Code Review and Refactoring Skills for AI Agents in 2026

Code review skills are becoming more important because agents are now good enough to create a lot of code quickly. That changes the bottleneck. The hard part is not always producing a first draft. It is knowing whether the change is correct, maintainable, secure, tested, and small enough to merge with confidence.

Refactoring skills sit right next to that problem. A code review can identify a messy boundary, an unsafe assumption, or a brittle API. A refactoring skill can help improve it without changing behavior. Used together, these skills turn an AI coding agent from a code generator into a steadier engineering assistant.

For this guide, we reviewed code review and refactoring entries in the current Awesome Skills index, then checked official guidance from GitHub pull request reviews, Google's code review practices, GitHub code scanning, and the TypeScript Handbook. The goal is practical fit: which skill helps an agent review, repair, or simplify code without pretending automation replaces engineering judgment.

How We Picked the Shortlist

Searching for "review" or "refactor" catches a mix of useful and noisy results. Some skills are about academic review, design review, prompt review, or generic architecture. For this article, we focused on skills that directly help with software quality workflows:

reviewing local diffs or pull requests before merge
responding to GitHub review comments
fixing failed CI checks and reading logs
running lint, formatting, and static checks
improving TypeScript and JavaScript quality
planning behavior-preserving refactors
reviewing architecture, API shape, and boundaries
using tests to keep refactors honest

The strongest skills do not just say "find bugs." They tell the agent where to look, how to rank findings, when to ask for context, and how to avoid rewriting working code for style preference alone.

The Skills Worth Trying First

Skill area	Representative skill	Best fit	Watch out for
General code review	code-reviewer	Reviewing local changes or remote PRs for correctness, maintainability, and project conventions	Review output needs severity and evidence, not a long list of guesses
PR comment handling	gh-address-comments	Reading GitHub review comments and turning them into scoped fixes	Do not accept every comment blindly if it is technically weak
CI failure repair	gh-fix-ci	Inspecting GitHub Actions checks, logs, and failure context	CI fixes should address root cause, not only silence the failing check
Lint and style	lint-fixer	Running lint, fixing project style issues, and validating code against local rules	Formatting cleanup is useful, but it is not deep review
TypeScript quality	typescript-write	TypeScript/JavaScript code quality, local conventions, and refactoring inside a typed codebase	Project conventions matter more than generic TypeScript advice
Surgical refactoring	refactor	Extracting functions, improving type safety, reducing complexity, and keeping behavior stable	Refactors need tests or clear characterization before broad changes
Architecture review	architecture-patterns	Clean Architecture, Hexagonal Architecture, DDD, and backend boundaries	Architecture skills can overreach if the change is small
API design review	api-design-principles	Reviewing REST or GraphQL interfaces, versioning, pagination, and contract clarity	API changes need compatibility checks
Test-first guardrails	test-driven-development	Bug fixes, behavior changes, and refactors that need proof	Tests should target behavior, not implementation details

If you only install one category, start with a code review skill. If your team works through GitHub PRs, add comment-handling and CI skills next. If the codebase is TypeScript-heavy, pair review with linting and type-aware refactoring.

1. Review Skills Should Read the Diff, Not the Vibe

A useful review starts with the actual change. What files moved? Which behavior changed? Which public contracts are touched? Which tests were added or skipped? GitHub's pull request review docs frame review as a collaborative step before merge: reviewers can comment, suggest changes, approve, or request changes. That maps well to agent skills because the agent can inspect the diff and produce structured feedback before a human spends attention.

code-reviewer, code-review, and similar skills are best when they focus on concrete findings. A good review item should include the file, the risky line or behavior, why it matters, and what would make the change safer.

Weak review output sounds confident but vague: "consider improving error handling" or "this may have performance issues." Strong review output explains the failing path: this branch returns early before cleanup, this API path skips validation, or this memoized value can go stale after props change.

That is the difference between an agent that comments on style and an agent that helps protect production.

2. Review Comment Skills Help Close the Loop

Review does not end when comments are posted. Someone has to read the feedback, separate real issues from preferences, apply the right fixes, and avoid creating new problems. That is where gh-address-comments and receiving-code-review fit.

These skills are useful because PR feedback is often fragmented. One reviewer comments on naming, another on a missing test, a third on an API contract, and CI adds another failure. A comment-handling skill can gather the threads and turn them into a plan.

The important part is not obedience. Good code review practice requires technical judgment. If a comment is unclear, the agent should restate the concern and check the code. If a suggestion would break another requirement, it should say so.

This category helps the agent behave less like a defensive author and more like a maintainer working through feedback.

3. Refactoring Skills Need Behavior Boundaries

Refactoring is not rewriting. It is improving structure while preserving behavior. Without boundaries, a "clean up this file" request can change public behavior, delete edge cases, or replace a local convention with a generic pattern.

refactor is a good representative for surgical cleanup: extracting functions, improving names, breaking down oversized code, tightening types, and reducing complexity. typescript-write adds another layer for TypeScript and JavaScript projects because it grounds refactors in local coding standards.

The TypeScript Handbook notes that static typing and editor tooling can catch errors before runtime and support quick fixes, refactorings, navigation, and references. That is why type-aware refactoring skills can be more reliable than purely textual cleanup.

The right prompt is not "make this better." It is closer to: "preserve behavior, reduce this function's complexity, keep public exports stable, and run the existing checks."

4. Lint, CI, and Code Scanning Skills Are Review Inputs

Automated checks are not replacements for review, but they are useful inputs. lint-fixer handles a narrow job: run lint, fix rule failures, and validate again. gh-fix-ci is broader because it reads GitHub Actions checks and logs before proposing a fix.

Security and static analysis signals belong here too. GitHub's code scanning docs describe alerts that can come from CodeQL, third-party tools, or custom queries, and those alerts can include severity and the code path that triggered the issue. For an agent, that kind of signal is valuable because it makes the review less speculative.

The mistake is treating every automated failure as something to suppress. A lint rule can reveal a real bug. A failing test can expose a behavior change. A security alert can point to a dangerous data flow. The skill should explain the signal before editing the code.

Humans decide what matters, but agents can collect the evidence, make the smallest fix, and rerun the check.

5. Architecture and API Review Skills Catch Bigger Problems

Some review findings do not show up in a single line. A change may introduce a circular dependency, mix infrastructure into domain logic, create a confusing API contract, or add an endpoint that is hard to version later.

architecture-patterns and api-design-principles help with that layer. They are useful when a change touches boundaries: service design, REST or GraphQL contracts, data ownership, pagination, authorization flow, or a migration path.

Google's code review guidance lists design, functionality, complexity, tests, naming, comments, style, and documentation as review concerns. That is a useful reminder: review is not just bug hunting. It is also deciding whether future maintainers will understand the code.

Use architecture skills sparingly. If the PR changes one button label, architecture review is noise. If it changes API behavior or moves core state, architecture review can catch problems a line-by-line reviewer may miss.

A Practical Stack for Review and Refactoring

For most teams, a compact stack works better than installing every review-related skill:

code-reviewer for first-pass diff review.
gh-address-comments for handling PR feedback.
gh-fix-ci for failed checks and GitHub Actions logs.
lint-fixer for project style and lint rules.
typescript-write for TypeScript or JavaScript refactoring in a real codebase.
refactor for behavior-preserving cleanup.
architecture-patterns or api-design-principles when the change touches system boundaries.
test-driven-development when the refactor or bug fix needs proof before broad edits.

That order is deliberate. Review first. Fix comments second. Use CI and lint as evidence. Refactor only when the behavior boundary is clear. Bring in architecture review when the change is large enough to justify it.

Why Trust This Guide

This guide is based on current Awesome Skills entries that explicitly support code review, PR feedback, CI repair, linting, refactoring, TypeScript quality, API design, and architecture review. We also checked official GitHub, Google, and TypeScript documentation to keep the framing grounded in real engineering practice rather than generic AI productivity claims.

The lens is practical. A good code review or refactoring skill should make an agent more careful: inspect the diff, name the risk, preserve behavior, run checks, and leave a trail that a human reviewer can verify.

Final Takeaway

Code review and refactoring skills are where AI coding agents become more useful for real teams. The best ones do not just produce more code. They help decide whether the code should merge, what feedback is worth acting on, which checks are meaningful, and how to simplify a codebase without changing what it does.

If you want to explore more, start with the Awesome Skills collection, search for "code review", "refactor", "lint", "CI", "TypeScript", or "architecture", and read the actual SKILL.md instructions before installing. The name tells you the category. The workflow tells you whether the skill can help with a real pull request.