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 jshph · Claude Skill · ★ 51
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is enzyme safe to install? View the security audit →
🧬 Enzyme Don't let your agent get lost in your knowledge base. Enzyme compiles 1,000+ documents into a concept graph in under 20 seconds. 8ms queries on device. Website · Docs · Discord · Getting Started Enzyme reads a knowledge base — markdown files, Obsidian vaults, Readwise exports, any text corpus — and compiles it into a concept graph. The graph captures the cross-cutting themes in your material as catalysts: pre-computed questions that an agent can search through instead of grepping through your files. No conversation history needed. No runtime reasoning. The expensive work happens once at init. After that, queries run locally in 8ms on an on-device embedding model. Install On macOS you can also use Home
| Stars | 51 |
| Forks | 1 |
| Language | TypeScript |
| Category | Claude Skill |
| Quality Score | 69.0495821755535/100 |
| Open Issues | 2 |
| Last Updated | 2026-08-04 |
| Created | 2025-01-22 |
| Platforms | claude-code, node |
| Est. Tokens | ~16k |
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enzyme is A compile step for knowledge bases. Gives your agent a concept graph of your content — under 20s to index, 8ms queries on device.. It is categorized as a Claude Skill with 51 GitHub stars.
enzyme is primarily written in TypeScript. It covers topics such as claude-code, knowledge-management, local-first.
You can find installation instructions and usage details in the enzyme GitHub repository at github.com/jshph/enzyme. The project has 51 stars and 1 forks, indicating an active community.
The top alternatives to enzyme on Agent Skills Hub include ChatCrystal, omega-memory, skill-conductor. 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: