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/cosmicstack-labs/mercury-agent-skills/interview-prepnpx skills add cosmicstack-labs/mercury-agent-skills --skill interview-prepgit clone --depth 1 https://github.com/cosmicstack-labs/mercury-agent-skillsWrote 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/cosmicstack-labs/mercury-agent-skills/interview-prep)<a href="https://agentmods.dev/skills/cosmicstack-labs/mercury-agent-skills/interview-prep"><img src="https://agentmods.dev/badge/skills/cosmicstack-labs/mercury-agent-skills/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 5.1 | $0.00021 | $0.00428 |
| Opus 5 | $0.00010 | $0.00214 |
| Sonnet 5 | $0.00004 | $0.00086 |
| Haiku 4.5 | $0.00002 | $0.00043 |
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 6d 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.
What it actually says
Interview Prep
Systematic preparation for technical and behavioral interviews.
Behavioral Frameworks
STAR for Behavioral Questions
Tell me about a time when...
| Element | What to Cover |
|---|---|
| Situation | Context — project, team, timeline |
| Task | Your specific responsibility |
| Action | What YOU did (not the team) |
| Result | Quantified outcome, what you learned |
Common Questions to Prepare
- "Tell me about yourself" → 60-second career narrative
- "Biggest challenge/project" → STAR with technical depth
- "Conflict with a teammate" → Show emotional intelligence
- "Failure/mistake" → Honest story + what you learned
- "Why this company?" → Research-driven, specific
Technical Interview Prep
Coding
- Practice 2-3 problems daily (LeetCode medium)
- Focus on: Arrays, Hashmaps, Trees, Graphs, DP
- Always: Clarify → Brute force → Optimize → Code → Test
- Think out loud — interviewer wants to hear your process
System Design
Practice these scenarios:
- Design URL shortener (read-heavy, hashing, scaling)
- Design chat system (WebSockets, persistence, presence)
- Design news feed (fan-out, caching, ranking)
- Design rate limiter (token bucket, sliding window, distributed)
Pre-Interview Checklist
- Research company and interviewers on LinkedIn
- Prepare 3 questions to ask at end
- Test your camera, mic, internet
- Have water, notebook, pen ready
- Review your resume and projects
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.
- 6d ago First seen · 55 lines · 21 tokens per session scan A 8a2f9438d720
interview-prep is a skill published in the GitHub repository cosmicstack-labs/mercury-agent-skills (471 stars, last pushed 11d ago), licensed MIT. It adds 21 tokens to every session and 428 once invoked, about $0.0001 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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