ownership-impact-interviewer

ownership-impact-interviewer is a skill for Claude Code, Codex from PrepLabsAI/InterviewMentor. It costs 105 tokens per session (4,946 once invoked), scanned A, original, MIT.

A practice interviewer for behavioral questions about taking ownership beyond assigned work and measuring impact. It asks what you noticed, what you chose to own, what you personally did, and how the result was measured.

In plain words
What is it for?
Use it to rehearse ownership-and-impact stories for software engineering interviews, from noticing an unassigned problem through follow-through and team or business outcomes.
Why use it?
It helps turn broad claims about initiative or impact into a clear account of your actions and measurable results. This makes your scope and contribution easier to explain.

Skill for Claude CodeCodex

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

Good fit Use it to rehearse ownership-and-impact stories for software engineering interviews, from noticing an unassigned problem through follow-through and team or business outcomes.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/preplabsai/interviewmentor/ownership-impact-interviewer
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 PrepLabsAI/InterviewMentor --skill ownership-impact-interviewer
Clone the repo
git clone --depth 1 https://github.com/PrepLabsAI/InterviewMentor

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 ownership-impact-interviewer

README.md
[![agentmods](https://agentmods.dev/badge/skills/preplabsai/interviewmentor/ownership-impact-interviewer/github.svg)](https://agentmods.dev/skills/preplabsai/interviewmentor/ownership-impact-interviewer)
Your own site
<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.

agentmods 80×15 button for ownership-impact-interviewer

Your own site · 80×15
<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>
Per session 105 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,946 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 $0.00105 $0.04946
Opus 5 $0.00053 $0.02473
Sonnet 5 $0.00021 $0.00989
Haiku 4.5 $0.00011 $0.00495

Measured 9d ago against content hash c93b77b961e8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

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 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.

agents/behavioral/ownership-impact-interviewer/SKILL.md · 230 lines

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.

Read the full file on GitHub · 230 lines

Files

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.

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 · 230 lines · 105 tokens per session scan A c93b77b961e8

Subscribe to this mod's changes

ownership-impact-interviewer is a skill published in the GitHub repository PrepLabsAI/InterviewMentor (103 stars, last pushed 2mo ago), licensed MIT. It adds 105 tokens to every session and 4,946 once invoked, about $0.0005 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.

Related

Other skills, from other repositories

hr-onboarding

A new-hire onboarding plan as a single page — first week schedule, buddy + manager intro, learning track, equipment checklist, and "you're set when…" outcomes. Use when the brief mentions "onboarding", "new hire", "first week plan", or "入职".

nexu-io/open-design · 62 tokens

book-mirror

Take any book (EPUB/PDF), produce a personalized chapter-by-chapter analysis. Each chapter is preserved in detail (The Chapter) and mirrored back to the reader's actual life (The Mirror) using brain context. The mirror observes and resonates — a friend pointing out parallels, NOT a consultant rearranging the reader's…

garrytan/gbrain · 138 tokens

miniapp

Build a tiny interactive HTML playground only when someone asks to see, play with, or step through a mechanism.

yc-software/qm · 25 tokens

eli5

Explain research, papers, or technical ideas in plain English with minimal jargon, concrete analogies, and clear takeaways. Use when the user says "ELI5 this", asks for a simple explanation of a paper or research result, wants jargon removed, or asks what something technically dense actually means.

companion-inc/feynman · 63 tokens

deck-course-module

A course or workshop slide template with persistent learning goals, teaching pages, multiple-choice self-tests, and a wrap-up.

nexu-io/html-anything · 25 tokens

master-yinguang

A reference-based assistant for questions about Yinguang and Pure Land Buddhism, a Buddhist tradition focused on faith, ethical living, and practice connected with rebirth in the Pure Land. It can answer in Yinguang’s historical teaching style.

xr843/Master-skill · 274 tokens