bug-hunter

To automate bug hunts, this Skill randomly selects files weighted by recency to surface non-obvious issues, filters findings through configurable automation flows, and automatically creates GitHub issues for approved results. It maintains an audit trail for governance over issue creation.

Randomized file selection weighted by recency is a mechanism to surface under-explored areas of a repository. By analyzing context across related files, it identifies non-obvious bugs and reports them with actionable context for continuous quality checks.

Yes, automated bug hunting applies directly to software development projects needing continuous quality checks. You can configure automation flows to approve, reject, or filter findings, automatically generating GitHub issues to maintain governance over issue creation.

To start a bug scan, simply instruct the system to begin scanning now. The process will automatically hunt bugs across your repository, analyze related files for context, and prepare findings for approval and issue creation.

Yes, Git integration is required to automate issue creation from bug hunts. The process requires Git, audit logs, and automation commands to filter findings, approve results, and maintain an audit trail for GitHub issue generation.

Automated bug discovery focuses on randomized, context-aware analysis rather than exhaustive full-codebase scanning. Findings must pass through configurable approval flows before GitHub issues are created, meaning human governance is still required to filter and approve results.