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 skills add saaspegasus/django-boilerplate --skill fix-typesgit clone --depth 1 https://github.com/saaspegasus/django-boilerplateWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/saaspegasus/django-boilerplate/fix-types)<a href="https://agentmods.dev/skills/saaspegasus/django-boilerplate/fix-types"><img src="https://agentmods.dev/badge/skills/saaspegasus/django-boilerplate/fix-types.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
What 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 5.1 | $0.00013 | $0.00731 |
| Opus 5 | $0.00006 | $0.00365 |
| Sonnet 5 | $0.00003 | $0.00146 |
| Haiku 4.5 | $0.00001 | $0.00073 |
Grade A, and why
fix-types 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 8d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- fix-types — 100% identical, 0 lines differ
What it actually says
Your task
To fix types, do the following.
- First run the type checker to see what the issues are:
uv run mypy . - Group the errors you find in to logical buckets.
- For each bucket of errors, go through the errors one at a time, tell me the fix you want to apply, and then ask if I have any questions or suggestions before proceeding.
- Only once I approve, apply the fix and move onto the next error in the bucket.
- Once you've completed a bucket, ask me if I'd like to move on to the next bucket.
Prefer cast() over type: ignore
When mypy can't infer the correct type, prefer using cast() over # type: ignore:
# Preferred - documents the expected type
choices = cast(list[tuple[str, str]], field.choices)
# Avoid when cast is possible - just silences the error
choices = list(field.choices) # type: ignore[arg-type]
Why: cast() explicitly documents what type you expect, making the code more readable and maintainable. It also doesn't silence other potential errors on the same line.
Prefer proper errors over assertions for null checks
When adding null checks to satisfy mypy, prefer raising proper exceptions over using assert:
# Preferred - proper error handling
if obj.related_field is None:
raise ValueError("Object must have a related field")
result = obj.related_field.some_method()
# Avoid - assertions can be disabled with -O flag
assert obj.related_field is not None
result = obj.related_field.some_method()
Why: Assertions can be disabled in production with python -O, making them unreliable for runtime validation. Proper exceptions ensure the check always runs and provides better error handling.
When using type: ignore, add a comment
If type: ignore is necessary (e.g., mypy limitation with valid code), always add a short explanation:
# Good - explains why the ignore is needed
self.tier = tier # type: ignore[misc] # mypy can't handle Enum tuple values with custom __init__
# Bad - no explanation
self.tier = tier # type: ignore[misc]
Type Hints for Django Lazy Translation Strings
When using type hints with Django's lazy translation strings (gettext_lazy), use the following pattern to avoid mypy errors while keeping the code working in production (where django-stubs-ext is not installed):
from __future__ import annotations # Must be the first import
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from django_stubs_ext import StrOrPromise
# Then use StrOrPromise in type hints
def my_function(name: StrOrPromise) -> StrOrPromise: ...
class MyData:
title: StrOrPromise
description: StrOrPromise
Why this pattern:
from __future__ import annotationsmakes type annotations strings at runtime (not evaluated)if TYPE_CHECKING:ensures the import only happens during type checking, not at runtimedjango-stubs-extis a dev dependency and won't be available in production- This pattern allows both regular strings and lazy translation strings to be accepted
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.
- 8d ago First seen · 93 lines · 13 tokens per session scan A ecbd71f6349a
fix-types is a skill published in the GitHub repository saaspegasus/django-boilerplate (168 stars, last pushed today), licensed MIT. It adds 13 tokens to every session and 731 once invoked, about $0.0001 per session on Opus 5. 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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