How It Works
┌─────────────────────────────────────────────────────────┐
│ INTERVIEW PREP │
├─────────────────────────────────────────────────────────┤
│ Step 1: CONTEXT │
│ - Read JD + candidate profile + stories │
│ - Detect company → load matching framework │
│ (e.g., amazon.md for LPs, mckinsey-bain-bcg.md) │
│ │
│ Step 2: PREP PACKAGE │
│ - Likely questions with STAR frameworks │
│ - Power stories mapped to question types │
│ - Smart questions to ask │
│ - Red flags + compensation notes │
│ │
│ Step 3: FOLLOW-UP QUESTIONS │
│ - Scenario questions from JD responsibilities │
│ - Deep-dive follow-ups for later rounds │
│ - Culture + motivation probes │
└─────────────────────────────────────────────────────────┘
Inputs
- Job description (provided by user)
- knowledge/profile.md — candidate context
- knowledge/stories/ — STAR story bank
- knowledge/frameworks/writing-framework.md — for structuring verbal answers
- knowledge/values/personal.md — for culture fit and motivation questions
- If available: output/[company]/company-brief.md — use company intel to tailor
- interview-type (if specified): recruiter-screen / technical / hiring-manager / final
- ${CLAUDE_PLUGIN_ROOT}/.claude/resources/ — detect the company or career path and load the matching framework. Search companies/ first (e.g. amazon.md, google.md), then paths/ (e.g. consulting.md, pe.md, marketplace.md), then fall back to general.md.
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.
- 5d ago First seen · 167 lines · 71 tokens per session scan A c32bd6640536
interview-prep is a skill published in the GitHub repository palashjain95/jobhunter (2 stars, last pushed 5mo ago), licensed MIT. It adds 71 tokens to every session and 1,346 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 2026-08-31.
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