agent-native-audit

Agent-native architecture structures a codebase around 8 core principles like action parity and context injection. An audit analyzes adherence to these principles, generating scored reports with specific recommendations for improvement.

You can run a full audit of agent-native architecture principles across your project. The Skill evaluates adherence to principles like CRUD completeness and UI integration, then generates scored reports with actionable recommendations.

An agent-native architecture review evaluates 8 core principles: action parity, tools as primitives, context injection, shared workspace, CRUD completeness, UI integration, capability discovery, and prompt-native features.

Yes, an agent-native audit provides quantitative scores for each of the 8 core principles and an overall assessment. This helps development teams measure their AI agent implementation against best practices.

The best way to identify capability discovery gaps is a principle-based audit. It lists specific missing elements and provides detailed recommendations for improving your agent-native architecture.

Yes, the audit analyzes adherence to shared workspace and context injection principles. It will highlight these as specific gaps in the generated report and provide recommendations for implementing them.