review-react-best-practices
Skill337 starsChanged 10 months agoMITView on GitHub
Review or refactor React / Next.js code for performance and reliability using a prioritized rule library (waterfalls, bundle size, server/client data fetching, re-renders, rendering). Use when writing React components, Next.js pages (App Router), optimizing bundle size, improving performance, or doing a React/Next.js performance review.
In this repository40 other files it gives its agents.
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The file
We split this skill into the rules it gives an agent
4 rules. About 0 are common, 3 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 8
Use this skill to turn “React feels slow / Next.js page is heavy / too many requests” into a repeatable, prioritized review.
- Distinctive: line 28
Only then go to HIGH (server patterns + serialization).
- Distinctive: line 56
When reviewing code, output:
- Distinctive: line 70
If running in a Ship Faster run directory, persist the report to:
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
React Best Practices Review (Performance-First)
Use this skill to turn “React feels slow / Next.js page is heavy / too many requests” into a repeatable, prioritized review.
This skill is intentionally built like a rule library:
SKILL.md: how to review + how to search rulesreferences/rules/*: one rule per file (taggable, sortable, easy to evolve)
When to apply
Use when:
- Building or refactoring React components
- Working in Next.js (App Router) on RSC boundaries, Server Actions, data fetching
- Reviewing PRs for performance regressions
- Bundle size increases / slow HMR / cold start issues
- UI jank / unnecessary re-renders / hydration issues
Review method (prioritized)
- Start with CRITICAL rules first (waterfalls + bundle).
- Only then go to HIGH (server patterns + serialization).
- Then MEDIUM (re-render + rendering).
- Then LOW-MEDIUM micro-optimizations (JS hot paths).
Section ordering lives in: references/rules/_sections.md
How to use the rules efficiently
Search by keyword
rg -n "waterfall|Promise\\.all|defer await" references/rules
rg -n "barrel|optimizePackageImports|dynamic" references/rules
rg -n "cache\\(|React\\.cache|serialization|RSC" references/rules
rg -n "memo\\(|useMemo|useCallback|dependencies" references/rulesSearch by tag
Each rule has tags: in YAML frontmatter.
rg -n "tags:.*bundle" references/rules
rg -n "tags:.*rerender" references/rulesOutput format (recommended)
When reviewing code, output:
- Summary (1 paragraph)
- Critical fixes (must-fix, biggest wins)
- High impact (should-fix)
- Medium / Low (nice-to-have)
For each issue include:
- Rule name (and file under
references/rules/) - Location (
path:line) - Why it matters (latency / bundle / CPU / UX)
- Minimal fix direction (prefer small diffs)
If running in a Ship Faster run directory, persist the report to:
run_dir/evidence/react-best-practices-review.md
Rule library
Rules live in:
references/rules/- Rule template:
references/rules/_template.md
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

