AI Chaos Index

A quantified measure of structural risk in AI-generated codebases. One number that tells you if your app is safe to scale — or silently falling apart.

Risk bands

ScoreZoneWhat it meansRecommended action
0–25StableMinor improvements possible. Architecture is sound.Deploy with confidence. Consider enforcement to maintain quality.
26–50RiskyStructural weaknesses present. Degradation likely under continued development.Plan remediation. Address before scaling.
51–75HighActive degradation. Each new feature increases instability.Stabilize before adding features.
76–100CriticalProduction instability imminent or already occurring.Architecture intervention needed immediately.

ACI does not measure bugs. It measures structural failure risk.

A codebase can have zero bugs and still score 80+ on ACI — because the architecture is one feature away from collapse.

Why not just use code quality tools?

Tools like ESLint, SonarQube, or CodeClimate measure code quality — style violations, complexity metrics, code smells.

ACI measures something different: structural integrity — whether the architecture can sustain continued development without degradation.

Code Quality ToolsAI Chaos Index
MeasuresStyle, complexity, duplicationStructural risk, architecture integrity
ScopeFile-levelSystem-level (dependency graph, boundaries)
PredictsCode maintainabilityRegression cascades, production failure risk
AI-specificNoYes — designed for prompt-driven codebases

Code quality and structural integrity are complementary — but only structural integrity predicts whether the next 10 features will succeed or fail.

Example ACI report

AI Chaos Index — Quick Scan Output

Repository: client-app (Next.js + Supabase)

Generated with: Lovable

Age: 4 months | 38k LOC

Root Cause Analysis

RC01 Architecture Drift 7.2 / 10 HIGH

RC02 Dependency Corruption 5.8 / 10 ELEVATED

RC03 Structural Entropy 4.1 / 10 MODERATE

RC04 Test Infrastructure 8.5 / 10 CRITICAL

RC05 Deployment Safety 6.3 / 10 HIGH

AI Chaos Index: 64.8 / 100 Risk Band: HIGH

Top Findings

[CRITICAL] 14 files exceed 500 LOC (max: 1,847)

[CRITICAL] Test coverage ratio: 3%

[HIGH] 6 circular dependency chains detected

[HIGH] No CI/CD pipeline

[ELEVATED] Business logic in 8 route handlers

This is an example output. Your report will reflect the actual structural state of your repository.

How to get your ACI score

Free — Run it yourself

The ASA Engine CLI runs locally on your machine. No data leaves your computer. Open source.

View ASA Engine CLI →

Quick Scan — $297

Professional analysis by an architect. ACI score + root cause breakdown + prioritized findings + personal video walkthrough. Delivered in 24 hours.

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Methodology

The AI Chaos Index is based on the ASA Standard — an open architecture standard for AI-generated codebases.

The scoring model analyzes:

  • Dependency graph structure and circular dependency detection
  • Layer boundary violations (business logic in wrong layers)
  • File size distribution and structural entropy metrics
  • Test coverage and test infrastructure completeness
  • CI/CD pipeline presence and deployment safety checks

The methodology is deterministic — the same codebase always produces the same score. No AI interpretation, no subjective judgment.

What's your AI Chaos Index?

Find out in 24 hours. One score. Complete structural clarity.