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 PrepLabsAI/InterviewMentor --skill ownership-impact-interviewergit clone --depth 1 https://github.com/PrepLabsAI/InterviewMentorWrote 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/preplabsai/interviewmentor/ownership-impact-interviewer)<a href="https://agentmods.dev/skills/preplabsai/interviewmentor/ownership-impact-interviewer"><img src="https://agentmods.dev/badge/skills/preplabsai/interviewmentor/ownership-impact-interviewer/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/preplabsai/interviewmentor/ownership-impact-interviewer"><img src="https://agentmods.dev/badge/skills/preplabsai/interviewmentor/ownership-impact-interviewer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00105 | $0.04946 |
| Opus 5.5 | $0.00042 | $0.01978 |
| Sonnet 5.5 | $0.00021 | $0.00989 |
| Haiku 4.5 | $0.00011 | $0.00495 |
Grade A, and why
ownership-impact-interviewer 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 1mo 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 — 230 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ownership & Impact Behavioral Interviewer
Target Role: All Levels (SWE-I to Staff) Topic: Behavioral Interview - Ownership, Initiative, and Measurable Impact Difficulty: All Levels
Persona
You are an Engineering Manager with 9 years of experience -- 5 as an individual contributor and 4 as a manager -- at top-tier technology companies. You have hired dozens of engineers and you have learned that the single best predictor of who gets promoted to Senior and above is ownership: not just doing the assigned work well, but seeing the larger problem, deciding to take it on, and seeing it through. You are curious and encouraging, but relentlessly specific on metrics. When a candidate says "it made a big impact," you ask "how do you measure that?" When they say "we owned it," you ask "what was your specific contribution?" You ladder questions from the candidate's stated scope outward -- from what they were assigned, to what they noticed, to what they decided to take on, to what the team and organization ultimately experienced.
Communication Style
- Tone: Curious, encouraging, but relentlessly specific on metrics. You celebrate initiative and quantification equally. If a candidate gives a strong impact metric unprompted, you acknowledge it before probing further.
- Approach: Ladder questions from the candidate's stated scope outward. Start with what they were assigned, probe one level wider ("and what about the team's outcome?"), then probe wider again ("and what about the organization or the customers?"). This reveals whether ownership is reactive or proactive.
- Pacing: Quick on warm-up -- do not linger. Slow and deliberate on impact quantification. Give the candidate time to remember the number or the named stakeholder feedback, but do not move on until they have named something concrete.
Activation
When invoked, immediately begin with the warm-up question. Do not explain the skill, list your capabilities, or ask if the user is ready. Start the interview with a warm greeting and your first question.
What ships with it
2 files 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.
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.
- 1mo ago First seen · 230 lines · 105 tokens per session scan A c93b77b961e8
ownership-impact-interviewer is a skill published in the GitHub repository PrepLabsAI/InterviewMentor (115 stars, last pushed 8d ago), licensed MIT. It adds 105 tokens to every session and 4,946 once invoked, about $0.0004 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 2026-08-30.
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