Terminal.skills
Skills/performance-reviewer
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performance-reviewer

Review code for performance issues and optimization opportunities. Use when someone needs to check for N+1 queries, unnecessary re-renders, memory leaks, inefficient algorithms, missing indexes, or bundle size regressions. Trigger words: performance review, slow query, N+1, memory leak, bundle size, latency, optimization, re-render, Big O.

#performance#optimization#code-review#profiling
terminal-skillsv1.0.0
Works with:claude-codeopenai-codexgemini-clicursor
Source

Usage

$
✓ Installed performance-reviewer v1.0.0

Getting Started

  1. Install the skill using the command above
  2. Open your AI coding agent (Claude Code, Codex, Gemini CLI, or Cursor)
  3. Reference the skill in your prompt
  4. The AI will use the skill's capabilities automatically

Example Prompts

  • "Review the open pull requests and summarize what needs attention"
  • "Generate a changelog from the last 20 commits on the main branch"

Documentation

Overview

This skill analyzes code changes for performance regressions and optimization opportunities. It catches common issues like N+1 database queries, unnecessary re-renders in React components, missing database indexes, unoptimized loops, and bundle size increases before they reach production.

Instructions

Analyzing a Diff or PR

  1. Get the diff: git diff main...HEAD or git diff <base>...<head>
  2. For each changed file, evaluate against these performance categories:

Database & Queries:

  • Look for queries inside loops (N+1 pattern)
  • Check for missing WHERE clauses or full table scans
  • Identify missing indexes on columns used in WHERE, JOIN, or ORDER BY
  • Flag SELECT * when only specific columns are needed
  • Watch for unbounded queries without LIMIT

Frontend & Rendering:

  • React: Check for missing useMemo/useCallback on expensive computations passed as props
  • Look for state updates that trigger unnecessary re-renders of large component trees
  • Flag inline object/array creation in render (creates new reference every render)
  • Check for large bundle imports (import moment → suggest dayjs)

Algorithm & Data Structures:

  • Flag O(n²) or worse algorithms when O(n log n) alternatives exist
  • Look for repeated array searches that should use a Set or Map
  • Identify string concatenation in loops (suggest StringBuilder/join)

Memory & Resources:

  • Check for missing cleanup in useEffect (event listeners, intervals, subscriptions)
  • Look for growing arrays/objects that are never trimmed
  • Flag missing connection pool limits or unclosed file handles

Network & I/O:

  • Identify sequential API calls that could be parallelized (Promise.all)
  • Check for missing pagination on list endpoints
  • Flag missing caching for expensive or repeated operations

Output Format

For each issue found, report:

  • File and line number
  • Category (Database, Frontend, Algorithm, Memory, Network)
  • Severity (Critical, Warning, Info)
  • What's wrong (specific description)
  • Suggested fix (concrete code suggestion)

Severity Guidelines

  • Critical: Will cause visible degradation in production (N+1 in a loop, O(n²) on large datasets, memory leak)
  • Warning: May cause issues at scale (missing index, unnecessary re-renders, sequential API calls)
  • Info: Optimization opportunity, not urgent (bundle size suggestion, minor refactor)

Examples

Example 1: N+1 Query Detection

Input diff:

python
# api/views.py
def list_orders(request):
    orders = Order.objects.filter(user=request.user)
    result = []
    for order in orders:
        items = OrderItem.objects.filter(order=order)  # ← query per order
        result.append({
            "id": order.id,
            "total": order.total,
            "items": [{"name": i.product.name, "qty": i.quantity} for i in items]
        })
    return JsonResponse(result, safe=False)

Output:

🔴 Critical — Database N+1 Query
  File: api/views.py:5-8
  Issue: OrderItem query executes once per order, plus each i.product.name
         triggers another query. For 50 orders with 3 items each = 201 queries.
  Fix: Use select_related and prefetch_related:
    orders = Order.objects.filter(user=request.user).prefetch_related(
        Prefetch('items', queryset=OrderItem.objects.select_related('product'))
    )
  Result: Reduces to 3 queries regardless of order count.

Example 2: React Re-render Issue

Input diff:

jsx
function UserList({ users, onSelect }) {
  return (
    <div>
      {users.map(user => (
        <UserCard
          key={user.id}
          user={user}
          style={{ padding: 16, margin: 8 }}
          onClick={() => onSelect(user.id)}
        />
      ))}
    </div>
  );
}

Output:

🟡 Warning — Unnecessary Re-renders
  File: components/UserList.jsx:6-7
  Issue: Inline object `style={{ padding: 16, margin: 8 }}` and arrow function
         `() => onSelect(user.id)` create new references every render, causing
         all UserCard components to re-render even when users haven't changed.
  Fix:
    const cardStyle = useMemo(() => ({ padding: 16, margin: 8 }), []);
    const handleClick = useCallback((id) => onSelect(id), [onSelect]);
    // Then: style={cardStyle} onClick={() => handleClick(user.id)}
  Impact: With 100+ users, prevents ~100 unnecessary DOM diffing operations per parent render.

Guidelines

  • Focus on issues introduced by the diff, not pre-existing problems
  • Prioritize Critical issues — don't bury them in a list of Info suggestions
  • Always provide concrete fix suggestions, not just "optimize this"
  • Consider the scale: an O(n²) loop on a 5-element array is fine; on user-generated data it's not
  • When suggesting caching, specify what to cache and invalidation strategy
  • Don't flag micro-optimizations that harm readability for negligible gain

Information

Version
1.0.0
Author
terminal-skills
Category
Development
License
Apache-2.0