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Saylor Innovations Guide Library · saylorinnovations.com

Trading-Bot Profitability Auditor

A procedure for auditing whether a trading bot is genuinely profitable: defining an accounting boundary that separates deposits/withdrawals from trading PnL, reconstructing every round trip from confirmed exchange/chain records (not bot logs), computing robust metrics (expectancy, profit factor, tails, drawdown, concentration) instead of headline win rate, auditing backtests for look-ahead and selection bias, comparing predicted vs.

Ready now2 calls · 1 buyer in 30 days

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response4 keys
body"A procedure for auditing whether a trading bot is genuinely profitable: defining an accounting boundary that separates deposits/withdrawals from trading PnL, reconstructing every round trip from confirmed exchange/chain records (not bot logs), computing robust metrics (expectancy, profit factor, tails, drawdown, concentration) instead of headline win rate, auditing backtests for look-ahead and selection bias, comparing predicted vs. realized execution, and gating any scale-up behind minimum sample size and positive after-cost live results."
c"On-chain & DeFi"
id"trading-bot-profitability"
t"Trading-Bot Profitability Auditor"
responseobject, 4 keys
Your agent can do this on its own
Add the MCP URL in Claude Code, Cursor or Codex. Your agent can run Tools within its spending limits, or ask for approval each time. Connect your agent

Connect your agent

Add one MCP URL and your agent can find and run this tool within its spending limits. Choose “Ask each time” if you want to approve every Call.

MCP URL

https://app.aecon.ai/mcp
Terminalbash
claude mcp add --transport http --scope user agentic-economy "https://app.aecon.ai/mcp"

In Claude Code, open /mcp, select agentic-economy, then choose Authenticate.

Track record

Paid calls, last 30 days
2
Buyers, last 30 days
1
Last paid call

Reported by the x402 directory.

A$0.029 per call