Technical debt analytics for small agile teams

CodeSage AI

Rank the debt that is most likely to create future bugs, then aim limited refactoring time at the files, findings, and categories that matter before the next release.

Start with GitHub sign-in Explore prioritization

Evidence-weighted priority

Move from noisy static-analysis backlogs to ranked engineering decisions.

CodeSage combines deterministic rule severity, SATD confidence, recent churn, debt category weights, and predicted file risk into a single priority score your team can explain.

Refactor-First

SATD comments, rule evidence, and file risk converge here.

Repository heat

18 files

High-churn modules with repeated findings move to the top.

Health trend

B+

Release pressure stays visible next to quality movement.

Repository history

Process metrics reveal churn, author count, file age, and recency.

Rules and security

Deterministic findings stay visible with source confidence intact.

Bug-prone files

ML risk influences priority without creating synthetic findings.

Scoring profiles

Teams rebalance evidence and category weights without rescanning.

Ready for the Refactor-First list

Connect a repository, scan a revision, and start with the debt most likely to affect delivery.