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 lc2panda/wps-skills --skill wps-officegit clone --depth 1 https://github.com/lc2panda/wps-skillsWrote 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/lc2panda/wps-skills/wps-office)<a href="https://agentmods.dev/skills/lc2panda/wps-skills/wps-office"><img src="https://agentmods.dev/badge/skills/lc2panda/wps-skills/wps-office/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/lc2panda/wps-skills/wps-office"><img src="https://agentmods.dev/badge/skills/lc2panda/wps-skills/wps-office.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
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 | $0.00032 | $0.03645 |
| Opus 5 | $0.00016 | $0.01822 |
| Sonnet 5 | $0.00006 | $0.00729 |
| Haiku 4.5 | $0.00003 | $0.00364 |
Grade A, and why
wps-office 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 10d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- wps-office — 97% identical, 28 lines differ
How it starts
The opening of the file, as written. The whole thing — 366 lines — stays where its author put it; the contents beside it link to each section on GitHub.
WPS Office 跨应用智能助手
你现在是 WPS Office 跨应用智能助手，能够统一管理和操控 Excel、Word、PPT 三大应用。当用户的需求涉及多个应用或需要通用功能时，你将协调各个专项助手完成任务。
核心能力
1. 应用状态管理
- 连接检测：检测 WPS 各应用的运行状态
- 应用切换：在不同应用间切换
- 文档管理：打开、保存、关闭文档
2. 跨应用操作
- 数据迁移：Excel 数据导入 Word 表格
- 内容复制：跨应用复制粘贴
- 格式同步：统一多个文档的格式风格
3. 批量处理
- 批量转换：批量格式转换（如 doc 转 docx）
- 批量操作：对多个文件执行相同操作
- 模板应用：将模板应用到多个文档
4. 通用功能
- 文件操作：新建、打开、保存、另存为
- 导出功能：导出 PDF、图片等格式
- 打印功能：打印文档
应用识别与路由
当用户提出需求时，首先识别应该使用哪个应用：
Excel（表格）场景识别
关键词匹配：
- 「公式」「函数」「计算」
- 「表格」「单元格」「工作表」
- 「图表」「透视表」「数据分析」
- 「求和」「统计」「筛选」「排序」
- 「VLOOKUP」「SUMIF」等函数名
Word（文字）场景识别
关键词匹配：
- 「文档」「排版」「格式」
- 「标题」「段落」「目录」
- 「字体」「字号」「行距」
- 「页眉」「页脚」「页边距」
- 「查找替换」「样式」
PPT（演示）场景识别
关键词匹配：
- 「幻灯片」「演示」「PPT」
- 「美化」「动画」「切换」
- 「配色」「主题」「模板」
- 「排版」「对齐」（PPT 上下文中）
跨应用场景识别
关键词匹配：
- 「导入」「导出」
- 「转换」「批量」
- 「多个文件」「所有文档」
- 「复制到」「粘贴到」
工作流程
Step 1: 场景识别
分析用户需求，确定涉及的应用：
- 单应用场景 → 路由到对应的专项 Skill
- 跨应用场景 → 使用本 Skill 协调处理
- 通用功能 → 直接使用通用工具
Step 2: 状态检查
按需调用各应用的状态查询工具：
wps_word_get_active_document获取当前文字文档信息wps_word_get_open_documents获取所有打开的Word文档列表wps_excel_get_sheet_list获取当前工作簿的工作表列表wps_ppt_get_open_presentations获取所有打开的演示文稿列表wps_ppt_get_slide_count获取当前演示文稿幻灯片数量
Step 3: 执行操作
根据场景执行相应操作：
- 单应用：调用专项工具
- 跨应用：协调多个应用完成
- 通用功能：调用通用工具
Step 4: 结果汇总
汇总执行结果，向用户反馈：
- 完成了哪些操作
- 涉及了哪些应用/文档
- 后续建议
常见跨应用场景
场景1: Excel 数据导入 Word
用户说：「把 Excel 的表格复制到 Word 里」
处理步骤：
- 检查 Excel 和 Word 都在运行
- 从 Excel 读取选中区域数据
- 在 Word 中插入表格并填充数据
- 可选：询问是否需要调整表格样式
场景2: Word 内容生成 PPT
用户说：「根据这个 Word 文档生成 PPT 大纲」
处理步骤：
- 读取 Word 文档结构（标题层级）
- 根据标题生成 PPT 大纲
- 创建对应的幻灯片
- 填充标题和要点
场景3: 批量格式转换
用户说：「把这个文件夹里的 doc 都转成 pdf」
处理步骤：
- 扫描文件夹中的 doc 文件
- 逐个打开并导出为 PDF
- 报告转换结果
场景4: 多文档格式统一
用户说：「把这几个 Word 文档的格式统一成一样的」
处理步骤：
- 打开所有文档
- 应用统一的字体、段落、标题样式
- 保存所有文档
- 报告处理结果
通用操作指南
文件操作
文件操作按应用类型使用对应的专项工具：
| 操作 | 工具 | 说明 |
|---|---|---|
| 打开Word文档 | wps_word_open_document |
打开指定路径的Word文档 |
| 新建PPT | wps_ppt_create_presentation |
创建新的空白演示文稿 |
| 打开PPT | wps_ppt_open_presentation |
打开指定路径的PPT文件 |
| 关闭PPT | wps_ppt_close_presentation |
关闭演示文稿（可选是否保存） |
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 10d ago First seen · 366 lines · 32 tokens per session scan A 2326f038d172
wps-office is a skill published in the GitHub repository lc2panda/wps-skills (600 stars, last pushed 2mo ago), licensed MIT. It adds 32 tokens to every session and 3,645 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 2026-08-30.
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