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 datadrivenconstruction · Claude Skill · ★ 282
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is DDC_Skills_for_AI_Agents_in_Construction safe to install? View the security audit →
DDC Skills Collection for AI Coding Assistants AI Tools for Construction Company Automation Works with any AI coding assistant: <img src="https://img.shields.io/
| Stars | 282 |
| Forks | 74 |
| Language | Python |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 71.3912036004924/100 |
| Open Issues | 1 |
| Last Updated | 2026-08-22 |
| Created | 2026-01-24 |
| Platforms | claude-code, python |
| Est. Tokens | ~17k |
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DDC_Skills_for_AI_Agents_in_Construction is 221 AI skills for construction: BIM analysis, cost estimation, scheduling, document control, and automation with Claude Code. It is categorized as a Claude Skill with 282 GitHub stars.
DDC_Skills_for_AI_Agents_in_Construction is primarily written in Python. It covers topics such as aec-industry, ai-agents, automation.
You can find installation instructions and usage details in the DDC_Skills_for_AI_Agents_in_Construction GitHub repository at github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction. The project has 282 stars and 74 forks, indicating an active community.
DDC_Skills_for_AI_Agents_in_Construction is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to DDC_Skills_for_AI_Agents_in_Construction on Agent Skills Hub include ios-simulator-skill, claude-skills, claude-skills-marketplace. 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: