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Skills SendTradeSignal

A specialized tool for sending quantitative trading signals to the FMZ platform via HTTP API.

install
source · Clone the upstream repo
git clone https://github.com/openclaw/skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/13290186019/send-signal" ~/.claude/skills/openclaw-skills-sendtradesignal && rm -rf "$T"
OpenClaw · Install into ~/.openclaw/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/13290186019/send-signal" ~/.openclaw/skills/openclaw-skills-sendtradesignal && rm -rf "$T"
manifest: skills/13290186019/send-signal/SKILL.md
tags
#trading#api#fmz#quantitative#automation#http
source content

SendTradeSignal (FMZ Connector)

Overview

This skill serves as a bridge between the OpenClaw AI agent and the FMZ Quantum Trading Platform. It enables the AI to execute trade decisions (Buy/Sell/Wait) programmatically by sending structured JSON signals to a specific robot instance running on FMZ.

Features

  • Real-time Signal Transmission: Sends trading commands instantly upon AI decision.
  • Secure Communication: Uses a user-defined UUID to verify the source of the signal, preventing unauthorized access.
  • Structured Data: Transmits comprehensive trade details including action type, target symbol (e.g., BTC_USDT), reference price, and reasoning.
  • HTTP/HTTPS Support: Compatible with standard web protocols for broad compatibility.

Usage

The AI should invoke this tool when a market analysis concludes with a definitive trading action.

Parameters

ParameterTypeDescription
action
stringThe specific trading action to take. Accepted values: 
buy
, 
sell
, 
wait
, 
close
.
symbol
stringThe trading pair symbol, formatted as 
BASE_QUOTE
(e.g., 
BTC_USDT
, 
ETH_USDT
).
price
floatThe current market price or limit price for the order.
reason
stringA brief explanation of why this trade decision was made (e.g., "RSI overbought", "Breaking support").

Example

When the AI detects a buying opportunity for Bitcoin at 65000 USDT due to a positive trend:

handler(
    action="buy",
    symbol="BTC_USDT",
    price=65000.0,
    reason="MACD golden cross detected on 4H chart."
)