Template Linting and Auto-Formatting for Django and Jinja Repositories
Uses djLint to scan Django, Jinja, Nunjucks, Twig, and HTML templates for indentation problems, malformed tags, and style drift, then optionally rewrites them into a consistent format. This is for agents that need to clean and validate template-heavy repos before review or release, not for general web framework setup.
npx skills add agentskillexchange/skills --skill template-linting-auto-formatting-django-jinja-repositories
This ASE entry turns djLint into a bounded repository hygiene skill rather than a generic package card. The agent behavior is simple and useful: inspect template files, run djLint against the relevant directories, surface concrete formatting and lint failures, and, when allowed, apply the formatter so the repository comes back into a stable and reviewable state. djLint supports Django templates, Jinja, Nunjucks, Twig, Handlebars, Go templates, and plain HTML, which makes it practical for mixed frontend and server-rendered projects where markup conventions drift over time.
What this skill actually does
The right time to invoke this skill is when a user needs an agent to clean up template files, catch broken tag structure, normalize indentation, or enforce template style before a pull request, release, migration, or large refactor. It is especially useful after AI-assisted code generation or multi-author edits, when templates often accumulate inconsistent spacing, duplicate constructs, or hard-to-read blocks. The agent returns a lint report, a list of touched files, and optionally the formatted output that can be committed or reviewed.
The scope boundary matters. This skill is not a listing for djLint as a product, and it is not a generic web framework entry. Its job-to-be-done is narrowly about template linting and auto-formatting inside an existing repo. It does not create applications, serve pages, or replace the framework’s own runtime features. Integration points are straightforward: pre-commit hooks, CI pipelines, local developer scripts, Python virtualenvs, and review bots that comment on changed templates. Upstream evidence is strong, with an active official repository, a published PyPI package, a live docs site, tags, and recent maintenance.