Does it support Django Rest Framework (DRF)?

Yes, it specifically analyzes DRF serializers for SerializerMethodFields and unoptimized ViewSet querysets that trigger excessive database hits.

Can it help with database indexing?

It identifies fields used in WHERE clauses and ORDER BY statements on large tables that lack db_index=True or Meta.indexes entries.

What makes this different from a standard linter?

This skill uses a 'research-first' approach, validating findings against data volume and call paths to ensure reported issues are real performance bottlenecks rather than stylistic preferences.

How does this skill detect N+1 queries?

It traces the data flow from Django views to templates or serializers to identify related model fields accessed inside loops without proper select_related or prefetch_related calls.

Does it suggest specific code improvements?

Yes, for every validated finding, it provides the specific line of code responsible and a corrected implementation using Django best practices.

Django Performance Auditor

Name: Django Performance Auditor
Author: sickn33

bysickn33

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31,721

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Gestión de Bases de Datos

Optimizes Django applications by identifying and validating N+1 queries, database bottlenecks, and inefficient ORM patterns.

The Django Performance Auditor skill empowers Claude to perform evidence-based performance audits on Django codebases. It systematically searches for critical database issues such as N+1 query patterns in views and serializers, memory-intensive unbounded querysets, and missing database indexes on large tables. Unlike generic linters, it focuses on provable impact by tracing data flow and verifying data volume before reporting, ensuring that developers receive high-priority, actionable recommendations rather than speculative micro-optimizations.

Características Principales

01Detection of N+1 query patterns in Django views and DRF serializers

02Identification of unbounded querysets that cause memory exhaustion and OOM errors

03Detection of inefficient write loops requiring bulk_create or bulk_update

04Evidence-based reporting with validated code locations and specific fix suggestions

05Analysis of missing database indexes for high-volume filter and sort operations

0631,721 GitHub stars

Casos de Uso

01Optimizing slow database-heavy endpoints and Django Rest Framework API responses

02Troubleshooting memory usage spikes and database lock contention in production

03Pre-deployment performance auditing for Django backend services

Características Principales

01Detection of N+1 query patterns in Django views and DRF serializers

02Identification of unbounded querysets that cause memory exhaustion and OOM errors

03Detection of inefficient write loops requiring bulk_create or bulk_update

04Evidence-based reporting with validated code locations and specific fix suggestions

05Analysis of missing database indexes for high-volume filter and sort operations

0631,721 GitHub stars

Casos de Uso

01Optimizing slow database-heavy endpoints and Django Rest Framework API responses

02Troubleshooting memory usage spikes and database lock contention in production

03Pre-deployment performance auditing for Django backend services