Shadcn improve is the better choice than a hand-rolled Claude Code subagent split for most teams, because it turns the "expensive model plans, cheap model executes" pattern into a fixed contract instead of a habit you have to maintain. It reached 10,423 GitHub stars and 427 forks on 11 November 2026, with 333 stars gained in a single day. The manual route still wins for small, one-off jobs where installing anything is more effort than the task.
TL;DR
- Shadcn improve is an Agent Skill that audits a codebase and writes implementation plans. It never edits source code; its only writes go to a
plans/folder (repo README). - It hit 10,423 stars at the 13:00 UTC scan on 11 November 2026 (Early Signal).
- Verdict: adopt improve if you run agents on a codebase more than occasionally. Stay manual for a single throwaway task.
- Install with
npx skills add shadcn/improve, then start with/improve quick. - Last verified: 11 November 2026.
Why is shadcn improve trending again?
The repository was created on 10 June 2026 and passed 1.4K stars in its first 48 hours, according to a third-party review. That same review recorded 7,534 stars and 314 forks on 9 July. Today's numbers are well above that baseline.
| Date | Stars | Source |
|---|---|---|
| 9 July 2026 | 7,534 | dev.to review |
| 11 Nov 2026, 13:00 UTC | 10,423 | Early Signal |
| 11 Nov 2026, 14:05 UTC | 10,488 | GitHub API read |
Our analysis of the two recorded endpoints (Early Signal, dev.to review) puts the July-to-November growth at 2,889 stars, an average of about 160 stars a week, which makes the 333-star day roughly twice the repo's usual weekly pace. The 14:05 UTC row is our own check of the live repository state, a single API snapshot (n=1). Stars measure attention, not quality, so treat this as a reason to look, not a reason to adopt.
What does shadcn improve actually do?
Shadcn improve, written by the creator of shadcn/ui, splits AI-assisted maintenance into two jobs. The most capable model does the thinking: understanding the code, judging what matters, writing the specification. A cheaper model does the typing. In the project's own framing, the plan is the product.
The audit runs nine categories in parallel subagents: correctness, security, performance, test coverage, tech debt, dependencies and migrations, developer experience, docs, and direction. Every finding carries file and line evidence, so you can check a claim before approving any work.
What makes an improve plan different from a prompt?
Each plan is built to survive being handed to an agent that has never seen your repository (repo README):
- Self-contained: all required context is inlined in the plan.
- Verification gates: every step ends with a command and its expected output.
- Hard boundaries: explicit STOP conditions tell the executor when to halt rather than improvise.
- Version-stamped: each plan records the git commit it was written against, so stale plans are detectable.
Plans are plain markdown, so a human or any other agent can pick one up. That portability matters if your team also uses other tools, such as the setup covered in our GitHub Copilot in Xcode 27.3 guide.
How do I set up shadcn improve?
- Run
npx skills add shadcn/improvein any host that supports the Agent Skills format. - Open your agent in the repository and run
/improve quickfirst. This is a short pass over the highest-confidence findings, and the review puts it at about five minutes. Standard mode takes about fifteen. - Reply with the findings you want planned, for example "plan 1, 3 and 5". Plans land in
plans/with an index. - Run
/improve execute 001to dispatch a cheaper executor into an isolated git worktree. The reviewer returns approve, revise (up to twice) or block. Merging stays with you. - Run
/improve reconcilenext session to refresh the backlog, and/improve branchbefore a pull request to audit only what the branch changed. Adding--issuespublishes plans as GitHub issues.
How does it compare with a manual Claude Code subagent split?
You can approximate the same pattern by hand. Write a brief, have a strong model draft a plan, then start a cheaper subagent to execute it. Our piece on Claude Code subagents and cheaper status updates covers the cost logic of delegating routine work, and the thinking behind plan-first work is explored in verify-first versus build-first engineering.
| Factor | Shadcn improve | Manual subagent split |
|---|---|---|
| Setup | One install command | None, but you write the brief every time |
| Plan consistency | Enforced by the skill's contract | Depends on whoever writes the prompt |
| Evidence | file:line on every finding | Whatever you ask for |
| Isolation | Git worktree per execution | Your responsibility |
| Flexibility | Bounded by its audit categories | Unlimited |
| Best for | Ongoing codebase upkeep | One-off or unusual tasks |
The manual approach is not worse in principle. It is worse in practice once the third person on your team writes their own version of the brief. A fixed contract with STOP conditions and verification gates removes that variance.
What are the limitations?
The review is candid about the costs (dev.to). Deep mode on a 200K-line monorepo is still not cheap. Audits are limited to the playbook's categories, so unusual concerns can slip through. Very weak local models as executors need more revision rounds. Reconcile also assumes you return to the project regularly.
There is a process objection too: teams that live in Linear or Jira may not want plans as markdown in git. The --issues option partly addresses that. The SKILL.md file is at v1.0.0, and the repository has no formal GitHub releases, so pin the commit you install if you need reproducibility.
If you are choosing a wider platform for agent-driven coding, our open-source AI agent platform comparison is a useful companion.
Who should adopt shadcn improve?
Adopt it if you maintain a codebase over months, share agent workflows across more than one developer, or want auditable evidence behind each change. Stay manual if you only need a single refactor, or if your project has requirements the nine audit categories do not cover. Either way, start with /improve quick on a non-critical repository and judge the findings before trusting the executor.
FAQ
Q: Does shadcn improve change my source code?
A: No. The skill only writes to the plans/ folder. Code changes happen only if you run /improve execute, which uses an executor in an isolated git worktree, and merging remains your decision.
Q: How many stars does shadcn improve have?
A: It had 10,423 stars and 427 forks at the 13:00 UTC scan on 11 November 2026 (Early Signal), and a live API read at 14:05 UTC showed 10,488.
Q: Which agents can run shadcn improve?
A: Any agent that supports the Agent Skills format. Install it with npx skills add shadcn/improve. Because plans are plain markdown, other agents and humans can also use them.
Q: What is the difference between quick and standard mode?
A: Quick mode returns the top high-confidence findings and takes about five minutes. Standard mode produces the full findings table and takes about fifteen, per the dev.to review.
Q: Is shadcn improve free to use?
A: The project is MIT licensed (GitHub). You still pay for the model usage of whichever agent runs the audit and the executor.
Last verified: 11 November 2026. This article was researched and drafted with AI assistance and reviewed against the primary sources linked above. Corrections are logged on this page when we find them.
