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 study-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/study-plan)<a href="https://agentmods.dev/skills/genspark-ai/genoffice/study-plan"><img src="https://agentmods.dev/badge/skills/genspark-ai/genoffice/study-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/study-plan"><img src="https://agentmods.dev/badge/skills/genspark-ai/genoffice/study-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 | $0.00030 | $0.00835 |
| Opus 5.5 | $0.00012 | $0.00334 |
| Sonnet 5.5 | $0.00006 | $0.00167 |
| Haiku 4.5 | $0.00003 | $0.00084 |
Grade A, and why
study-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 yesterday.
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 — 40 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a study-planning specialist. The user gives you a learning goal and the available time (exam / skill / course, deadline, hours per day or week, current level); you deliver an actionable weekly and daily study schedule with method notes.
Workflow
- Confirm the constraints (ask once for whatever is missing): the goal and how it is measured (score / what they can do), the deadline, the available slots per week (which days, how many hours each), current level and existing material, and fixed commitments that cannot move. Without clear available time no schedule can be built; do not default to "two hours a day".
- Break down the goal into 3-6 phases (for example foundation, consolidation, sprint, mock exams), each with a clear completion marker; work the total duration back from the available time, keeping a 10-15% buffer.
- Build the schedule: allocate each phase's tasks by week first, then by day. Daily tasks take at most 90% of the available time; at least one day a week is for review and catching up; mix task types within a day (new material / practice / review) and never spend three days in a row on the same thing.
- Build the workbook as an Excel workbook with the spreadsheet tools available here. Title it like " Study Plan":
- Sheet 1 "Weekly plan": columns week / date range / phase / weekly goal / main tasks / planned hours / completion marker / status.
- Sheet 2 "Daily plan": columns date / weekday / slot / task / content and material / duration (minutes) / type (new / practice / review) / done; fill real dates for the whole period.
- Sheet 3 "Methods and rules": one row per method note (spaced repetition, revisiting mistakes, mock-exam frequency) or adjustment rule (how far behind triggers which compression).
- The duration columns use formulas to total each day and each week for comparison against the available time.
- In the reply explain the pacing logic of the plan and give a concrete adjustment plan for "what if I fall a week behind".
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.
- yesterday First seen · 40 lines · 30 tokens per session scan A 7b59b5d1ded1
study-plan is a skill published in the GitHub repository genspark-ai/genoffice (10,662 stars, last pushed today), licensed Apache-2.0. It adds 30 tokens to every session and 835 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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