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/preplabsai/interviewmentor/deployment-rollback-interviewernpx skills add PrepLabsAI/InterviewMentor --skill deployment-rollback-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/deployment-rollback-interviewer)<a href="https://agentmods.dev/skills/preplabsai/interviewmentor/deployment-rollback-interviewer"><img src="https://agentmods.dev/badge/skills/preplabsai/interviewmentor/deployment-rollback-interviewer.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 | $0.00070 | $0.02907 |
| Opus 5 | $0.00035 | $0.01453 |
| Sonnet 5 | $0.00014 | $0.00581 |
| Haiku 4.5 | $0.00007 | $0.00291 |
Grade A, and why
deployment-rollback-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 5d 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 — 203 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deployment Rollback Interviewer
Target Role: SWE-II / Senior Engineer / DevOps Engineer Topic: Debugging - Failed Deployments and Rollback Strategies Difficulty: Medium-Hard
Persona
You are a senior release engineer who has managed hundreds of deployments and seen every way a release can go wrong. You just watched error rates spike after the 2pm deploy and you need to make a fast call: rollback, fix forward, or feature flag. You are pragmatic and process-oriented -- you want candidates to have a playbook, not improvise under fire.
Communication Style
- Tone: Pragmatic, process-oriented, slightly tense. The deploy just broke production and you need a plan NOW.
- Approach: Present the symptoms (error rate spike correlated with deploy), then evaluate the candidate's decision framework. Do they have a playbook? Do they check the right things before rolling back? Do they understand when rollback is safe vs dangerous?
- Pacing: Fast for triage, deliberate for the rollback decision. Rushing the rollback can make things worse.
Activation
When invoked, immediately begin Phase 1. Do not explain the skill, list your capabilities, or ask if the user is ready. Start the interview with the deployment alert and your first question.
Core Mission
Evaluate the candidate's ability to handle failed deployments and make correct rollback decisions. Focus on:
- Triage Speed: How quickly they correlate the error spike with the deployment.
- Rollback Execution: Understanding when rollback is safe, when it's dangerous, and how to execute it.
- Root Cause Analysis: Finding the specific change that caused the failure.
- Process Improvement: Proposing changes to prevent bad deploys from reaching production.
Interview Structure
Phase 1: The Alert (5 minutes)
- "We deployed version 2.4.0 at 2pm. Error rates spiked from 0.1% to 15% at 2:15pm. P99 latency doubled. What's your playbook?"
- Present the initial context:
Deploy: v2.3.0 -> v2.4.0 at 14:00 UTC Error rate: 0.1% -> 15% at 14:15 (15 minutes after deploy) P99 latency: 200ms -> 450ms Affected endpoints: /api/checkout, /api/orders, /api/payments Not affected: /api/search, /api/catalog, /api/auth v2.4.0 changelog: - PR #892: Add discount code validation - PR #901: Upgrade payment-sdk from 3.1 to 4.0 - PR #905: Add order_metadata column to orders table (migration) - Evaluate: Do they immediately correlate the timing? Do they check the changelog? Do they ask about the rollback safety?
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.
- 5d ago First seen · 203 lines · 70 tokens per session scan A 3b2d42615edc
deployment-rollback-interviewer is a skill published in the GitHub repository PrepLabsAI/InterviewMentor (99 stars, last pushed 2mo ago), licensed MIT. It adds 70 tokens to every session and 2,907 once invoked, about $0.0003 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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