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 ivangfalco · Claude Skill · ★ 227
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is ads-skills safe to install? View the security audit →
Ivan Falco's Ads Skills for Claude Code Turn Claude Code into your B2B advertising co-pilot. 40+ strategy files, 39 API scripts, and battle-tested frameworks for LinkedIn, Meta, and Google Ads - built from managing $200K+/month in B2B ad spend across 12+ accounts. Clone this repo, open Claude Code, and ask it anything about your ads. It knows the strategy, it can pull your data, and it can manage your campaigns. Built by Ivan Falco - Head of Growth at ColdIQ and Head of the Ads/ABM agency. Building AI-native advertising systems that make one person operate like five. If you need help with ads operations, growth operations, or scaling your B2B campaigns - DM Ivan directly: LinkedIn What's Inside 4 Skills 40+ Knowledge Base Files Ads Foundations (10
| Stars | 227 |
| Forks | 76 |
| Language | Python |
| Category | Claude Skill |
| Quality Score | 65.9263498321459/100 |
| Last Updated | 2026-07-15 |
| Created | 2026-04-07 |
| Platforms | claude-code, python |
| Est. Tokens | ~15k |
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ads-skills is Ivan Falco's Ads Skills for Claude Code - LinkedIn, Meta, and Google Ads. 40+ strategy files, 39 API scripts. Built by the Head of Growth at ColdIQ.. It is categorized as a Claude Skill with 227 GitHub stars.
ads-skills is primarily written in Python.
You can find installation instructions and usage details in the ads-skills GitHub repository at github.com/ivangfalco/ads-skills. The project has 227 stars and 76 forks, indicating an active community.
The top alternatives to ads-skills on Agent Skills Hub include digital-marketing-pro, life-sciences, claude-ai-mcp. 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: