Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add rules/technickai/ai-coding-config/django-management-commandsgit clone --depth 1 https://github.com/TechNickAI/ai-coding-configWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00000 | $0.00442 |
| Opus 5 | $0.00000 | $0.00221 |
| Sonnet 5 | $0.00000 | $0.00088 |
| Haiku 4.5 | $0.00000 | $0.00044 |
Grade A, and why
django-management-commands scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Django Management Commands
Command Structure
Core structure
We put handle() as the first method. We keep logic inline within handle() by
default, splitting into helper functions only if they're reusable. Helper methods go
below handle(), never above. We include clear docstrings and help text for non-obvious
arguments.
Example Structure
from django.core.management.base import BaseCommand
class Command(BaseCommand):
"""Process pending orders and update inventory.
Analyzes order queue and updates stock levels accordingly.
"""
help = "Process pending orders"
def add_arguments(self, parser):
parser.add_argument(
'--dry-run',
action='store_true',
help='Show what would be done without making changes',
)
def handle(self, *args, **options):
"""Execute the command."""
dry_run = options['dry_run']
self.stdout.write(self.style.SUCCESS('Starting order processing...'))
# Command logic here...
processed_count = self.process_orders(dry_run)
self.stdout.write(
self.style.SUCCESS(f'Successfully processed {processed_count} orders')
)
def process_orders(self, dry_run):
"""Helper methods below handle()."""
# Helper logic here
pass
Handle Method Guidelines
Stats Dictionary Pattern
stats = {
"total": 0,
"processed": 0,
"skipped": {
"reason_1": 0,
"reason_2": 0,
},
"errors": [],
}
Return stats at the end for logging and monitoring.
Testing
Test Structure
We test with call_command, mock external services, and verify stats dictionary
structure.
from django.core.management import call_command
from io import StringIO
def test_command():
out = StringIO()
call_command('your_command', stdout=out)
assert 'Success' in out.getvalue()
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 90 lines · 0 tokens per session scan A 7da1fdb79377
django-management-commands is a cursor rule published in the GitHub repository TechNickAI/ai-coding-config (24 stars, last pushed 2mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 442 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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