Developed and integrated support for the ResearchClawBench evaluation framework within the huggingface.js repository, enabling automatic recognition of benchmark datasets and the display of a benchmark leaderboard directly on the Hub. This work involved updating the EVALUATION_FRAMEWORKS registry in TypeScript to include the new framework, ensuring seamless identification of evaluation-framework-tagged datasets without altering runtime data flow. The implementation aligned with the Hub Evaluation Results workflow and improved dataset discoverability and benchmarking visibility. Leveraging skills in AI, benchmarking, and full stack development, the contribution focused on enhancing the evaluation infrastructure and user experience for benchmarking within the Hugging Face ecosystem.