by mozanunal · LLM Plugin · ★ 95
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
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.
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 | 95 |
| Forks | 4 |
| Language | Python |
| Category | LLM Plugin |
| License | Apache-2.0 |
| Quality Score | 71/100 |
| Last Updated | 2025-06-04 |
| Created | 2025-06-04 |
| Platforms | cli, python |
| Est. Tokens | ~186k |
llm-tools-kiwix Expose offline Kiwix ZIM archives (like Wikipedia, Stack Exchange, DevDocs) to Large Language Models (LLMs) via the LLM CLI tool and Python library. This plugin allows LLMs to search and read content from your local ZIM files. Key Features Automatic ZIM File Discovery: Finds files in the current working directory and in the directory specified by the environment variable.
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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: