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 Signet-AI · Codex Skill · ★ 289
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is signetai safe to install? View the security audit →
Signet AI Own your agent's context. 97.6% average LongMemEval answer accuracy Local-first context · source-backed recall · repairable memory · portable across agents Quick start · Why Signet · Benchmarks · Docs · Discord Models change. Providers change. Agent shells change. Your context should not. Your agents are starting to remember projects, users, decisions, documents, conversations, p
| Stars | 289 |
| Forks | 41 |
| Language | TypeScript |
| Category | Codex Skill |
| Quality Score | 64.8707812376025/100 |
| Open Issues | 54 |
| Last Updated | 2026-09-23 |
| Created | 2026-02-11 |
| Platforms | claude-code, codex, node |
| Est. Tokens | ~19k |
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signetai is Sync and store memories, shared identity files (AGENTS.md, CLAUDE.md), session transcripts, institutional knowledge, and secrets between all of your favorite harnesses and models.. It is categorized as a Codex Skill with 289 GitHub stars.
signetai is primarily written in TypeScript. It covers topics such as agent-memory, ai-memory, claude-code.
You can find installation instructions and usage details in the signetai GitHub repository at github.com/Signet-AI/signetai. The project has 289 stars and 41 forks, indicating an active community.
The top alternatives to signetai on Agent Skills Hub include memorix, bitrouter, autocontext. 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: