During August 2025, Eddy Ponton developed a Public Data Transparency and Quality Scoring feature for the dataforgoodfr/13_eclaireur_public repository. He designed and implemented a backend workflow in Python and SQL, leveraging Polars for efficient data processing. The feature introduced a reproducible assessment framework that evaluates the transparency and quality of local authority data publications, specifically targeting subsidy declarations and public procurement datasets. By creating a grading mechanism that assigns A–E scores based on standardized criteria, Eddy enabled stakeholders to consistently assess data quality. His work addressed the need for objective evaluation, supporting improved data publication practices and increased stakeholder trust.