Feature Request: Performance Insights Tool - Automated N+1 and Slow Query Detection #660
Description
Problem Statement
As Laravel developers, we frequently encounter performance bottlenecks that are difficult to spot during development without external tools. Common issues include:
- N+1 queries that slip through code reviews
- Slow database queries that degrade user experience
- Excessive query counts per request that impact scalability
- Memory usage issues that surface under load
Currently, detecting these requires:
- Installing and configuring Laravel Telescope or Debugbar
- Manually reviewing logs
- Running performance profilers
- Discovering issues late in development or production
Proposed Solution
Add a new Performance Insights Tool to Laravel Boost that provides automated performance analysis directly within the AI development workflow.
Capabilities
1. N+1 Query Detection
// Analyzes logs to detect patterns like:
// SELECT * FROM users WHERE id = 1
// SELECT * FROM posts WHERE user_id = 1
// SELECT * FROM posts WHERE user_id = 2
// SELECT * FROM posts WHERE user_id = 3
// ... repeated queries
// Suggests: User::with('posts')->get()2. Slow Query Analysis
- Identifies queries exceeding configurable thresholds (default: 100ms)
- Reports execution time, query content, and file location
- Prioritizes by impact (frequency × duration)
3. Query Count Monitoring
- Tracks total queries per endpoint/request
- Warns on excessive counts (e.g., >50 queries)
- Compares against application baselines
4. Memory Usage Insights
- Reports peak memory usage from logs
- Identifies memory-intensive operations
- Tracks trends over time
Tool Schema
#[Description('Analyze application performance and detect issues like N+1 queries, slow queries, and memory usage.')]
class PerformanceInsightsTool extends Tool
{
public function schema(JsonSchema $schema): array
{
return [
'type' => $schema->string()
->enum(['n+1', 'slow-queries', 'query-count', 'memory'])
->description('Type of performance analysis to run')
->required(),
'limit' => $schema->integer()
->description('Number of entries to analyze')
->default(10),
'threshold' => $schema->integer()
->description('Threshold for slow query detection (ms)')
->default(100),
];
}
}Benefits
For Developers
- ✅ Proactive issue detection during development
- ✅ Reduced debugging time
- ✅ Learn performance best practices through suggestions
- ✅ No additional tool installation needed
For Laravel Boost
- ✅ Natural fit with existing capabilities (
database-query,read-log-entries,last-error) - ✅ Differentiates Boost from generic AI coding tools
- ✅ Addresses a real pain point in Laravel development
- ✅ Aligns with Laravel's philosophy of developer happiness
For AI Agents
- ✅ Can proactively suggest optimizations
- ✅ Provides concrete, actionable insights
- ✅ Improves code quality automatically
Implementation Considerations
Architecture
- Leverage existing ReadLogEntries tool for log parsing
- Integrate with DatabaseQuery for query analysis
- Follow established MCP tool patterns
- Maintain read-only, non-destructive operations
Parsing Strategies
- Regex patterns for common N+1 signatures
- Laravel query log format parsing
- Configurable thresholds per project
- Support for custom log formats
Output Format
{
"type": "n+1_detected",
"severity": "high",
"location": "app/Http/Controllers/UserController.php:42",
"queries": 150,
"suggestion": "Use eager loading: User::with('posts', 'comments')->get()",
"example": "// Current: N+1 pattern\n// Suggested: Eager loading"
}