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 DigitalArchivst · Agent Tool · ★ 68
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is Open-Genealogy safe to install? View the security audit →
Open-Genealogy A toolkit of AI prompts and utilities for genealogical research, designed to follow the Genealogical Proof Standard. For genealogists at every level — from hobbyists exploring their first census record to credentialed professionals managing client work. What's Here Genealogy AI Starter Workspace Description: Project-folder starter kit for Codex, Claude Code, and Cowork Start Here: README.md Research Description: GPS-based research methodology Start Here: research-assistant-v8.5-compact.md GRA Skill Description: GPS research assistant for Claude Code (v8.5.3) Start Here: SKILL.md Transcription Description: Diplomatic transcription for handwritten documents Start Here: ocr-htr-v08.md [Image Analysis](image-anal
| Stars | 68 |
| Forks | 6 |
| Language | Python |
| Category | Agent Tool |
| Quality Score | 59.2326169336273/100 |
| Open Issues | 1 |
| Last Updated | 2026-07-12 |
| Created | 2024-02-17 |
| Platforms | claude-code, python |
| Est. Tokens | ~14k |
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Open-Genealogy is GPS-aligned AI prompts and Agent Skills for genealogical research (CC-BY-NC-SA-4.0). It is categorized as a Agent Tool with 68 GitHub stars.
Open-Genealogy is primarily written in Python. It covers topics such as agent-skills, claude-code, genealogy.
You can find installation instructions and usage details in the Open-Genealogy GitHub repository at github.com/DigitalArchivst/Open-Genealogy. The project has 68 stars and 6 forks, indicating an active community.
The top alternatives to Open-Genealogy on Agent Skills Hub include awesome-ai-agent-skills, agent-skills, semanticscholar-skill. 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: