Does it support custom verification scripts?

Yes, it utilizes specific Python and Bash scripts for schema validation, integrity checks, and backtesting as part of the gated phases.

What is the 5-phase verification workflow?

It is a gated process covering schema mapping, data auditing, evaluation planning, reproducible backtesting, and final contract bundle generation.

What artifacts does the pipeline produce?

It produces quality summaries (JSON), evaluation metrics, evidence reports (Markdown), and a complete deployable contract bundle.

Can this skill be used for TimeGPT pipelines?

Yes, it is specifically designed to work within the Nixtla ecosystem for generating and verifying TimeGPT pipelines and model benchmarks.

How does it handle validation errors?

It treats script outputs as ground truth, requiring the user to update mappings or data until the deterministic verification scripts pass before moving to the next phase.

Data & Model Verification Pipeline

Name: Data & Model Verification Pipeline
Author: intent-solutions-io

byintent-solutions-io

Ciencia de Datos y ML

Automates a multi-phase gated workflow to produce verified datasets, evaluation metrics, and deployable contract bundles.

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The Data & Model Verification Pipeline skill provides a rigorous, five-phase framework for ensuring the integrity and correctness of data-driven workflows. It manages the entire lifecycle of a project from raw input mapping and deterministic data audits to running reproducible backtests and generating deployable API contract bundles. This skill is essential for teams requiring provable correctness at data boundaries and high-confidence evaluation results before moving machine learning models or data pipelines into production environments.

Características Principales

Automated 5-phase gated verification workflow
Deterministic data quality auditing and schema mapping
Reproducible model evaluation and backtesting
Automated generation of deployable contract bundles
Detailed evidence reporting with metrics and quality summaries
0 GitHub stars

Casos de Uso

Generating provable evaluation reports for machine learning models
Auditing data integrity and schema compliance before deployment
Validating time-series datasets and TimeGPT pipeline inputs

Acerca de

Características Principales

Automated 5-phase gated verification workflow
Deterministic data quality auditing and schema mapping
Reproducible model evaluation and backtesting
Automated generation of deployable contract bundles
Detailed evidence reporting with metrics and quality summaries
0 GitHub stars

Casos de Uso

Generating provable evaluation reports for machine learning models
Auditing data integrity and schema compliance before deployment
Validating time-series datasets and TimeGPT pipeline inputs