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 dream-num · Codex Skill · ★ 64
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is skills safe to install? View the security audit →
Official Univer Skills for Workbook Automation Languages: English | 简体中文 Official Univer skills for workbook automation across Claude Code, Codex, and Cursor. This repository exposes canonical Univer product skills: : required entry skill for workbook tasks : path-first workbook work through : SaC workbook behavior plans under : plan review and pack-by-pack execution : assertion-backed SaC TDD and verify repair loops Highlights 🧮 A spreadsheet engine that lives in your terminal Drive real workbook semantics from the CLI: formulas, formatting, conditional formatting, charts, shapes, layout, import/export, and live preview. ✅ Commits for workbook state Agents mutate workbooks fast; humans review the rendered result; only verified changes become explicit, synca
| Stars | 64 |
| Forks | 2 |
| Language | JavaScript |
| Category | Codex Skill |
| License | Apache-2.0 |
| Quality Score | 70.4573912920822/100 |
| Open Issues | 5 |
| Last Updated | 2026-08-31 |
| Created | 2026-03-18 |
| Platforms | claude-code, cli, codex, node |
| Est. Tokens | ~14k |
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skills is Univer Skill enables AI tools to work directly with spreadsheets, Excel workbooks, and CSV files. Powered by Univer CLI, it brings Git-style diffs, reviews, approvals, and rollbacks to spreadsheet wor. It is categorized as a Codex Skill with 64 GitHub stars.
skills is primarily written in JavaScript. It covers topics such as agent-skills, ai-agent, claude-code.
You can find installation instructions and usage details in the skills GitHub repository at github.com/dream-num/skills. The project has 64 stars and 2 forks, indicating an active community.
skills is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to skills on Agent Skills Hub include awesome-ai-agent-skills, RivalSearchMCP, jdatamunch-mcp. 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: