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 laboramus-ai/laboramus-ai-claude-plugin --skill interview-prepgit clone --depth 1 https://github.com/laboramus-ai/laboramus-ai-claude-pluginWrote 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/laboramus-ai/laboramus-ai-claude-plugin/interview-prep)<a href="https://agentmods.dev/skills/laboramus-ai/laboramus-ai-claude-plugin/interview-prep"><img src="https://agentmods.dev/badge/skills/laboramus-ai/laboramus-ai-claude-plugin/interview-prep/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/laboramus-ai/laboramus-ai-claude-plugin/interview-prep"><img src="https://agentmods.dev/badge/skills/laboramus-ai/laboramus-ai-claude-plugin/interview-prep.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00041 | $0.00515 |
| Opus 5 | $0.00020 | $0.00258 |
| Sonnet 5 | $0.00008 | $0.00103 |
| Haiku 4.5 | $0.00004 | $0.00052 |
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 12d 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
Laboramus — Interview Prep
A leaf step: it consumes existing artifacts and produces interview-prep.md. Nothing depends on it. Written in the user's language.
Inputs (use what exists)
Locate the current application folder per ../../references/conventions.md §1. Then use:
strategy-brief.md, analyses/employer.md, analyses/fit-comparison.md, analyses/role-requirements.md, job-posting.md, profile/candidate-profile.md.
Output → interview-prep.md
1. Interview questions (15–20, in 4 categories)
- Standard HR (3–4): personalized versions of classics (strengths, weaknesses, goals) — based on the candidate's real profile, never generic.
- Skill gaps (2–4): questions targeting the gaps from fit-comparison and their mitigations. Only if real gaps exist.
- Behavioral / STAR (3–4): "Tell me about a time when…" tied to concrete experiences in the profile and requirements in the role.
- Motivation (2–3): "Why this company? / Why this role?" grounded in the employer analysis and the candidate's actual career logic.
(No cultural-fit category — we don't run cultural-fit analysis.)
For each question give:
- the question,
- why it's asked + which analysis it derives from,
- difficulty (easy / medium / hard),
- a model-answer outline (3–5 bullet points — NOT a full scripted answer),
- the strength to highlight (from profile/brief),
- a pitfall to avoid.
2. Questions to ask the employer (5–7)
Smart questions across culture / role / growth / team / practical. For ones answerable from the employer analysis, give a suggested answer; for ones needing insider knowledge, note that.
3. Prep tips (3–5)
Specific to THIS application, not generic advice.
Rules
Personalization is mandatory — no generic questions without context. Everything traces to the analyses. Outlines, not scripted answers. If a personality summary exists, use it only as reinforcement (the "does it help?" rule).
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.
- 12d ago First seen · 39 lines · 41 tokens per session scan A 12814c0e40bf
interview-prep is a skill published in the GitHub repository laboramus-ai/laboramus-ai-claude-plugin (2 stars, last pushed 13d ago), licensed MIT. It adds 41 tokens to every session and 515 once invoked, about $0.0002 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 2026-08-31.
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