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 lijigang · Claude Skill · ★ 211
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is ljg-explain-concept safe to install? View the security audit →
ljg-explain-concept A Claude Code skill that deconstructs any concept through 8 exploration dimensions, then compresses all insights into a single epiphany. What it does Given any concept (e.g. "entropy", "recursion", "freedom"), the skill performs: Preprocessing — clarify definition, identify core morphemes 8-Dimensional Exploration: Historical tracing Dialectical analysis Phenomenological reduction Linguistic deconstruction Mathematical formalization Existentialist examination Aesthetic dimension Meta-philosophical reflection Introspection — first-person view from inside the concept Epiphany Compression — The One formula + Feynman-style sentence + ASCII topology Output — writes org-mode file to Install Usage License MIT
| Stars | 211 |
| Forks | 13 |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 59.0204220209455/100 |
| Last Updated | 2026-02-09 |
| Created | 2026-02-09 |
| Platforms | claude-code |
| Est. Tokens | ~1k |
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ljg-explain-concept is Claude Code skill: 8-dimensional concept anatomist. Deconstructs any concept into epiphany.. It is categorized as a Claude Skill with 211 GitHub stars.
You can find installation instructions and usage details in the ljg-explain-concept GitHub repository at github.com/lijigang/ljg-explain-concept. The project has 211 stars and 13 forks, indicating an active community.
ljg-explain-concept is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to ljg-explain-concept on Agent Skills Hub include digital-marketing-pro, life-sciences, claude-ai-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.
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