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 anysearch-ai · Codex Skill · ★ 6.2k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is anysearch-skill safe to install? View the security audit →
AnySearch Skill Unified real-time search engine skill for AI agents. Supports general web search, vertical domain search, parallel batch search, and full-page content extraction. Download & Install For AI Agents If your agent platform supports a skill marketplace/store, search for anysearch and install from there. Otherwise, download and install manually: is a useful shared install location when multiple AI tools read from the same skill directory, including Codex, Cursor, and OpenClaw personal agent skills. For Humans Download the zip: https://github.com/anysearch-ai/anysearch-skill/archive/refs/heads/main.zip 2.
| Stars | 6,214 |
| Forks | 358 |
| Language | Python |
| Category | Codex Skill |
| License | Apache-2.0 |
| Quality Score | 74.4576961213313/100 |
| Open Issues | 1 |
| Last Updated | 2026-09-17 |
| Created | 2026-04-30 |
| Platforms | browser, python |
| Est. Tokens | ~12k |
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anysearch-skill is Unified real-time search engine skill for AI agents. Supports general web search, vertical domain search, parallel batch search, and full-page content extraction.. It is categorized as a Codex Skill with 6.2k GitHub stars.
anysearch-skill is primarily written in Python. It covers topics such as anysearch, hermes, openclaw.
You can find installation instructions and usage details in the anysearch-skill GitHub repository at github.com/anysearch-ai/anysearch-skill. The project has 6.2k stars and 358 forks, indicating an active community.
anysearch-skill is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to anysearch-skill on Agent Skills Hub include MemOS, AI-Infra-Guard, context-mode. 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: