Agent-Native Architecture Reviewer

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Audits application code and design to ensure AI agents have full functional parity and context awareness alongside human users.

The Agent-Native Architecture Reviewer is a specialized diagnostic tool designed to transition applications into 'agent-native' environments where AI agents are first-class citizens. It systematically reviews codebases to ensure that every action available to a human user in the UI has a corresponding tool for an agent, and that agents have access to the same runtime context as users. By identifying anti-patterns like context starvation and sandbox isolation, this skill helps developers build robust systems where agents and humans can collaborate seamlessly in a shared workspace using flexible, primitive-based tools.

Key Features

01Anti-Pattern Detection for identifying 'Orphan Features' and 'Silent Actions'
02Context Parity Validation to verify agents see the same data as human users
03Action Parity Mapping to ensure every UI button has a corresponding agent tool
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05Shared Workspace Verification to ensure agents and users operate in the same data layer
06Tool Design Auditing to favor flexible primitives over rigid business logic workflows

Use Cases

01Refactoring rigid backend tools into flexible primitives for better agent problem-solving
02Designing system prompts that dynamically inject runtime application state
03Auditing a PR after adding new UI features to ensure agent accessibility