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 natolambert · Agent Tool · ★ 272
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is colloquium safe to install? View the security audit →
Colloquium Markdown-based slide creation tool for research talks. Git-friendly, AI-drivable, single-file HTML output. Docs · Core Example (RLHF Book) · PyPI Install Colloquium uses uv for fast, reliable Python package management. For development: Quick Start Create a markdown file: Build it: CLI Commands Frontmatter Refe
| Stars | 272 |
| Forks | 16 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 69.0860756309932/100 |
| Open Issues | 1 |
| Last Updated | 2026-09-08 |
| Created | 2026-02-22 |
| Platforms | python |
| Est. Tokens | ~18k |
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colloquium is A markdown native slides tool for academics building with agents.. It is categorized as a Agent Tool with 272 GitHub stars.
colloquium is primarily written in Python. It covers topics such as education, slides.
You can find installation instructions and usage details in the colloquium GitHub repository at github.com/natolambert/colloquium. The project has 272 stars and 16 forks, indicating an active community.
colloquium is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to colloquium on Agent Skills Hub include ppt-image-first, academic-pptx-skill, human-skill-tree. 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: