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Evidence-based architecture audits for AI-era codebases

Software Engineering#AI coding agent#LLM#code audit#architecture audit#evidence-based
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Version1.0.0
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What problem does it solve?

This Skill performs evidence-based architecture audits for AI-era codebases, ensuring architectural invariants remain stable under AI-assisted change.

Core Features & Use Cases

  • PR Audits: Conduct PR scoped audits with customizable lenses.
  • Full-scale Audits: Run comprehensive audits across all mandatory lenses for a full report.
  • Commit Range Audits: Analyze specific commit ranges for architectural drift.
  • Module Audits: Assess individual modules or directory subtrees.
  • ADR Audits: Review ADRs for code drift and compliance.
  • Refactoring Proposal Audits: Evaluate proposed refactorings for potential invariant violations.
  • Evidence Verification: Adversarially verify candidate findings.
  • Severity Classification: Classify findings into severity levels.
  • Report Synthesis: Assemble final audit reports.
  • Closure Verification: Re-verify fixed findings post-incident.

Quick Start

Run an audit on your current PR with the /invairiant audit-pr command.

Dependency Matrix

Required Modules

None required

Components

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💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: invairiant
Download link: https://github.com/mindicator/invAIriant/archive/main.zip#invairiant

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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