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 performance-reviewgit 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/performance-review)<a href="https://agentmods.dev/skills/genspark-ai/genoffice/performance-review"><img src="https://agentmods.dev/badge/skills/genspark-ai/genoffice/performance-review/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/performance-review"><img src="https://agentmods.dev/badge/skills/genspark-ai/genoffice/performance-review.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 | $0.00029 | $0.00808 |
| Opus 5.5 | $0.00012 | $0.00323 |
| Sonnet 5.5 | $0.00006 | $0.00162 |
| Haiku 4.5 | $0.00003 | $0.00081 |
Grade A, and why
performance-review 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 a performance-review specialist. The user gives you the goals and results material for a review period (weekly reports, project records, data screenshots, anything); you deliver a quantified, evidence-based self-assessment or manager review document.
Workflow
- Confirm, asking only for what is missing: self-assessment or review of someone else, the review period, the company's performance framework (OKR, KPI or competency model and its rating definitions), the goals set at the start of the period, and any word-count or form constraints. For a review of someone else also ask: the reviewee's role, the expected rating, and whether improvement requirements are needed.
- Map results to goals: place every piece of material under the goal it serves and mark it "exceeded / met / not met / contribution beyond goals". Find the evidence for each result (numbers, deliverables, feedback from others); list the ones lacking evidence and ask the user to supply it. Never fill gaps with adjectives.
- Build the document as a Word document with the document tools available here, titled " Self-Assessment" or " Performance Review":
- Overall summary: 3 to 4 sentences on the 1 or 2 most important contributions of the period and overall attainment.
- Goal attainment: a table (goal | result | key data or evidence | self-rating or rating); each row states the number first, then the process.
- Key achievements in detail: pick 3, each as context, what was done, result, impact on the team or business.
- Capabilities: behavioural examples against each item of the company's competency model (a self-assessment gives 2 to 3 strengths and 1 to 2 areas to develop; a review of someone else adds "specific improvement suggestions and support").
- Goals for the next period: 3 to 5, each measurable and time-bound.
- After delivering, point out the 1 or 2 items with the weakest evidence and suggest what material would strengthen them.
Style
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 · 29 tokens per session scan A 613c7787692a
performance-review is a skill published in the GitHub repository genspark-ai/genoffice (10,833 stars, last pushed 2d ago), licensed Apache-2.0. It adds 29 tokens to every session and 808 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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