WyckoffTradingAgent: Open-source Wyckoff trading agent and AI stock screener for volume-price analysis, A-share screening, CLI

by YoungCan-Wang · MCP Server · ★ 768

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

Security audit verdict: SAFE · quality 67/100

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. Full audit →

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.

a-sharesai-trading-agenttrading-agentvolume-price-analysiswyckoff

Quick Facts

Stars768
Forks216
LanguagePython
CategoryMCP Server
LicenseAGPL-3.0
Quality Score67/100
Open Issues23
Last Updated2026-11-04
Created2026-01-12
Platformscli, mcp, python
Est. Tokens~16k

About WyckoffTradingAgent

WyckoffAgent — Open-Source Wyckoff Trading Agent Open-source Wyckoff trading agent and AI stock screener for volume-price analysis, A-share screening, portfolio diagnosis, CLI workflows, and MCP tools. A 股威科夫量价分析智能体 — 你说人话,他读盘面。 English 架构文档 WyckoffAgent is a research-oriented AI trading analysis agent.

Compatible Skills

These tools work well together with WyckoffTradingAgent for enhanced workflows:

  • ai-hedge-fund-crypto — semantic(0.46)+complementary+rare_topics+same_lang+similar_pop+shared_platform (70%)
  • LLM_trader — semantic(0.34)+complementary+rare_topics+same_lang+similar_pop+shared_platform (61%)
  • MarketBot — semantic(0.38)+complementary+same_lang+similar_pop+shared_platform (58%)
  • ClawForge — semantic(0.35)+complementary+same_lang+similar_pop+shared_platform (57%)
  • crypto-trading-arena — semantic(0.32)+complementary+same_lang+similar_pop+shared_platform (56%)

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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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