reviewing-agent-prompting

To audit and improve prompts for coding agents, you apply state-machine structure to enforce clear entry conditions, actions, exits, and transitions. This reduces hallucinations by imposing strict phase gates and explicit output formats.

State-machine framing for agent prompt review structures prompts into explicit states with entry conditions, defined actions, exit criteria, and transitions. This enforces clear phase gates and escalation triggers to improve reliability.

You structure system prompts by applying a structured review framework that defines phase gates, explicit output requirements, escalation triggers, and anti-patterns. This ensures first-action clarity and reliable state transitions.

Yes, the prompt audit framework is applicable to system prompts, task delegation prompts, and instruction prompts across software engineering workflows. It evaluates and refines all these prompt types using state-machine logic.

The best way to evaluate prompt anti-patterns and escalation triggers is through a structured review framework. It audits prompts against defined anti-patterns and ensures escalation triggers are explicitly stated for first-action clarity.