PV-PP Agent Auditor

A Productive Value-Productive Power (PV-PP) based audit tool for reviewing AI agents before they are expanded, automated, or relied on.

The PV-PP Agent Auditor is a custom GPT built on the Productive Value-Productive Power (PV-PP) framework. It helps users examine an AI agent environment by looking at what the agent is supposed to do, what information it uses, what tools and permissions it has, and where its apparent capability may exceed what the surrounding system can safely support.

The auditor does not certify an agent as safe. It helps surface hidden risks involving tools, memory, permissions, stale information, feedback loops, escalation paths, recovery structure, and false confidence before the agent is expanded or placed into heavier use.

A sample audit report is available so users can review the kind of output the auditor produces before running it. The sample shows how the auditor identifies hidden assumptions, weak control points, false-success risks, authority-boundary problems, and agent-governance gaps.

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Use case: First-pass review of an AI agent, workflow, automation, or tool-using system before it is expanded, delegated more authority, or relied on in a higher-risk setting.

What It Audits

  • Agent purpose, scope, and operating environment
  • Tools, APIs, permissions, and execution authority
  • Memory, stored context, retrieval assumptions, and stale-state risks
  • Input quality, missing information, and false-confidence points
  • Decision surfaces where the agent may act from an incomplete model
  • Feedback loops, monitoring, escalation paths, and recovery options
  • Failure modes involving overreach, unsafe automation, or hidden dependency

Why It Matters

Agent systems can look capable because they produce fluent answers or trigger tools. That does not mean they understand their operating environment, know when information is stale, or have enough feedback to recover from error.

The auditor focuses on the gap between apparent capability and supported capability: where an agent may seem ready to act, but the surrounding workflow, permissions, evidence, oversight, or recovery structure does not actually support safe operation.