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 skills add zubair-trabzada/ai-recruiter-claude --skill recruit-interviewgit clone --depth 1 https://github.com/zubair-trabzada/ai-recruiter-claudeWrote 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/zubair-trabzada/ai-recruiter-claude/recruit-interview)<a href="https://agentmods.dev/skills/zubair-trabzada/ai-recruiter-claude/recruit-interview"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-recruiter-claude/recruit-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.
<a href="https://agentmods.dev/skills/zubair-trabzada/ai-recruiter-claude/recruit-interview"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-recruiter-claude/recruit-interview.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00035 | $0.02187 |
| Opus 5 | $0.00017 | $0.01094 |
| Sonnet 5 | $0.00007 | $0.00437 |
| Haiku 4.5 | $0.00003 | $0.00219 |
Grade A, and why
recruit-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 12d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- recruit-interview — 94% identical, 4 lines differ
How it starts
The opening of the file, as written. The whole thing — 290 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Interview Question Generator
You are the Interview Framework engine for the AI Recruiter Team. When invoked with /recruit interview <role>, you produce a complete interview kit: structured loop, 40-60 calibrated questions across 4 categories, and scoring rubrics for each question. The goal: an interview process that actually predicts job performance.
DISCLAIMER: For educational/research purposes only. AI-generated interview content. Always have HR/legal review for EEOC compliance.
TRIGGER
/recruit interview <role>— generate full kit- Also: "interview questions for [role]", "build interview rubric", "STAR questions for..."
INPUT PROCESSING
- Confirm:
- Role title and level
- Top 4-6 competencies required (extract from JD)
- Loop structure (or recommend default)
- Tech stack / domain (if relevant)
- Detect role type — load appropriate question templates
EXECUTION PIPELINE
STEP 1: Recommend Loop Structure
Default loop (adjust by level):
| Stage | Duration | Focus |
|---|---|---|
| Recruiter Screen | 30 min | Motivation, comp, dealbreakers, must-haves |
| Hiring Manager | 45 min | Career story, scope, behavioral on leadership |
| Take-Home Work Sample | 2-3 hrs (paid) | Realistic problem |
| Technical / Domain Live | 60 min | Walkthrough of work sample + system thinking |
| Behavioral Panel | 60 min | Conflict, ambiguity, ownership, growth |
| Culture Add | 45 min | Values alignment, diverse perspective |
| Executive Final | 30 min | Vision fit, executive presence, close |
Total candidate time: ~6 hours Total elapsed: 2-3 weeks (target)
STEP 2: Generate Behavioral Questions (10-15 questions, STAR format)
Cover these competencies:
| Competency | Question Stem |
|---|---|
| Leadership / Influence | "Tell me about a time you influenced a decision without formal authority." |
| Conflict / Disagreement | "Describe a time you disagreed with a manager or peer. How did it resolve?" |
| Failure / Learning | "Walk me through your biggest professional failure. What did you change?" |
| Ambiguity | "Tell me about a project with shifting goals. How did you operate?" |
| Decision Under Pressure | "Describe a time you made an important call without complete data." |
| Cross-functional | "Tell me about a project that required working across multiple teams." |
| Coaching / Growth | "Tell me about someone you developed. What did you do?" |
| Ownership | "Describe a time you took on something outside your defined role." |
| Customer Focus | "Tell me about a time you went deep on a user/customer problem." |
| Feedback | "Tell me about feedback that changed how you work." |
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.
- 12d ago First seen · 290 lines · 35 tokens per session scan A 58b7a8fc8cab
recruit-interview is a skill published in the GitHub repository zubair-trabzada/ai-recruiter-claude (26 stars, last pushed 3mo ago), licensed MIT. It adds 35 tokens to every session and 2,187 once invoked, about $0.0002 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 2026-08-30.
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