Extract and formalize implemented model methodology into a structured narrative.
npx skills add https://github.com/gtylee/CodexGAS --skill methodology-gtylee
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
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.
Run the methodology skill against the current model codebase to generate a complete methodology narrative that can be reviewed for accuracy and traceability.
High-intent search queries and answers about installing and using this skill.
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.
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.
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.
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.
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.
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.
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