No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by alchaincyf · AI Tool · ★ 409
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is huashu-excel safe to install? View the security audit →
huashu-excel 「给我一份Excel，给你交一份专业报告。」 一个真正懂数据分析的skill。 数据分析与 Excel 全流程 · 体检 → 清洗 → 对齐 → 分析 → 对账 → 交付 「这个数你怎么算的？」 —— 每个交过数字的人都被这么问过。 答不上来通常不是记性差，是那个数从一开始就没法被追溯。 而 AI 算错的时候不会报错。 你写代码，错了会抛异常； 你做数据分析，错了什么都不会发生。一个 +161% 的错误， 交付出去的时候和正确答案长得完全一样。 丢一份乱七八糟的 Excel 给它——标题占了第一行、表头两级、地区列用合并单元格、 金额带千分位、中间夹着「华东小计」、尾巴三行是「合计/占比/同比」。 主流做法算这份表的月度总额，比真值高 161%，零报错、零 NaN、零警告。 这个 skill 存在的全部理由，就是让那句反问能被答上来。它先读原始单元格再动 pandas，把表里的「合计」行当成免费的校验和拿来对账，交付前跑一遍 master check——不通过就不给你数字。 跨 agent 通用——Claude Code、Cursor、Codex、OpenClaw、Hermes 都能装。 看效果对比 · 装上就能用 · 八步流程 · 五个不一样 · 图表 · 报告 看效果对比 同一份表，同一个问题：「1 月总销售额是多少？」 主流做法： 发现表头位置不对就加 ，发现数字读不出来就清掉千分位。看起来已经挺周全了。 错在三个地方，没有任何一处会报错： 行的 15,368,317 被当成了一家门店 的 6,157,150 又被当成一家门店 有一行是粘贴事故造成的完全重复，算了两次 huashu-excel 体检阶段就把问题全列出来，一个都不猜： 【必须先处理】 表头不在第 1 行：第 1, 2 行是标题/说明，真表头在第
| Stars | 409 |
| Forks | 66 |
| Language | Python |
| Category | AI Tool |
| License | MIT |
| Quality Score | 59.306702364723/100 |
| Open Issues | 2 |
| Last Updated | 2026-09-15 |
| Created | 2026-08-23 |
| Platforms | python |
| Est. Tokens | ~15k |
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huashu-excel is 数据分析与 Excel 全流程 skill：体检脏表、清洗、对齐需求、分析、对账、交付。让 AI 算出来的数字经得起追问。跨 agent 通用，依赖仅 openpyxl。. It is categorized as a AI Tool with 409 GitHub stars.
huashu-excel is primarily written in Python.
You can find installation instructions and usage details in the huashu-excel GitHub repository at github.com/alchaincyf/huashu-excel. The project has 409 stars and 66 forks, indicating an active community.
huashu-excel is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to huashu-excel on Agent Skills Hub include EDRSilencer, perf-map-agent, shaping-skills. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: