by Innei · Agent Tool · ★ 111
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
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 | 111 |
| Forks | 10 |
| Language | TypeScript |
| Category | Agent Tool |
| Quality Score | 55/100 |
| Open Issues | 2 |
| Last Updated | 2026-07-07 |
| Created | 2026-06-24 |
| Platforms | node |
| Est. Tokens | ~13k |
Kansoku 装在你 Mac 上的能查账的 AI 看盘搭子——它说的每句话你都能查:每个结论挂着完整证据链,归档之后不许改口,事后按命中率记分。 Kansoku(観測) 是一个 macOS 桌面应用:行情从你自己的长桥账户拉,指标全部本地实算,AI 用你自己配置的模型盯盘、答疑、改研究稿,结论落成本地文件。数据和 key 都不出你的机器。 下载安装 去 Releases 下载最新 版本的 (macOS · Apple Silicon),拖进「应用程序」即可。应用内置 Sparkle 自动更新(EdDSA 签名 + 增量包),装一次就不用再回来手动下载。 前置依赖:本机安装并登录 longbridge CLI(行情和账户数据都走它)。应用当前没有付费开发者签名,首次打开需要右键 →「打开」,详见 。 首次启动有引导:连上长桥数据,再选一个 AI 接入方式(本机 codex 登录态 /...
These tools work well together with trade-skills for enhanced workflows:
Looking for a trade-skills alternative? If you're comparing trade-skills 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.
AI Stock Partner on Your Mac – Local Market Information, Multi-timeframe K-line, AI Intraday Comments and Foll
MCP server with persistent memory + FTS5 search for Claude Code conversation history. Index your ~/.claude/pro
Projx — A CLI tool for scaffolding production-grade projects. Pick your stack (FastAPI, Fastify, React, Flutte
The User Pays AI SDK
Comprehensive UI/UX and Backend component design skills for AI-assisted development with Claude
Explore other popular agent tool tools:
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: