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agent-native-reviewer

Identify and fix action parity gaps between user actions and agent capabilities.

Updated Mar 14, 2026
Search Tags:#code-review#ai-agents#tool-design#system-prompts#parity-audit#agent-native-reviewer
One-click install
npx skills add https://github.com/Andreicr1/netz-analysis-engine --skill agent-native-reviewer-andreicr1
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agent-native-reviewer
Source: https://github.com/Andreicr1/netz-analysis-engine/tree/main/.gemini/skills/agent-native-reviewer
Command: npx skills add https://github.com/Andreicr1/netz-analysis-engine --skill agent-native-reviewer-andreicr1

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Reviews code to ensure agents are first-class citizens with the same capabilities as users -- not bolt-on features. Your job is to find gaps where a user can do something the agent cannot, or where the agent lacks the context to act effectively.

Core Features & Use Cases

  • Action parity: Identify UI actions lacking equivalent agent tools.
  • Context parity: Validate agents see the same data and prompts as users.
  • Guided audits: Provide actionable recommendations and documentation to fix parity gaps.

Quick Start

Run a parity audit against the latest codebase to verify that every user action has a corresponding agent capability.

Frequently Asked Questions about agent-native-reviewer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
What is an action parity gap in AI agent code review?▼

An action parity gap occurs when a user can perform a UI action that the AI agent cannot, or when the agent lacks the necessary context to act effectively. Identifying these gaps ensures agents function as first-class citizens rather than bolt-on features.

How do I check if my AI agent has the same capabilities as the user interface?▼

You can check agent capabilities by running a structured parity audit that maps user UI actions to agent tools, validates context parity to ensure equal data access, and reviews tool design to confirm functional equivalence.

When should I perform a context parity check for my AI agent?▼

Perform a context parity check during feature additions or pull request reviews to ensure the agent sees the same data and system prompts as the user, preventing blind spots in agent actions.

Can I use this parity audit for pull request reviews on agent tooling?▼

Yes, this structured review process is specifically applicable to PR reviews and feature additions in codebases that integrate agents with UI features, prompts, or tools, providing actionable recommendations to fix gaps.

What is the best way to validate tool design for AI agents?▼

The best way to validate tool design is through a risk-aware review process that maps agent capabilities against user actions, checks context parity, and generates documentation for fixing any identified parity gaps.

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