by stvlynn · Agent Tool · ★ 121
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
npx --yes skills add stvlynn/dingtalk-wukong-skills --skill='*' --full-depth
npx --yes skills add stvlynn/dingtalk-wukong-skills --skill='*' --full-depth -gTaken from the project's README on GitHub. Check the security audit before running it.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 121 |
| Forks | 21 |
| Language | Python |
| Category | Agent Tool |
| Quality Score | 62/100 |
| Open Issues | 2 |
| Last Updated | 2026-03-19 |
| Created | 2026-03-19 |
| Platforms | python |
| Est. Tokens | ~14k |
DingTalk Wukong Skills A curated collection of Agent Skills for DingTalk ecosystem and professional document processing. English | 简体中文 [!IMPORTANT] This project is a collection of skills extracted from Wukong v0.9.2 (arm64). These skills are optimized for Agent environments like cli-gemini, claude-code, and codex.
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Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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: