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 Developers frequently forget to handle stale signals, leading to executions based on outdated market data or expired session states.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.

Use cases

• Designing human-in-the-loop triggers for crypto trading or arbitrage bots.
• Building approval flows for Telegram bots that manage server infrastructure.
• Creating safety gates for AI agents authorized to send payments or edit sensitive accounts.
• Establishing audit trails for automated publishing or social media workflows.

Known limitations

The skill focuses on logic and interface design rather than providing specific backend code for database persistence or API authentication. It assumes the developer handles the underlying state management and secure communications.