I built a Claude Code skill called Stack Changes . The idea is simple: one diff, one thesis . A lot of AI coding tools are good at generating code, but that often creates a new problem: the giant PR. You start with a reasonable change, then add a refactor, tests, cleanup, CLI wiring, and a few behavior changes. Suddenly reviewers are looking at 1,000+ lines and doing their best to mentally untangle it. This skill tries to solve the problem before review. You give it a large local diff, commit, branch, PR, CL, or diff, and it produces a stacked landing plan: refactors first, behavior changes later, each step making one clear argument and building/testing on its own. Example: Before: +1,019 lines, 27 files, 1 PR After: [1/7] refactor: introduce Money/Transaction domain model [2/7] refactor: route rendering through query pipeline [3/7] refactor: extract Formatter interface + registry [4/7] feat: add CSV, JSON, HTML, and Markdown formatters [5/7] feat: add filtering, sorting, and grouping [6/7] feat: add per-category budgets [7/7] feat: wire up CLI It is not meant to be another AI PR reviewer. It does not primarily hunt for bugs or post comments. It is more like a PR authoring coach: before asking humans to review a change, make the change reviewable. A few things I tried to make practical: It works with GitHub, Graphite, Sapling, Gerrit, Phabricator, ghstack, spr, and plain git. It looks at local repo context like changed files, review system, ownership boundaries, build/test hints, and project conventions. The demo stack is verified in CI by checking out each step and running the relevant build/test commands. Repo: https://github.com/Ishtiaqhossain/claude_stack_changes Would love feedback from people using Claude Code, stacked PRs, or review-heavy workflows. Curious whether this matches how you split large changes in practice. submitted by /u/Sorry-Quantity728
Originally posted by u/Sorry-Quantity728 on r/ClaudeCode