Introducing Agent Audit β The Economic Layer for AI Agents.
AI agents donβt just run workflows, they operate hidden economies of calls, retries, loops, and decisions that quietly accumulate cost.
Agent Audit acts as the system of record for this economy, showing which agents are pulling their weight, where spend is wasted, and where opportunities for savings may exist, all in real dollar terms instead of tokens.
With one command, you can run a local audit and get your first signal in under sixty seconds.
Agent Audit analyzes your OpenClaw or Hermes data directly on your machine, requires no account, and keeps everything local unless you choose to push results.
Agent Audit goes beyond simple usage metrics by turning runtime data into economic visibility. It identifies confirmed waste like retries and loops, along with savings opportunities such as context bloat, idle workflows, and inefficient model usage.
Every audit provides a clear view of spend, waste, opportunity impact, waste rates, and trends over time, helping teams understand where costs are coming from and how their agent systems are performing economically.
Run everything locally or push results to a hosted workspace for shared visibility and historical tracking.
Today, Agent Audit brings transparency to agent economics.
Tomorrow, it evolves toward economic governance with budget guardrails and policy controls.
Because the future of AI agents isnβt just intelligence, itβs economics.