methodology

Extract and formalize implemented model methodology into a structured narrative.

Updated Jan 30, 2026

Search Tags:#documentation #methodology #calibration #inputs #outputs #model-governance

Ready to run

npx skills add https://github.com/gtylee/CodexGAS --skill methodology-gtylee

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: methodology
Source: https://github.com/gtylee/CodexGAS/tree/main/modelgas/skills/methodology
Command: npx skills add https://github.com/gtylee/CodexGAS --skill methodology-gtylee

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill translates the implemented model methodology into a formal, machine- and human-readable description that aligns mathematical intent, numerical implementation, and practical usage for validation and governance.

Core Features & Use Cases

Formalizes the relationship between code, mathematics, and operational behavior to support audits and governance reviews.
Documents inputs, outputs, calibration details, and numerical schemes to enable reproducibility.
Use Case: A governance reviewer requests a precise narrative of how the model computes risk measures from input data, including key steps and parameters.

Quick Start

Run the methodology skill against the current model codebase to generate a complete methodology narrative that can be reviewed for accuracy and traceability.

Frequently Asked Questions about methodology

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

FAQPage Schema

How do I document model methodology for governance and validation reviews?▼

Documenting model methodology for governance involves extracting mathematical intent, numerical implementation, and runtime behavior into a structured narrative. This process formalizes calibration, inputs, outputs, and data flows to ensure reproducibility and auditability.

What is the best way to formalize model calibration and data flows for an audit?▼

Formalizing model calibration and data flows for an audit requires mapping entry points and parameter sources to numerical schemes. This creates a JSON-ready methodology description that traces operational behavior back to documented intent.

Can I generate a methodology narrative directly from a codebase?▼

Yes, you can generate a methodology narrative directly from a codebase by analyzing the code structure. The system identifies divergence between documented intent and actual code to produce a structured, machine-readable description for validation.

How do I capture divergence between documented intent and code for model governance?▼

Capturing divergence between documented intent and code requires explicit references to entry points and signatures. By aligning mathematical intent with numerical implementation, the system highlights inconsistencies for governance and audit purposes.

What inputs and outputs are required for model methodology documentation?▼

Inputs and outputs required for model methodology documentation include parameter sources, numerical methods, and data flows. Analyzing these elements produces a JSON-ready description that supports governance, validation, and audit reviews.

Does model governance documentation require explicit references to numerical methods?▼

Yes, model governance documentation requires explicit references to numerical methods and parameter sources. This ensures the structured narrative accurately connects mathematical intent with runtime behavior for validation purposes.