Dj Architecture
dvf/opinionated-django
Implement a Django feature following the opinionated architecture — prefixed ULID IDs, repository pattern, Pydantic DTOs, svcs service locator, project-scoped django-ninja API, Celery reliable…
Django + Celery async task patterns — configuration, task design, beat scheduling, retries, canvas workflows, monitoring, and testing.
$ npx skills add affaan-m/ECC --skill django-celery -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install affaan-m/ECC django-celery --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/django-celery .claude/skills/django-celery && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "django-celery" agent skill from https://github.com/affaan-m/ECC/tree/main/skills/django-celery into .claude/skills/django-celery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "django-celery", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/affaan-m/ECC/tree/main/skills/django-celeryType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add affaan-m/ECC --skill django-celery -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install affaan-m/ECC django-celery --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/django-celery .agents/skills/django-celery && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "django-celery" agent skill from https://github.com/affaan-m/ECC/tree/main/skills/django-celery into .agents/skills/django-celery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "django-celery", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add affaan-m/ECC --skill django-celery -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install affaan-m/ECC django-celery --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/django-celery .cursor/skills/django-celery && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "django-celery" agent skill from https://github.com/affaan-m/ECC/tree/main/skills/django-celery into .cursor/skills/django-celery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "django-celery", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/affaan-m/ECC.git --path skills/django-celery--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add affaan-m/ECC --skill django-celery -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install affaan-m/ECC django-celery --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/django-celery .gemini/skills/django-celery && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "django-celery" agent skill from https://github.com/affaan-m/ECC/tree/main/skills/django-celery into .gemini/skills/django-celery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "django-celery", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install affaan-m/ECC django-celeryInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add affaan-m/ECC --skill django-celery -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/django-celery .github/skills/django-celery && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "django-celery" agent skill from https://github.com/affaan-m/ECC/tree/main/skills/django-celery into .github/skills/django-celery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "django-celery", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add affaan-m/ECC --skill django-celery -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install affaan-m/ECC django-celery --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/django-celery .opencode/skills/django-celery && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "django-celery" agent skill from https://github.com/affaan-m/ECC/tree/main/skills/django-celery into .opencode/skills/django-celery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "django-celery", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
django-celeryDjango + Celery async task patterns — configuration, task design, beat scheduling, retries, canvas workflows, monitoring, and testing.
Django Celery is an agent skill from affaan-m/ECC. Django + Celery async task patterns — configuration, task design, beat scheduling, retries, canvas workflows, monitoring, and testing. Use when adding background jobs, scheduled tasks, or async processing to a Django app.
Its SKILL.md is about 3.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Backend & APIs, covering Background jobs and Backend development. It works with Django. The repository describes itself as: The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond. The licence is MIT.
Read from SKILL.md and the folder at commit 2d515e4. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
pipredis-cliFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use pip, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Django Celery loads about 3.3k tokens when it runs. Until then it costs about 59 tokens; SKILL.md has 226 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from affaan-m/ECC at commit 2d515e4, republished under its MIT licence (© affaan-m). 226 words, ~3,279 tokens.
.claude/skills/django-celery/SKILL.md (or your agent's skills folder).Production-grade patterns for background task processing in Django using Celery with Redis or RabbitMQ.
pip install 'celery[redis]' django-celery-results django-celery-beatcelery.py — App Entrypoint# config/celery.py
import os
from celery import Celery
os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'config.settings.development')
app = Celery('myproject')
app.config_from_object('django.conf:settings', namespace='CELERY')
app.autodiscover_tasks() # Discovers tasks.py in each INSTALLED_APP
@app.task(bind=True, ignore_result=True)
def debug_task(self):
print(f'Request: {self.request!r}')# config/__init__.py
from .celery import app as celery_app
__all__ = ('celery_app',)# config/settings/base.py
# Broker (Redis recommended for production)
CELERY_BROKER_URL = env('CELERY_BROKER_URL', default='redis://localhost:6379/0')
CELERY_RESULT_BACKEND = env('CELERY_RESULT_BACKEND', default='django-db')
# Serialization
CELERY_ACCEPT_CONTENT = ['json']
CELERY_TASK_SERIALIZER = 'json'
CELERY_RESULT_SERIALIZER = 'json'
# Task behavior
CELERY_TASK_TRACK_STARTED = True
CELERY_TASK_TIME_LIMIT = 30 * 60 # Hard limit: 30 min
CELERY_TASK_SOFT_TIME_LIMIT = 25 * 60 # Soft limit: sends SoftTimeLimitExceeded
CELERY_WORKER_PREFETCH_MULTIPLIER = 1 # Prevent worker hoarding long tasks
CELERY_TASK_ACKS_LATE = True # Re-queue on worker crash
# Result persistence
CELERY_RESULT_EXPIRES = 60 * 60 * 24 # Keep results 24 hours
# Beat scheduler (for periodic tasks)
CELERY_BEAT_SCHEDULER = 'django_celery_beat.schedulers:DatabaseScheduler'
# Installed apps
INSTALLED_APPS += [
'django_celery_results',
'django_celery_beat',
]# Start worker (development)
celery -A config worker --loglevel=info
# Start beat scheduler (periodic tasks)
celery -A config beat --loglevel=info --scheduler django_celery_beat.schedulers:DatabaseScheduler
# Combined worker + beat (dev only, never production)
celery -A config worker --beat --loglevel=info
# Production: multiple workers with concurrency
celery -A config worker --loglevel=warning --concurrency=4 -Q default,high_priority# apps/notifications/tasks.py
from celery import shared_task
import logging
logger = logging.getLogger(__name__)
@shared_task(name='notifications.send_welcome_email')
def send_welcome_email(user_id: int) -> None:
"""Send welcome email to newly registered user."""
from apps.users.models import User
from apps.notifications.services import EmailService
try:
user = User.objects.get(pk=user_id)
except User.DoesNotExist:
logger.warning('send_welcome_email: user %s not found', user_id)
return # Idempotent — do not raise, task already impossible to complete
EmailService.send_welcome(user)
logger.info('Welcome email sent to user %s', user_id)@shared_task(
bind=True,
name='integrations.sync_to_crm',
max_retries=5,
default_retry_delay=60, # seconds before first retry
autoretry_for=(ConnectionError, TimeoutError),
retry_backoff=True, # exponential backoff
retry_backoff_max=600, # cap at 10 minutes
retry_jitter=True, # randomise to avoid thundering herd
)
def sync_contact_to_crm(self, contact_id: int) -> dict:
"""Sync contact to external CRM with retry on transient failures."""
from apps.crm.services import CRMClient
try:
result = CRMClient().sync(contact_id)
return result
except CRMClient.RateLimitError as exc:
# Specific retry delay from response header
raise self.retry(exc=exc, countdown=int(exc.retry_after))Design tasks so they can safely run multiple times with the same inputs:
@shared_task(name='orders.mark_shipped')
def mark_order_shipped(order_id: int, tracking_number: str) -> None:
"""Mark order as shipped — safe to run multiple times."""
from apps.orders.models import Order
updated = Order.objects.filter(
pk=order_id,
status=Order.Status.PROCESSING, # Guard: only update if not already shipped
).update(
status=Order.Status.SHIPPED,
tracking_number=tracking_number,
)
if not updated:
logger.info('mark_order_shipped: order %s already shipped or not found', order_id)from celery.exceptions import SoftTimeLimitExceeded
@shared_task(
bind=True,
name='reports.generate_pdf',
soft_time_limit=120,
time_limit=150,
)
def generate_pdf_report(self, report_id: int) -> str:
"""Generate PDF report with graceful timeout handling."""
from apps.reports.services import PDFGenerator
try:
path = PDFGenerator.build(report_id)
return path
except SoftTimeLimitExceeded:
# Clean up partial files before hard kill
PDFGenerator.cleanup(report_id)
raisefrom datetime import timedelta
from django.utils import timezone
# Fire and forget (async)
send_welcome_email.delay(user.pk)
# Schedule in the future
send_reminder.apply_async(args=[user.pk], countdown=3600) # 1 hour from now
send_reminder.apply_async(args=[user.pk], eta=timezone.now() + timedelta(days=1))
# Apply with queue routing
sync_contact_to_crm.apply_async(args=[contact.pk], queue='high_priority')
# Run synchronously (tests / debugging only)
result = generate_pdf_report.apply(args=[report.pk])# config/settings/base.py
from celery.schedules import crontab
CELERY_BEAT_SCHEDULE = {
'cleanup-expired-sessions': {
'task': 'users.cleanup_expired_sessions',
'schedule': crontab(hour=2, minute=0), # 2am daily
},
'sync-inventory': {
'task': 'products.sync_inventory',
'schedule': 60.0, # every 60 seconds
},
'weekly-digest': {
'task': 'notifications.send_weekly_digest',
'schedule': crontab(day_of_week='monday', hour=8, minute=0),
},
}# Manage periodic tasks from Django admin or code
from django_celery_beat.models import PeriodicTask, CrontabSchedule
import json
schedule, _ = CrontabSchedule.objects.get_or_create(
hour='*/6', minute='0',
timezone='UTC',
)
PeriodicTask.objects.update_or_create(
name='Sync inventory every 6 hours',
defaults={
'crontab': schedule,
'task': 'products.sync_inventory',
'args': json.dumps([]),
'enabled': True,
}
)from celery import chain, group, chord
# Chain: run tasks sequentially, passing results
pipeline = chain(
fetch_data.s(source_id),
transform_data.s(), # receives fetch_data result as first arg
load_to_warehouse.s(),
)
pipeline.delay()
# Group: run tasks in parallel
parallel = group(
send_welcome_email.s(user_id)
for user_id in new_user_ids
)
parallel.delay()
# Chord: parallel tasks + callback when all complete
result = chord(
group(process_chunk.s(chunk) for chunk in data_chunks),
aggregate_results.s(), # called with list of chunk results
)
result.delay()# apps/core/tasks.py
from celery.signals import task_failure
@task_failure.connect
def on_task_failure(sender, task_id, exception, args, kwargs, traceback, einfo, **kw):
"""Log all task failures to Sentry / alerting."""
import sentry_sdk
with sentry_sdk.new_scope() as scope:
scope.set_context('celery', {
'task': sender.name,
'task_id': task_id,
'args': args,
'kwargs': kwargs,
})
sentry_sdk.capture_exception(exception)# Route failed tasks to dead-letter queue after max retries
@shared_task(
bind=True,
max_retries=3,
name='payments.charge_card',
)
def charge_card(self, order_id: int) -> None:
from apps.payments.models import Order, FailedCharge
try:
_do_charge(order_id)
except Exception as exc:
if self.request.retries >= self.max_retries:
# Persist to dead-letter table for manual review
FailedCharge.objects.create(
order_id=order_id,
error=str(exc),
task_id=self.request.id,
)
return # Don't raise — task is permanently failed
raise self.retry(exc=exc)# tests/test_tasks.py
import pytest
from unittest.mock import patch, MagicMock
from apps.notifications.tasks import send_welcome_email
class TestSendWelcomeEmail:
@pytest.mark.django_db
def test_sends_email_to_existing_user(self, user):
with patch('apps.notifications.services.EmailService') as mock_email:
send_welcome_email(user.pk)
mock_email.send_welcome.assert_called_once_with(user)
@pytest.mark.django_db
def test_skips_missing_user_gracefully(self):
"""Should not raise when user is deleted between enqueue and execute."""
send_welcome_email(99999) # Non-existent user — must not raise# config/settings/test.py
CELERY_TASK_ALWAYS_EAGER = True # Run tasks synchronously in tests
CELERY_TASK_EAGER_PROPAGATES = True # Re-raise exceptions from tasks
# tests/test_integration.py
@pytest.mark.django_db
def test_registration_triggers_welcome_email(client):
with patch('apps.notifications.services.EmailService') as mock_email:
response = client.post('/api/users/', {
'email': 'new@example.com',
'password': 'strongpass123',
})
assert response.status_code == 201
mock_email.send_welcome.assert_called_once()@pytest.mark.django_db
def test_task_retries_on_connection_error():
with patch('apps.crm.services.CRMClient.sync') as mock_sync:
mock_sync.side_effect = ConnectionError('timeout')
with pytest.raises(ConnectionError):
sync_contact_to_crm.apply(args=[1], throw=True)
assert mock_sync.call_count == 1 # First attempt only when eager# Inspect active workers and queues
celery -A config inspect active
celery -A config inspect stats
celery -A config inspect reserved
# Check queue lengths (Redis)
redis-cli llen celery
# Flower: web-based real-time monitor
pip install flower
celery -A config flower --port=5555# BAD: Passing model instances — they may be stale by execution time
send_welcome_email.delay(user) # Never pass ORM objects
send_welcome_email.delay(user.pk) # Always pass PKs
# BAD: Calling tasks synchronously in production views
result = generate_report.apply() # Blocks the request thread
# BAD: Non-idempotent task without guards
@shared_task
def charge_and_fulfill(order_id):
order.charge() # May charge twice if task retries!
order.fulfill()
# GOOD: Idempotent with status guard
@shared_task
def charge_and_fulfill(order_id):
order = Order.objects.select_for_update().get(pk=order_id)
if order.status != Order.Status.PENDING:
return # Already processed
order.charge()
order.fulfill()| Check | Setting |
|---|---|
| Worker restarts on crash | supervisord or systemd unit |
CELERY_TASK_ACKS_LATE = True | Re-queue tasks on worker crash |
CELERY_WORKER_PREFETCH_MULTIPLIER = 1 | Fair distribution of long tasks |
| Separate queues per priority | -Q default,high_priority,low_priority |
CELERY_TASK_SOFT_TIME_LIMIT set | Graceful timeout before hard kill |
| Sentry integration | Capture all task_failure signals |
| Flower or other monitor | Visibility into queue depths |
| Beat runs on single node only | Prevents duplicate scheduled task execution |
django-patterns — ORM, service layer, and project structuredjango-tdd — Testing Django models, views, and servicespython-testing — pytest configuration and fixtures© affaan-m, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/django-celery of affaan-m/ECC.
Open the folder on GitHubat commit 2d515e4
We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in affaan-m/ECC, which our catalogue first saw on October 7, 2026.
Django Celery next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Django Celery this skillaffaan-m/ECC | 277k | 1 repos | ~3.3k | Automated safety check: Pass | MIT | |
| Dj Architecturedvf/opinionated-django | 109 | — | ~4k | Automated safety check: Notes | MIT | |
| Django Celery Expertvintasoftware/django-ai-plugins | 153 | — | ~1.2k | Automated safety check: Pass | None | |
| Sentry Python SDKgetsentry/sentry-for-ai | 268 | — | ~4.1k | Automated safety check: Pass | Apache-2.0 | |
| Django Prodavila7/claude-code-templates | 33k | 8 repos | ~1.7k | Automated safety check: Pass | MIT | |
| Dj Servicesdvf/opinionated-django | 109 | — | ~3k | Automated safety check: Notes | MIT |
dvf/opinionated-django
Implement a Django feature following the opinionated architecture — prefixed ULID IDs, repository pattern, Pydantic DTOs, svcs service locator, project-scoped django-ninja API, Celery reliable…
vintasoftware/django-ai-plugins
Expert Django Celery guidance for asynchronous task processing.
getsentry/sentry-for-ai
Full Sentry SDK setup for Python. An agent skill from getsentry/sentry-for-ai.
davila7/claude-code-templates
Master Django 5.x with async views, DRF, Celery, and Django Channels.
dvf/opinionated-django
Structure Django business logic as plain services that receive their dependencies via constructor injection, and wire them through an svcs registry so they can be resolved anywhere — views, Celery…
dvf/opinionated-django
Add reliable signals (async side-effects via Celery) to a Django feature.
affaan-m/ECC
Audits your installed Claude skills and commands for quality, with a quick mode for recently changed skills and a full mode that evaluates all of them through subagents.
affaan-m/ECC
Ingests, indexes, searches, edits and monitors video, audio and live streams through the VideoDB Python SDK, returning stream links, clips and timestamps.
affaan-m/ECC
Route broad documentation-governance requests to existing ECC skills and run an opt-in, read-only audit of mapped documentation roles, links, ADR indexes, and evidence references.
affaan-m/ECC
Scans installed skills for principles that recur across them and proposes rule-file changes: append, revise, add a section, create a file or leave as covered.
affaan-m/ECC
Builds DRAFT counterparty agreements from one markdown template and a small JSON spec per party, with clauses picked by the party's role.
affaan-m/ECC
Set an ECC-specific frontend design direction for production UI work.
Works with
Categories
Django + Celery async task patterns — configuration, task design, beat scheduling, retries, canvas workflows, monitoring, and testing. Django Celery is an agent skill from affaan-m/ECC. Django + Celery async task patterns — configuration, task design, beat scheduling, retries, canvas workflows, monitoring, and testing.
Django Celery fits situations like: adding background jobs; scheduled tasks; async processing to a Django app.
Run `npx skills add affaan-m/ECC --skill django-celery -a claude-code`. Or copy the skill folder (skills/django-celery in affaan-m/ECC) into .claude/skills/django-celery in your project. Claude Code loads it when a task matches its description.
Run `npx skills add affaan-m/ECC --skill django-celery -a codex`. Or copy the skill folder (skills/django-celery in affaan-m/ECC) into .agents/skills/django-celery in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add affaan-m/ECC --skill django-celery -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/django-celery, .gemini/skills/django-celery, .github/skills/django-celery and .opencode/skills/django-celery in your project.
Going by SKILL.md and its folder, Django Celery needs the command-line tools its instructions call (pip and redis-cli). Our summary lists: Python 3.
SKILL.md contains no URLs. Its commands use pip, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Django Celery is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.3k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Django Celery: Dj Architecture (dvf/opinionated-django, 109 stars), Django Celery Expert (vintasoftware/django-ai-plugins, 153 stars), Sentry Python SDK (getsentry/sentry-for-ai, 268 stars) and Django Pro (davila7/claude-code-templates, 33k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
affaan-m (a GitHub user) maintains it in affaan-m/ECC, which has 276,673 GitHub stars. The repository holds 683 skills in this directory. The repository was last updated on October 11, 2026.
Source: affaan-m/ECC on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.