globalpercent: 全球宏观预期概率面板 — Polymarket+Kalshi 双源 · 5端点 · 10模块 · 零鉴权

by simonlin1212 · Agent Tool · ★ 75

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 61/100

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.

ai-skillclaude-codefastapikalshimacropolymarketprediction-markets

Quick Facts

Stars75
Forks18
LanguagePython
CategoryAgent Tool
LicenseApache-2.0
Quality Score61/100
Last Updated2026-09-16
Created2026-06-05
Platformsclaude-code, python
Est. Tokens~15k

About globalpercent

简体中文 | English globalpercent 全球宏观预期概率面板 — 2 数据源 · 5 端点 · 10 模块 · 零鉴权零账户 架构 · 快速开始 · 端点 · 模块 · FAQ · 更新日志 架构(一口气讲完) 全球宏观预期概率面板 · 数据管道 │ Polymarket Gamma API ─┐ ├─► 每个源的 fetcher 把每条市场整形成同一套 schema Kalshi events API ────┘ (question, probyes, change24h, volume24h, source, …) │ 共享 taxonomy 把每条分到一个模块 (货币政策/宏观经济/地缘政治/政治选举/股指大宗/A

Compatible Skills

These tools work well together with globalpercent for enhanced workflows:

  • polymarket-mcp-server — semantic(0.45)+complementary+rare_topics+same_lang+similar_pop+shared_platform (75%)

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How this security grade is produced

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:

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