shadcn/improvePublic

Use your most capable model to audit your codebase and write plans for cheaper models to execute.

AI summary: An agent skill that uses high-capability models to audit codebases and write execution plans.

Stars
9.2K
+2 today
Forks
414
Watchers
34
Open issues
5
Open PRs
12
Contributors
~5
Commits
23
Branches
1

MITCreated Jun 10, 2026Last push 22d ago+22 stars this week+132 this month

Quick answers

What is improve?
An agent skill that uses high-capability models to audit codebases and write execution plans.
What does improve do?
Improve operates as an advanced agent skill that delegates complex repository analysis to highly capable, expensive AI models in order to produce detailed implementation specifications. Rather than modifying source code directly, it acts purely as a technical architect, mapping the codebase and identifying areas for enhancement across security, performance, and technical debt. It outputs self-contained, explicitly defined markdown plans that include verified local test commands and strict scope boundaries. These plans are then handed off to smaller, cheaper execution models, allowing for a highly efficient, compound-intelligence workflow.
Who is improve for?
Improve is designed for software architects, technical leads, and developers who heavily utilize AI coding agents for complex repository tasks. It requires an environment that supports the Agent Skills format and access to both high-tier and low-tier LLM APIs.
How do I get started with improve?
npx skills add shadcn/improve
How popular is improve on GitHub?
shadcn/improve has 9,195 stars and 414 forks on GitHub, and gained 22 stars in the last 7 days.
What license does improve use?
shadcn/improve is released under the MIT license.

Star history

since Jul 29, 2026
02.5K5K7.5KJul 2026Aug 2026Sep 2026Oct 2026
9.2K stars as of Oct 3, 2026. Measured daily since Jul 29, 2026; GitHub no longer exposes earlier star timestamps.

Contribution activity

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15 commits in the last yearLessMore

Signals and awards

derived from tracked data
  • Breakout launch

    9,195 stars in 116 days

  • Permissive license

    MIT

  • Repeat trending

    5 trending appearances

What improve does

Improve operates as an advanced agent skill that delegates complex repository analysis to highly capable, expensive AI models in order to produce detailed implementation specifications. Rather than modifying source code directly, it acts purely as a technical architect, mapping the codebase and identifying areas for enhancement across security, performance, and technical debt. It outputs self-contained, explicitly defined markdown plans that include verified local test commands and strict scope boundaries. These plans are then handed off to smaller, cheaper execution models, allowing for a highly efficient, compound-intelligence workflow.

Improve is designed for software architects, technical leads, and developers who heavily utilize AI coding agents for complex repository tasks. It requires an environment that supports the Agent Skills format and access to both high-tier and low-tier LLM APIs.

  • High-level codebase auditing: Exhaustively scans repositories to identify hotspots, bugs, and architectural flaws using top-tier reasoning models.
  • Markdown plan generation: Outputs completely self-contained, prioritized implementation specs that any agent or human can easily parse and execute.
  • Targeted branch analysis: Scopes its audits strictly to the files modified in a current branch to quickly review and plan PR improvements.
  • Automated execution dispatch: Can seamlessly spawn a cheaper secondary model in an isolated worktree to implement and test the generated plans.
  • Backlog reconciliation: Verifies which generated plans have been successfully implemented and refreshes or retires specs that have drifted.

Where teams use it

Cost-Optimized AI Development

Teams use the tool to leverage an expensive model (like Claude 3.5 Sonnet) to write the architectural spec, while assigning a cheaper model (like Haiku) to actually write the code.

Automated Code Reviews

Lead developers run the targeted branch audit to automatically generate a prioritized list of structural improvements before approving a pull request.

Technical Debt Management

Maintainers execute deep audits to systematically uncover and catalog performance bottlenecks and security flaws into an actionable markdown backlog.

Agentic CI/CD Pipelines

DevOps engineers integrate the tool to automatically audit nightly builds, generating concrete fix plans that are automatically published as GitHub issues.

Getting started: npx skills add shadcn/improve

README

main branch

improve

An agent skill that audits any codebase and writes implementation plans for other agents to execute.

The idea: use your most capable model for the part where intelligence compounds — understanding the codebase, judging what's worth doing, writing the spec — and hand execution to cheaper models. The skill never implements anything itself. The plan is the product.

you          →  /improve                    (expensive model, advises)
plans/       →  001-fix-n-plus-one.md       (self-contained specs)
other agent  →  implements, tests, ships    (cheap model, executes)

Install

npx skills add shadcn/improve

Works in any agent that supports Agent Skills format. The plans it writes are plain markdown, so any agent (or human) can pick them up.

Usage

/improve                        full audit → prioritized findings → plans
/improve quick                  cheap pass: hotspots, top findings only
/improve deep                   exhaustive: every package, every category
/improve security               focused audit (also: perf, tests, bugs, ...)
/improve branch                 audit only what the current branch changes
/improve next                   feature suggestions — where to take the project
/improve plan <description>     skip the audit, spec one thing
/improve review-plan <file>     critique and tighten an existing plan
/improve execute <plan>         dispatch a cheaper executor, review its work
/improve reconcile              refresh the backlog: verify, unblock, retire
/improve ... --issues           also publish plans as GitHub issues

How to use

A typical first run, start to finish:

  1. Open your agent in the repo and run /improve (or /improve quick to keep it cheap).
  2. It maps the repo, audits it, and comes back with a findings table. Reply with the ones you want planned — "plan 1, 3 and 5".
  3. Plans land in plans/ — one file each, plus an index with the recommended order. Read them; they're meant to be reviewed.
  4. Hand a plan to any agent ("implement plans/001-*.md"), or let the skill run it: /improve execute 001. It dispatches a cheaper model in an isolated worktree, reviews the diff against the plan, and reports back with a verdict. Merging stays up to you.
  5. Next session, run /improve reconcile to clean up the backlog: verify what landed, refresh what drifted, unblock what got stuck.

Before a PR, /improve branch does the same thing scoped to just what your branch changes.

Example

A run against shadcn/ui came back with findings like:

| # | Finding                                        | Category  | Effort | Confidence |
|---|------------------------------------------------|-----------|--------|------------|
| 1 | shadow-config duplicated in search.ts/view.ts, | tech-debt | M      | HIGH       |
|   | copies already drifted (TODO at search.ts:31)  |           |        |            |
| 2 | O(n²) icon migration (migrate-icons.ts:168)    | perf      | S      | HIGH       |

…and rejected a few, with reasons recorded so they don't come back next run:

- [SEC-01] https_proxy env var "SSRF": by-design — standard proxy convention,
  every CLI honors it. Not a finding.

Picking #1 produced this plan — current code excerpted, exact steps, the repo's own test/lint commands as verification gates, and STOP conditions for when reality doesn't match.

How it works

Recon. Maps the repo: stack, conventions, and the exact build/test/lint commands — these become verification gates in every plan. It also ingests intent and design docs when present — ADRs (docs/adr/), PRDs, CONTEXT.md, DESIGN.md, PRODUCT.md — so decided tradeoffs aren't re-flagged as findings, direction suggestions stay grounded in stated product intent, and plans speak the repo's own vocabulary. Composes with any repo that already maintains these docs.

Audit. Fans out parallel subagents across nine categories: correctness, security, performance, test coverage, tech debt, dependencies & migrations, DX, docs, and direction (feature suggestions — every one must cite evidence from the repo itself, no generic idea-slop). Every finding carries file:line evidence, impact, effort, and confidence.

Vet. Subagents over-report, so the advisor re-reads every cited location itself before showing you anything — false positives get dropped, wrong attributions get corrected, rejections get recorded.

Prioritize. Findings land in a table ordered by leverage (impact ÷ effort, weighted by confidence). You pick what becomes plans.

Plan. One file per selected finding, written into plans/ with an index, priority order, and dependency graph.

What makes the plans executable

Plans are written for the weakest plausible executor — a model that has never seen the advisor session and may be much smaller. Three properties carry that:

  • Self-contained. All context is inlined: exact file paths, current-state code excerpts, repo conventions with an exemplar file, verified commands. No "as discussed above."
  • Verification gates. Every step ends with a command and its expected output. Done criteria are machine-checkable. The executor never has to judge whether it succeeded.
  • Hard boundaries. Explicit out-of-scope lists, and STOP conditions — "if X, stop and report" — instead of letting a small model improvise when reality doesn't match the plan.

Each plan also stamps the git commit it was written against, so executors run a mechanical drift check before touching anything.

Closing the loop

Plans aren't fire-and-forget:

  • execute <plan> spawns a cheaper executor subagent in an isolated git worktree, hands it the plan, then reviews the result like a tech lead — re-runs every done criterion, checks scope compliance, reads the diff against intent. Verdict: approve (merging stays your call), send back for revision (max 2 rounds), or block and refine the plan.
  • reconcile processes what happened since: verifies DONE plans still hold, investigates BLOCKED ones and rewrites around the obstacle, refreshes drifted plans, retires findings that got fixed independently.
  • --issues publishes plans as GitHub issues — same self-contained body, so any agent or human can pick them up where work already lives.

Hard rules

  • Never modifies source code itself. The only writes go to plans/; executors edit only in disposable worktrees, and merging is always yours.
  • Never runs commands that mutate your working tree — read, search, and read-only analysis only.
  • Never reproduces secret values. Locations and credential types only, rotation always recommended.
  • Asked to implement? It declines and points at the plan (or offers execute).

License

MIT © shadcn

View on GitHub

Recent activity

commits and pull requests

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15 commits in the last 52 weeks.

When work happens

weekday and hour
SunMonTueWedThuFriSat036912151821Sun 0:00 — 0 commitsSun 1:00 — 0 commitsSun 2:00 — 0 commitsSun 3:00 — 0 commitsSun 4:00 — 0 commitsSun 5:00 — 0 commitsSun 6:00 — 0 commitsSun 7:00 — 0 commitsSun 8:00 — 0 commitsSun 9:00 — 0 commitsSun 10:00 — 0 commitsSun 11:00 — 0 commitsSun 12:00 — 0 commitsSun 13:00 — 0 commitsSun 14:00 — 0 commitsSun 15:00 — 0 commitsSun 16:00 — 0 commitsSun 17:00 — 0 commitsSun 18:00 — 0 commitsSun 19:00 — 0 commitsSun 20:00 — 0 commitsSun 21:00 — 0 commitsSun 22:00 — 0 commitsSun 23:00 — 0 commitsMon 0:00 — 1 commitsMon 1:00 — 0 commitsMon 2:00 — 0 commitsMon 3:00 — 0 commitsMon 4:00 — 0 commitsMon 5:00 — 0 commitsMon 6:00 — 0 commitsMon 7:00 — 0 commitsMon 8:00 — 0 commitsMon 9:00 — 0 commitsMon 10:00 — 3 commitsMon 11:00 — 0 commitsMon 12:00 — 0 commitsMon 13:00 — 0 commitsMon 14:00 — 0 commitsMon 15:00 — 0 commitsMon 16:00 — 0 commitsMon 17:00 — 0 commitsMon 18:00 — 0 commitsMon 19:00 — 0 commitsMon 20:00 — 0 commitsMon 21:00 — 0 commitsMon 22:00 — 0 commitsMon 23:00 — 0 commitsTue 0:00 — 0 commitsTue 1:00 — 0 commitsTue 2:00 — 0 commitsTue 3:00 — 0 commitsTue 4:00 — 0 commitsTue 5:00 — 0 commitsTue 6:00 — 0 commitsTue 7:00 — 0 commitsTue 8:00 — 0 commitsTue 9:00 — 0 commitsTue 10:00 — 0 commitsTue 11:00 — 0 commitsTue 12:00 — 0 commitsTue 13:00 — 0 commitsTue 14:00 — 0 commitsTue 15:00 — 0 commitsTue 16:00 — 0 commitsTue 17:00 — 0 commitsTue 18:00 — 0 commitsTue 19:00 — 0 commitsTue 20:00 — 0 commitsTue 21:00 — 0 commitsTue 22:00 — 0 commitsTue 23:00 — 0 commitsWed 0:00 — 0 commitsWed 1:00 — 0 commitsWed 2:00 — 0 commitsWed 3:00 — 0 commitsWed 4:00 — 0 commitsWed 5:00 — 0 commitsWed 6:00 — 0 commitsWed 7:00 — 0 commitsWed 8:00 — 0 commitsWed 9:00 — 0 commitsWed 10:00 — 0 commitsWed 11:00 — 0 commitsWed 12:00 — 0 commitsWed 13:00 — 0 commitsWed 14:00 — 0 commitsWed 15:00 — 2 commitsWed 16:00 — 3 commitsWed 17:00 — 0 commitsWed 18:00 — 0 commitsWed 19:00 — 0 commitsWed 20:00 — 1 commitsWed 21:00 — 0 commitsWed 22:00 — 0 commitsWed 23:00 — 0 commitsThu 0:00 — 0 commitsThu 1:00 — 0 commitsThu 2:00 — 0 commitsThu 3:00 — 0 commitsThu 4:00 — 0 commitsThu 5:00 — 0 commitsThu 6:00 — 0 commitsThu 7:00 — 0 commitsThu 8:00 — 0 commitsThu 9:00 — 0 commitsThu 10:00 — 0 commitsThu 11:00 — 0 commitsThu 12:00 — 0 commitsThu 13:00 — 0 commitsThu 14:00 — 0 commitsThu 15:00 — 0 commitsThu 16:00 — 0 commitsThu 17:00 — 0 commitsThu 18:00 — 2 commitsThu 19:00 — 0 commitsThu 20:00 — 0 commitsThu 21:00 — 0 commitsThu 22:00 — 1 commitsThu 23:00 — 0 commitsFri 0:00 — 0 commitsFri 1:00 — 0 commitsFri 2:00 — 0 commitsFri 3:00 — 0 commitsFri 4:00 — 0 commitsFri 5:00 — 0 commitsFri 6:00 — 0 commitsFri 7:00 — 0 commitsFri 8:00 — 0 commitsFri 9:00 — 0 commitsFri 10:00 — 0 commitsFri 11:00 — 1 commitsFri 12:00 — 0 commitsFri 13:00 — 0 commitsFri 14:00 — 0 commitsFri 15:00 — 0 commitsFri 16:00 — 0 commitsFri 17:00 — 0 commitsFri 18:00 — 0 commitsFri 19:00 — 0 commitsFri 20:00 — 0 commitsFri 21:00 — 0 commitsFri 22:00 — 0 commitsFri 23:00 — 0 commitsSat 0:00 — 0 commitsSat 1:00 — 0 commitsSat 2:00 — 0 commitsSat 3:00 — 0 commitsSat 4:00 — 0 commitsSat 5:00 — 0 commitsSat 6:00 — 0 commitsSat 7:00 — 0 commitsSat 8:00 — 0 commitsSat 9:00 — 0 commitsSat 10:00 — 0 commitsSat 11:00 — 0 commitsSat 12:00 — 0 commitsSat 13:00 — 0 commitsSat 14:00 — 0 commitsSat 15:00 — 1 commitsSat 16:00 — 0 commitsSat 17:00 — 0 commitsSat 18:00 — 0 commitsSat 19:00 — 0 commitsSat 20:00 — 0 commitsSat 21:00 — 0 commitsSat 22:00 — 0 commitsSat 23:00 — 0 commits
Commit volume by weekday and hour (UTC). Larger dots mean more commits.

Who is committing

last 52 weeks
Maintainer commits18 (78%)
Community commits5 (22%)

23 commits in total over the last year.

DateListRankStars gained
Jun 15, 2026daily#16+22
Jun 14, 2026daily#7+60
Jun 13, 2026daily#15+42
Jun 12, 2026daily#19+21
Jun 11, 2026daily#17+22
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