Approval Flow Design for Risky AI & Web3 Actions

The problem

Automated agents often perform high-risk actions like trading, payments, or public posting without sufficient safety checks. Developers frequently forget to handle stale signals, leading to executions based on outdated market data or expired session states.

What it does

• Classifies action risks from low to high based on blast radius and reversibility.
• Defines specific approval objects including action type, scope, failure modes, and expiry.
• Implements freshness checks to validate signals immediately before execution.
• Designs user decision surfaces for Telegram and chat interfaces with clear risk notes.
• Standardizes audit logging for proposed, approved, and executed states.

Why this beats prompting it yourself

This skill enforces a systematic safety architecture that generic prompts miss, such as the "stale approval rule" and dynamic parameter recalculation. It ensures your agent handles the critical gap between user approval and final execution, preventing financial or operational errors due to timing drift. The rules come out of a live trading framework where no order reaches an exchange without an explicit Approve in Telegram, and price, margin, venue status and position limits are re-read at the moment of the tap rather than trusted from the original card. That system is written up in full — workflow, guardrails and what the testing disproved — at milaarty.com/cases/human-approved-trading