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@roman-rr/trading-skills

Crypto trading signals skill for Claude Code and Codex

This repo packages live crypto trading signals as a skill, plugin, and MCP server. Agents can ask for current signals, signal history, and performance stats, then use the returned trade setup and verification chain.

112 stars13 forksMakefileUpdated 4mo ago
Who it's for

Builders who want their agent to look up crypto trading signals inside Claude Code, Codex, Cursor, or Windsurf.

What it delivers

You can ask your agent for live, verified crypto signals instead of checking a separate trading dashboard.

What it does

Live signal fetch

Returns current bullish or bearish signals with entry, stop loss, take profit, leverage, and position size.

Transmission chain

Shows the data points and reasoning steps behind each signal.

MCP tools

Exposes `register`, `get_signals`, `get_signal`, `get_signal_history`, and `get_stats`.

Multi-agent support

Includes install paths for Claude Code, Codex, Cursor, and Windsurf, plus a Claude plugin.

Performance tracking

Tracks hit rate, ROI, profit factor, and verified outcomes against real prices.

How to get it

  1. 1Run
    /plugin install roman-rr/trading-skills
  2. 2Run
    npx skills add roman-rr/trading-skills
  3. 3Run
    claude mcp add trading-signals --transport http -- https://signals.x70.ai/mcp
  4. 4Run
    # Claude Code
    git clone https://github.com/roman-rr/trading-skills.git
    cp -r trading-skills/trading-signals ~/.claude/skills/trading-signals
    
    # OpenAI Codex CLI
    cp -r trading-skills/trading-signals ~/.codex/skills/trading-signals

README

Trading Signals

⭐ Enjoying free signals? Push STAR to keep them free — it directly supports higher accuracy and continued development!

Trading Signals for AI Agents

17 triggers. 44 algorithms. 3 AI experts. Every signal backed by causal reasoning and verified against real prices.

Live crypto trading signals for Claude Code, OpenAI Codex, Cursor, Windsurf & 30+ AI agents. Every signal includes entry, SL, TP, leverage, position size, and a full transmission chain showing exactly which data points led to the trade.

FREE during beta. More stars = more development time = better signals for everyone.

Install

Claude Code Plugin (recommended)

/plugin install roman-rr/trading-skills

npx (Claude Code, Codex, Cursor, Windsurf, etc.)

npx skills add roman-rr/trading-skills

MCP Server (Claude Desktop / Claude Code / Cursor)

claude mcp add trading-signals --transport http -- https://signals.x70.ai/mcp

Or add to Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json):

{
  "mcpServers": {
    "trading-signals": {
      "url": "https://signals.x70.ai/mcp"
    }
  }
}

Exposes 5 tools: register, get_signals, get_signal, get_signal_history, get_stats.

OpenAI Codex CLI

See agents/openai.yaml for agent configuration.

Manual

# Claude Code
git clone https://github.com/roman-rr/trading-skills.git
cp -r trading-skills/trading-signals ~/.claude/skills/trading-signals

# OpenAI Codex CLI
cp -r trading-skills/trading-signals ~/.codex/skills/trading-signals

Always Watching

17 Triggers. 6 Groups. Every Minute.

The sentinel continuously scans 50+ perpetual markets for anomalies across six orthogonal dimensions -- volume, positioning, price dynamics, cross-asset flows, microstructure, and options-derived signals. A signal fires only when multiple independent dimensions agree, filtering noise from genuine opportunities.

Multi-Expert Consensus

Three specialized AI experts analyze every opportunity independently -- each with a different lens on market structure. Signals require agreement; conflicting views are flagged or filtered. The system continuously learns which analytical approaches perform best per market condition.

Research-Grounded

44 Scientific Methods. 53 Academic Citations.

Every algorithm is grounded in peer-reviewed research from quantitative finance, statistics, and machine learning -- spanning position sizing, anomaly detection, technical analysis, market microstructure, and adaptive risk management.

What You Get

FeatureDescription
Live signalsBullish/bearish with full trade setup -- entry, SL, TP, leverage, position size
Transmission chains2-4 causal reasoning steps per signal with specific data points
50+ coinsDynamically selected from top volume, funding, and OI on Hyperliquid perps
Confidence score0-100 AI conviction level per signal
Auto-verificationEvery signal tracked against real prices -- TP/SL monitoring every minute
Paper trading P&LReal trades on a virtual account with optimal position sizing
Dynamic risk controlConfidence-based leverage caps, volatility-calibrated SL, automatic regime detection
Performance statsHit rate, cumulative ROI, profit factor, breakdown by direction/coin/model

Signal Preview

CoinDirConfEntrySLTPLevR/RType
BTCBull87%$68,450$67,200$71,8003x2.7momentum_shift
ETHBear82%$3,840$3,920$3,6802x2.0funding_anomaly
SOLBull79%$142.50$138.00$152.002x2.1volume_spike

API Endpoints

MethodPathAuthDescription
POST/api/skill/registerNoRegister & get API key
GET/api/skill/signalsAPI keyList signals (active/verified/all)
GET/api/skill/signals/:idAPI keySingle signal detail
GET/api/skill/statsAPI keyPerformance statistics

Example Prompts

Once installed, ask your AI agent:

  • "Get me the latest crypto trading signals"
  • "Show me today's highest-confidence BTC and ETH signals"
  • "What's the 30-day hit rate for these trading signals?"
  • "Build me a Python script that fetches crypto signals and alerts me on Telegram"
  • "Show me verified signals from the last week -- what hit TP?"

Pricing

FREE during beta -- no charges, no credit card.

Contributing

Issues, feature requests, and PRs are welcome. Please open an issue first to discuss changes.

License

Proprietary -- Free API during beta. Paid license required for commercial redistribution. See LICENSE.txt.

Files in the repo

Repository payload8 top-level entries
  • .claude-plugin
  • audits
  • trading-signals
  • .gitignore
  • CONTRIBUTING.md
  • LICENSE.txt
  • Makefile
  • README.md

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