UKGovernmentBEIS/inspect_evals
Feb 2026 – Feb 2026
1 Month active
Languages Used
DockerfileMarkdownPython
Technical Skills
ContainerizationDevOpsPythonPython Developmentbackend developmentdocumentation
Stephen Kyle
PROFILE
Stephen Kyle
Jimmy Kane enhanced the evaluation pipeline for the UKGovernmentBEIS/inspect_evals repository, focusing on reliability and developer experience. He improved the Ds1000 scorer by enabling robust extraction of submitted code from code tags regardless of their position, and updated documentation to guide agent usage, culminating in a major version upgrade. Jimmy also addressed infrastructure issues in the MLE_Bench grading server, correcting Dockerfile execution and ensuring compatibility with conda environments. Using Python, Dockerfile, and Markdown, he delivered more accurate scoring and reproducible grading runs. His work demonstrated depth in backend development, containerization, and documentation, resulting in clearer upgrade paths and smoother onboarding.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
2Total
Bugs
1
Commits
2
Features
1
Lines of code
82
Activity Months1
Your Network
101 peopleWork History
February 2026
2 Commits • 1 Features
Feb 1, 2026February 2026: Strengthened the evaluation pipeline for UKGovernmentBEIS/inspect_evals with a focus on reliability, correctness, and developer experience. Key deliverables included: (1) Ds1000 Scorer Enhancement enabling robust extraction of submitted code from <code> tags regardless of position, along with agent usage guidance and a major version bump to 2.0.0; (2) MLE_Bench Grading Infrastructure Fix addressing Dockerfile execution and conda-environment execution of the grading server, with updates to the README and changelog to reflect improvements. These changes improved scoring accuracy and grading reliability, reduced onboarding friction, and established clearer upgrade paths.
2 Commits • 1 Features
Feb 1, 2026February 2026: Strengthened the evaluation pipeline for UKGovernmentBEIS/inspect_evals with a focus on reliability, correctness, and developer experience. Key deliverables included: (1) Ds1000 Scorer Enhancement enabling robust extraction of submitted code from <code> tags regardless of position, along with agent usage guidance and a major version bump to 2.0.0; (2) MLE_Bench Grading Infrastructure Fix addressing Dockerfile execution and conda-environment execution of the grading server, with updates to the README and changelog to reflect improvements. These changes improved scoring accuracy and grading reliability, reduced onboarding friction, and established clearer upgrade paths.
February 2026
Activity
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Quality Metrics
Correctness90.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage30.0%
Skills & Technologies
Programming Languages
DockerfileMarkdownPython
Technical Skills
ContainerizationDevOpsPythonPython Developmentbackend developmentdocumentation
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