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carlos-ASG AI Skills

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Browse published AI skills maintained by carlos-ASG. Compare skill descriptions and follow each source repository for setup instructions.

Author statistics

Indexed skills

7

Repository stars across indexed skills

0

Repository forks

0

Average repository stars per indexed skill

0

Repository stars may repeat across skills from the same repository.

7 skills

Browse skills

GitHub

django-health

carlos-ASG

Django health check configuration and patterns using django-health-check for system monitoring, Docker healthchecks, and Kubernetes probes. Trigger: When implementing health checks, monitoring endpoints, or rea...

GitHub

django-ratelimit

carlos-ASG

Django rate limiting patterns using django-ratelimit with Redis backend for protecting views from abuse and spam. Trigger: When implementing rate limiting, spam protection, or throttling in Django views.

GitHub

python

carlos-ASG

Python modern patterns and best practices using type hints, dataclasses, and Protocol-based design. Trigger: When implementing or refactoring Python in .py files (type hints, dataclasses, protocols, enums, type...

GitHub

django-htmx

carlos-ASG

HTMX and django-htmx integration patterns for building modern, interactive Django applications without complex JavaScript. Trigger: When implementing interactive features, partial page updates, or dynamic forms...

GitHub

chartjs-graphs

carlos-ASG

Chart.js integration patterns for creating interactive statistical graphs in Django templates. Covers HTML setup, data injection, and JavaScript chart rendering with datalabels plugin.

GitHub

django-orm

carlos-ASG

Django ORM patterns and best practices with QuerySets, managers, migrations, and django-tenants database operations. Trigger: When working with Django models, queries, database operations, or migrations.

GitHub

django

carlos-ASG

Django modern patterns and best practices for views, forms, URL routing, and management commands. Trigger: When implementing or refactoring Django views, forms, URLs, or commands.

The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.