supercov: Layering structured judgment on coverage/test signals
You should be able to explain Supercov in four sentences: what enters the system, what Jev judges, what code executes, and what independently proves the job finished.
Use caseAdd one narrow, explicit decision to code or a workflow
Focus on supercov’s decision boundary: layering structured judgment on coverage/test signals to flag gaps worth fixing. From the public repository, separate the problem, where Jev judges, what code still owns, and how to reproduce the smallest safe example. Source walkthrough—not a restated live benchmark.
Source · supercorp-ai/supercov · Open-source project
What this project does
Section titled “What this project does”Public sources present this project for layering structured judgment on coverage/test signals to flag gaps worth fixing. This site has not reproduced the full project.
Sources
Section titled “Sources”
GitHub Open Graph preview for the supercorp-ai/supercov repository; a repository preview, not a screenshot of running software. Notes are based on its public source.
A useful first read
Section titled “A useful first read”Add one narrow, explicit decision to code or a workflow
Based on the public repository; this site has not reproduced the full project. Read the source before deciding whether to try it.