BLOG / USE-CASES
How teams use codebase intelligence for onboarding, audits, and visibility
A code audit checklist for technical due diligence: a 20-minute automated first pass, then the manual checks, worked step by step on pallets/flask.
How to compare code health across many repositories fairly: which code-level signals to track, how to normalise them, and which tools build the view.
A diff can't show the file that should have changed with it. Co-change from git history and blast radius help code review catch coupled changes.
How Nx, Turborepo, Bazel, Pants, moon and Rush map dependencies, plus a checklist for moving 50+ projects into one monorepo.
repowise is developed against an index of itself: every pull request is gated by the same risk and health checks we ship. The setup, measurements, and limits.
Onboard engineers faster on any codebase with an auto-generated wiki and 10 MCP tools that recover the why behind legacy code. See the 30-day approach inside.
Read an unfamiliar codebase fast by treating the first pass like an incident review, not a refactor: four lenses, an hourly workflow, and a repeatable audit memo.
A production incident creates one question fast: who changed this code? The answer is rarely “the last commit.” It is usually a chain of changes, ownership…
pr bot silent default is the only sane default for review automation. A GitHub PR bot should stay out of the way on green changes, then speak only when it…

Run a pre-acquisition code audit on a Flask monolith with graph, git history, wiki freshness, and ADRs. Find surprises before week two.

Audit legacy code with graph, history, wiki, and ADRs to answer ownership, risk, and rewrite questions before a deal. See 4 layers in one review.

A security review codebase case study on a Python monolith: find 19 hotspots, map ownership gaps, and cut duplicate reads with one review path.