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 hanityx · Codex Skill · ★ 57
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is threadlens safe to install? View the security audit →
ThreadLens 한국어 · 中文 · 日本語 · Español · Português You remember the conversation — you just don't know if it was Codex, Claude, Gemini, or Copilot. ThreadLens lets you search, open and review conversations, analyze impact, back up, and safely clean up your local AI sessions from one place. No cloud, no account — jus
| Stars | 57 |
| Forks | 7 |
| Language | TypeScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 63.0850506065423/100 |
| Open Issues | 1 |
| Last Updated | 2026-05-20 |
| Created | 2026-02-15 |
| Platforms | claude-code, cli, codex, gemini, node |
| Est. Tokens | ~13627k |
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threadlens is Search, review, back up, and safely clean up local sessions from Codex, Claude, Gemini, and Copilot.. It is categorized as a Codex Skill with 57 GitHub stars.
threadlens is primarily written in TypeScript. It covers topics such as chat-history, claude-code, codex.
You can find installation instructions and usage details in the threadlens GitHub repository at github.com/hanityx/threadlens. The project has 57 stars and 7 forks, indicating an active community.
threadlens is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to threadlens on Agent Skills Hub include agf, sage, wechat-cli. 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: