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 PramodDutta/qaskills --skill interview-prep-generatorgit clone --depth 1 https://github.com/PramodDutta/qaskillsWrote 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/pramoddutta/qaskills/interview-prep-generator)<a href="https://agentmods.dev/skills/pramoddutta/qaskills/interview-prep-generator"><img src="https://agentmods.dev/badge/skills/pramoddutta/qaskills/interview-prep-generator/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/pramoddutta/qaskills/interview-prep-generator"><img src="https://agentmods.dev/badge/skills/pramoddutta/qaskills/interview-prep-generator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
SkillSpector: 1 finding, up to low
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- low Excessive Agency · line 415 Skill's behavior or capabilities extend beyond its stated purpose. Scope creep allows an agent to perform actions unrelated to its documented functionality, increasing the attack surface.Fix: Limit the skill's scope to its documented purpose. Remove instructions that enable the agent to perform actions outside its stated functionality.
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 | $0.00016 | $0.03243 |
| Opus 5.5 | $0.00006 | $0.01297 |
| Sonnet 5.5 | $0.00003 | $0.00649 |
| Haiku 4.5 | $0.00002 | $0.00324 |
Grade A, and why
Interview Prep Generator 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 — 422 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Interview Prep Generator
When to Use This Skill
Use this skill when the user wants to:
- Prepare for a job interview
- Practice answering interview questions
- Create STAR stories from their experience
- Anticipate questions for a specific role
- Mentions: "interview prep", "prepare for interview", "STAR stories", "interview questions", "behavioral questions"
Core Capabilities
- Generate role-specific interview questions
- Create STAR stories from resume bullets
- Predict questions based on job description
- Prepare answers for common questions
- Create talking points for each experience
- Identify potential concerns and prepare responses
Interview Preparation Framework
Phase 1: Role Analysis
- Extract likely questions from job description
- Identify skills that will be tested
- Research company interview style
Phase 2: Story Banking
- Convert resume bullets into STAR stories
- Create stories for common competencies
- Practice concise delivery
Phase 3: Mock Preparation
- Practice common questions
- Prepare questions to ask
- Research company-specific topics
The STAR Method Detailed
Structure
- Situation: Set the context (1-2 sentences)
- Task: Describe your responsibility (1 sentence)
- Action: Explain what YOU did (2-3 sentences)
- Result: Share the outcome with metrics (1-2 sentences)
STAR Story Template
SITUATION: "At [Company], we faced [specific challenge/context]..."
TASK: "I was responsible for [specific ownership]..."
ACTION: "I [specific action 1], [specific action 2], and [specific action 3]..."
RESULT: "As a result, [quantified outcome]. This led to [business impact]."
Example STAR Story
Question: "Tell me about a time you led a team through a difficult project."
Answer:
SITUATION: "At TechCorp, our main product was losing customers to a competitor who had launched a better mobile experience. We were seeing 5% monthly churn, up from our normal 2%."
TASK: "As the product manager, I was responsible for turning around our mobile product to stop the bleeding and win back customers."
ACTION: "I started by interviewing 30 churned customers to understand exactly why they left. Based on that research, I prioritized 5 critical features that would achieve parity with competitors. I then worked with engineering to restructure our roadmap, negotiated with leadership to add 2 contract developers, and implemented weekly sprint reviews to keep the project on track. I also started a beta program with 50 of our best customers to get feedback before full launch."
RESULT: "We launched the improved mobile app in 3 months, reducing churn from 5% back to 2% within 60 days. We recovered 35% of churned customers and the NPS for our mobile app increased from 32 to 58. This project was recognized in our company all-hands as a turnaround success."
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 · 422 lines · 16 tokens per session scan A 92309c692400
Interview Prep Generator is a skill published in the GitHub repository PramodDutta/qaskills (241 stars, last pushed 6d ago), licensed MIT. It adds 16 tokens to every session and 3,243 once invoked, about $0.0001 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 2026-09-03.
Other skills, from other repositories
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This skill should be used when the user wants to "practice interview", "mock interview", "prepare for interview", "system design interview", "behavioral interview", "STAR stories", "interview coaching", or wants to prepare for technical interviews using the Placed career platform at placed.exidian.tech.
project-interview-skill
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placed-career-tools
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placed-job-tracker
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