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 hoangsonww · Agent Tool · ★ 82
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is Agentic-AI-Pipeline safe to install? View the security audit →
Agentic Multi‑Stage Bot - A Research & Outreach Agent 🤖 [
| Stars | 82 |
| Forks | 20 |
| Language | Python |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 64.6292903528186/100 |
| Open Issues | 13 |
| Last Updated | 2026-07-20 |
| Created | 2025-07-27 |
| Platforms | aws, docker, python |
| Est. Tokens | ~77k |
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Agentic-AI-Pipeline is 🦾 A production‑ready research outreach AI agent that plans, discovers, reasons, uses tools, auto‑builds cited briefings, and drafts tailored emails with tool‑chaining, memory, tests, and turnkey Dock. It is categorized as a Agent Tool with 82 GitHub stars.
Agentic-AI-Pipeline is primarily written in Python. It covers topics such as agent, agentic-ai, anthropic.
You can find installation instructions and usage details in the Agentic-AI-Pipeline GitHub repository at github.com/hoangsonww/Agentic-AI-Pipeline. The project has 82 stars and 20 forks, indicating an active community.
Agentic-AI-Pipeline is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to Agentic-AI-Pipeline on Agent Skills Hub include oreilly-ai-agents, eval-view, pydantic-ai-backend. 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: