Agent Native Audit (Grade A) logo

Agent Native Audit (Grade A)Security-tested development skill for Claude AI. Grade A. Run comprehensive agent-native architecture review with scored principles

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Daniel NikulshynReviewed by Daniel Nikulshyn·Updated July 2026

Overview

Agent Native Audit (Grade A) is a security-tested development skill for Claude AI that performs a comprehensive review of a codebase against agent-native architecture principles. It launches parallel sub-agents for each principle and produces a scored report. The tool audits core principles such as Action Parity, Tools as Primitives, Context Injection, Shared Workspace, CRUD Completeness, UI Integration, Capability Discovery, and Prompt-Native Features. The process involves loading the agent-native skill, launching parallel sub-agents for each principle, and generating scores and recommendations for improvement. Each sub-agent is tasked with enumerating instances in the codebase, checking compliance against the principle, and providing a specific score along with gaps and recommendations. The tool seems particularly useful for ensuring that agent capabilities align with user actions, that tools provide capability rather than behavior, and that the system includes dynamic context about the app state. It's worth noting that the tool requires a good understanding of agent-native architecture principles and the specific codebase being audited.

Key features

  • Action Parity Audit
  • Tools as Primitives Audit
  • Context Injection Audit
  • Scored report generation
  • Parallel sub-agents for multiple principles

Pricing

Model
Free
Category
Skills
Rating
No reviews yet

Use cases

Codebase Audit

Conduct a comprehensive review of a codebase against agent-native architecture principles to identify gaps and areas for improvement

Agent Capability Alignment

Ensure that agent capabilities align with user actions and that tools provide capability rather than behavior

Dynamic Context Injection

Verify that the system includes dynamic context about the app state to improve agent performance and decision-making

Pros & Cons

Pros

  • Comprehensive review of codebase against agent-native architecture principles
  • Scored report with specific gaps and recommendations
  • Parallel sub-agents for efficient auditing of multiple principles

Cons

  • Requires good understanding of agent-native architecture principles and the codebase
  • May require significant setup and configuration for optimal use
  • Scoring and recommendations may require further interpretation and prioritization

Reviews

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Q&A

Are there any limitations to using Agent Native Audit?

Yes, it requires a good understanding of agent-native architecture principles and the codebase, and may need significant setup and configuration.

Asked by Esther Adeyemi · Oct 10, 2025

What is included in the report?

The report includes scores, gaps, and recommendations for improvement for each principle audited.

Asked by Frank Müller · Sep 23, 2025

What principles are audited?

It audits principles such as Action Parity, Tools as Primitives, Context Injection, and more, using parallel sub-agents for each.

Asked by Vikram Rao · Aug 10, 2025

What does Agent Native Audit do?

It performs a comprehensive review of a codebase against agent-native architecture principles and produces a scored report.

Asked by Noor Siddiqui · Jul 30, 2025

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