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 FTShare-Lab · Codex Skill · ★ 65
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is FTShare-skill safe to install? View the security audit →
中文 · English 让金融数据成为 AI 的可靠上下文。 FTShare Skill 让 Agent 根据自然语言问题，自动选择并调用基础金融数据与 FTShare 特色因子接口。 FTShare 正式版 · 获取 API Key · 快速开始 · 问题反馈 [!IMPORTANT] 本仓库提供一个可安装的父 Skill：。Agent 读取父 Skill 后，再从内部子 Skill 中选择对应数据接口，通过 执行请求并读取 JSON。所有请求都需要环境变量 。 FTShare Skill 是什么 FTShare Skill 是 FTShare 面向 Agent 运行时提供的金融数据接入方式。将 加载到 Claude Code、Codex、OpenClaw 等运行时后，用户可以直接用自然语言提出数据问题，由 Agent 完成接口选择、参数组织和结果读取。 <a href="https://ft
| Stars | 65 |
| Forks | 13 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 65.4421885278353/100 |
| Open Issues | 1 |
| Last Updated | 2026-09-27 |
| Created | 2026-06-28 |
| Platforms | claude-code, codex, python |
| Est. Tokens | ~14k |
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FTShare-skill is FTShare financial data Skill for AI agents｜通过自然语言路由基础金融数据与 FTShare 特色因子。. It is categorized as a Codex Skill with 65 GitHub stars.
FTShare-skill is primarily written in Python. It covers topics such as agent, agent-skills, agent-tools.
You can find installation instructions and usage details in the FTShare-skill GitHub repository at github.com/FTShare-Lab/FTShare-skill. The project has 65 stars and 13 forks, indicating an active community.
FTShare-skill is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to FTShare-skill on Agent Skills Hub include agent-skills, hhxg-top-hhxg-python, data-structure-protocol. 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: