Keywordo-kun-AI-SEO-Agent-n8n-Workflow: This workflow uses n8n, Gemini, and DataForSEO to create an AI agent that spies on your competitors, finds

by AgriciDaniel · Agent Tool · ★ 81

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 59/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

aiautomationmarketing-automationn8nopen-sourceworkflow

Quick Facts

Stars81
Forks25
CategoryAgent Tool
LicenseMIT
Quality Score59/100
Open Issues1
Last Updated2026-04-10
Created2025-11-01
Platformsgemini
Est. Tokens~16k

About Keywordo-kun-AI-SEO-Agent-n8n-Workflow

📺 Full Video Walkthrough & Setup Guide Watch the full demo and setup guide on YouTube: Youtube Video Chat interface example: https://articollov2.vercel.app This repository contains the complete workflow for Keywordo-kun, an AI agent specialized in competitor analysis, keyword research, and automated SEO content creation.

Compatible Skills

These tools work well together with Keywordo-kun-AI-SEO-Agent-n8n-Workflow for enhanced workflows:

  • cobrew — semantic(0.17)+complementary+shared_fw(vercel)+similar_pop+shared_platform (54%)
  • n8n-workflows-maker — semantic(0.42)+complementary+similar_pop (50%)
  • agent-fleet-o — semantic(0.22)+complementary+similar_pop+shared_platform (48%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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:

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