Methodology

How Structural Maturity Is Assessed

The RAMTSE framework defines the structure of maturity. The methodology defines how that structure is examined in real systems.

AgentIQIndex evaluates architectural patterns within agent codebases to assess structural design decisions. The focus is not on business logic or feature completeness, but on how the system is built.

The evaluation is evidence-based, directional, and designed to evolve over time.

01

Evaluation Approach

The assessment analyzes source code to identify structural indicators associated with each RAMTSE dimension.

We examine whether the system demonstrates:

Clear separation of concerns
Explicit orchestration flows
Structured tool integration
Defined error-handling pathways
Embedded safety boundaries
Managed state and memory integration

The analysis is static.

It does not execute the agent, simulate workflows, or evaluate runtime outputs.

It evaluates architecture — not behavior.

02

Structural Indicators

Each RAMTSE dimension is supported by identifiable architectural signals.

These signals reflect implementation choices such as:

Explicit state managementDefined control flow transitionsEncapsulation of external interactionsPresence of resilience mechanismsClear boundary enforcement

Signals are aggregated to produce a maturity assessment for each dimension.

A stronger and more consistent structural pattern results in a higher maturity indication.

The presence of signals suggests intentional design. Their absence may indicate structural gaps — or unconventional implementation.

03

Scoring Interpretation

Scores represent relative structural maturity within the framework.

They:

Highlight strengths
Surface architectural weaknesses
Encourage balanced system design

They do not:

Measure intelligence
Guarantee correctness
Predict runtime performance

The purpose of scoring is clarity — not ranking.

04

Confidence Indicators

Because the evaluation is based on structural detection rather than runtime observation, each dimension includes a confidence indicator.

Confidence reflects:

Strength of detected architectural patterns
Consistency across the codebase
Density of supporting signals

Lower confidence does not imply poor design. It may indicate custom or non-standard implementations.

05

What Is Not Evaluated

AgentIQIndex does not assess:

Model output quality
Real-world task accuracy
Latency or infrastructure performance
User experience

Static analysis cannot capture emergent behavior or runtime dynamics.

The framework should be used as a structural lens — not a certification.

06

Iterative Refinement

Agent systems are evolving rapidly.

The RAMTSE framework and its implementation will continue to evolve as architectural patterns mature and new best practices emerge.

Future iterations may incorporate additional dimensions such as runtime observability or governance indicators where appropriate.

Agent systems are engineered systems operating across time.

Sustained reliability depends on structure, not isolated demonstrations.

The methodology reflects that principle.

Apply the Framework

Understand the dimensions, then evaluate your system.