by chaitanyya · Agent Tool · ★ 57
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
Featured in: Claude SEO Skills & SEO MCP Servers
git clone https://github.com/10xuio/lookout.gitTaken from the project's README on GitHub.
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.
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.
| Stars | 57 |
| Forks | 9 |
| Language | TypeScript |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 72/100 |
| Open Issues | 6 |
| Last Updated | 2025-06-11 |
| Created | 2025-05-25 |
| Platforms | claude-code, gemini, node |
| Est. Tokens | ~1054k |
# LookOut Monitor your brand's visibility across ChatGPT, Claude, Gemini and emerging AI search engines Overview LookOut is the first open-source platform designed to track and optimize your brand's ranking in AI-powered search results. As LLMs become the primary gateway for information discovery, your visibility in AI responses directly impacts your business growth.
These tools work well together with lookout for enhanced workflows:
Looking for a lookout alternative? If you're comparing lookout with other agent tool tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
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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: