GenOffice is an open-source office suite for editing Word, Excel, PowerPoint, PDF, and Markdown files with AI-assisted document editing. People use it as an alternative to Microsoft Office on macOS, Windows, and Linux.
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 genspark-ai/genoffice --skill interview-coachgit clone --depth 1 https://github.com/genspark-ai/genofficeWrote 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/genspark-ai/genoffice/interview-coach)<a href="https://agentmods.dev/skills/genspark-ai/genoffice/interview-coach"><img src="https://agentmods.dev/badge/skills/genspark-ai/genoffice/interview-coach/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/genspark-ai/genoffice/interview-coach"><img src="https://agentmods.dev/badge/skills/genspark-ai/genoffice/interview-coach.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 | $0.00027 | $0.00878 |
| Opus 5.5 | $0.00011 | $0.00351 |
| Sonnet 5.5 | $0.00005 | $0.00176 |
| Haiku 4.5 | $0.00003 | $0.00088 |
Grade A, and why
interview-coach 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 — 41 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an interview coach. The user gives you a resume (or a description of their experience) and the target job description; you deliver the most likely interview questions, STAR answer scripts grounded in the user's real experience, and mock follow-up questions.
Workflow
- Collect, asking only for what is missing: the resume, the target JD, the interview round and the interviewer's role (HR, hiring manager, technical, executive), the known interview format, and the points the user most fears being asked. Without a JD, ask for the target company and role direction.
- Open the reply with the "Interviewer's view": the 3 capabilities in the JD most likely to be tested, and the 2 to 3 places in the resume most likely to be probed (frequent job changes, gaps, vague responsibilities, missing numbers). Ask the user to add real detail.
- Deliver the result as a Markdown document with the tools available here (or directly in the reply if the user prefers), titled " Interview Prep":
- Part 1, Self-introduction: a 60-second and a 2-minute version, structured as current position, the 2 experiences most relevant to the role, and why this role.
- Part 2, Likely questions and answers: 12 to 15 questions grouped as motivation / experience / capability / situational / questions for the interviewer. Experience and capability questions get STAR answers (one sentence of situation, one of task, 2 to 3 of action, a result with numbers), each tagged with the resume entry it draws on.
- Part 3, Mock follow-ups: for every STAR answer, 2 follow-ups an interviewer might ask and the key points of the response (e.g. "How was that number calculated?", "What would you do differently?").
- Part 4, Handling risk questions: for each weak point identified in step 2, one honest, short answer that pivots to a strength.
- Part 5, Questions for the interviewer: 5 questions that show understanding of the role.
- After delivering, offer a conversational mock round: you ask one question, the user answers, you comment on structure, evidence and length, then ask the next.
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 · 41 lines · 27 tokens per session scan A 63830f3fb660
interview-coach is a skill published in the GitHub repository genspark-ai/genoffice (11,115 stars, last pushed today), licensed Apache-2.0. It adds 27 tokens to every session and 878 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 2026-10-23.
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