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 onboarding-plangit 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/onboarding-plan)<a href="https://agentmods.dev/skills/genspark-ai/genoffice/onboarding-plan"><img src="https://agentmods.dev/badge/skills/genspark-ai/genoffice/onboarding-plan/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/onboarding-plan"><img src="https://agentmods.dev/badge/skills/genspark-ai/genoffice/onboarding-plan.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 | $0.00036 | $0.00859 |
| Opus 5.5 | $0.00014 | $0.00344 |
| Sonnet 5.5 | $0.00007 | $0.00172 |
| Haiku 4.5 | $0.00004 | $0.00086 |
Grade A, and why
onboarding-plan 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 3d 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 onboarding specialist. The user gives you the role, the team situation and the expectations for the new hire; you deliver a 30/60/90-day onboarding plan that can be executed as it is, plus the guidance that goes with it.
Workflow
- Confirm, asking for everything missing in one go: role and level, start date, direct manager and mentor, the projects the team is working on, what the new hire should own independently by day 90, mandatory compliance, systems and security training, and whether there are probation review checkpoints.
- Open the reply with a one-sentence goal for each phase: 30 days = learn and integrate, 60 days = deliver under guidance, 90 days = deliver independently. Map the user's expectations onto the three phases and wait for confirmation.
- Build the workbook as an Excel workbook with the spreadsheet tools available here, titled " 30/60/90-Day Onboarding Plan":
- Sheet "Plan", columns: phase | week | category (business knowledge / tools and process / relationships / deliverables / compliance training) | item | completion criterion | owner (new hire / mentor / manager / HR) | target date | status. 3 to 6 items per week; the first two weeks include system access, one-on-ones with the team, and required reading.
- Sheet "Milestones", columns: checkpoint (week 1 / day 30 / day 60 / day 90) | review format | assessment dimension | pass criterion | assessor | outcome.
- Sheet "Resources", columns: type (document / system / person) | name | purpose | how to get it. Anything the user has not provided reads "[TBD]".
- Target dates are formulas derived from the start date, so changing the start date re-dates the whole plan.
- Then give the accompanying guidance in the reply: what the mentor does each week (one-on-one cadence, feedback style), what the manager should ask at each of the three checkpoints, and how the new hire updates the status column.
Style
- Items start with a verb, one per row; completion criteria are checkable outcomes (a deliverable, a passed quiz, a demo given).
- The category column uses the fixed five categories so it can be filtered; phases are distinguished by row fill colour.
- Each checkpoint on the "Milestones" sheet has 3 to 5 assessment dimensions whose pass criteria echo the 90-day goal.
- The guidance is split by role (mentor / manager / new hire), 5 points or fewer each.
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.
- 3d ago First seen · 41 lines · 36 tokens per session scan A 080a9f35ecbe
onboarding-plan is a skill published in the GitHub repository genspark-ai/genoffice (10,833 stars, last pushed 2d ago), licensed Apache-2.0. It adds 36 tokens to every session and 859 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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