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 CHENyiru3/AI-Skills-Collections --skill code-qualitygit clone --depth 1 https://github.com/CHENyiru3/AI-Skills-CollectionsWrote 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/chenyiru3/ai-skills-collections/code-quality)<a href="https://agentmods.dev/skills/chenyiru3/ai-skills-collections/code-quality"><img src="https://agentmods.dev/badge/skills/chenyiru3/ai-skills-collections/code-quality/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/chenyiru3/ai-skills-collections/code-quality"><img src="https://agentmods.dev/badge/skills/chenyiru3/ai-skills-collections/code-quality.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00071 | $0.00937 |
| Opus 5.5 | $0.00028 | $0.00375 |
| Sonnet 5.5 | $0.00014 | $0.00187 |
| Haiku 4.5 | $0.00007 | $0.00094 |
Grade A, and why
improving-python-code-quality scanned grade A with 1 finding 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 6d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
def fetch(url: str, timeout: int | None = None) -> bytes: ... How it starts
The opening of the file, as written. The whole thing — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Python Code Quality
Quick Reference
| Tool | Purpose | Command |
|---|---|---|
| ruff | Lint + format | ruff check src && ruff format src |
| mypy | Type check | mypy src |
Ruff Configuration
Minimal config in pyproject.toml:
[tool.ruff]
line-length = 88
target-version = "py310"
[tool.ruff.lint]
select = ["E", "W", "F", "I", "B", "C4", "UP"]
For full configuration options, see RUFF_CONFIG.md.
MyPy Configuration
[tool.mypy]
python_version = "3.10"
disallow_untyped_defs = true
warn_return_any = true
For strict settings and overrides, see MYPY_CONFIG.md.
Type Hints Patterns
# Basic
def process(items: list[str]) -> dict[str, int]: ...
# Optional
def fetch(url: str, timeout: int | None = None) -> bytes: ...
# Callable
def apply(func: Callable[[int], str], value: int) -> str: ...
# Generic
T = TypeVar("T")
def first(items: Sequence[T]) -> T | None: ...
For protocols and advanced patterns, see TYPE_PATTERNS.md.
Common Anti-Patterns
# Bad: Mutable default
def process(items: list = []): # Bug!
...
# Good: None default
def process(items: list | None = None):
items = items or []
...
# Bad: Bare except
try:
...
except:
pass
# Good: Specific exception
try:
...
except ValueError as e:
logger.error(e)
Pythonic Idioms
# Iteration
for item in items: # Not: for i in range(len(items))
for i, item in enumerate(items): # When index needed
# Dictionary access
value = d.get(key, default) # Not: if key in d: value = d[key]
# Context managers
with open(path) as f: # Not: f = open(path); try: finally: f.close()
# Comprehensions (simple only)
squares = [x**2 for x in numbers]
Module Organization
src/my_library/
├── __init__.py # Public API exports
├── _internal.py # Private (underscore prefix)
├── exceptions.py # Custom exceptions
├── types.py # Type definitions
└── py.typed # Type hint marker
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 6d ago First seen · 136 lines · 71 tokens per session scan A 86458d38ad93
improving-python-code-quality is a skill published in the GitHub repository CHENyiru3/AI-Skills-Collections (1 stars, last pushed 7d ago), licensed MIT. It adds 71 tokens to every session and 937 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-02.
Other skills, from other repositories
mcore-linting-and-formatting
Linting and formatting for Megatron-LM. Covers running autoformat.sh, tools (ruff, black, isort, pylint, mypy), and code style rules.
splitting-oversized-modules
Split an oversized Python module (a thousand-plus-line logic.py, models.py, api.py, or its test file) into a package of one module per concern, mechanically and provably without changing behavior. Use on a request to split / break up / decompose a god module or move functions out of one, once a human has agreed to…
splitting-oversized-modules
Split an oversized Python module (a thousand-plus-line logic.py, models.py, api.py, or its test file) into a package of one module per concern, mechanically and provably without changing behavior. Use on a request to split / break up / decompose a god module or move functions out of one, once a human has agreed to…
plankton-code-quality
Write-time code quality enforcement using Plankton — auto-formatting, linting, and Claude-powered fixes on every file edit via hooks.
coding.make_function_private
Identify private or public functions in a file and rename with underscore.
coding_qa.review
Review Python files for bugs, suggest fixes, and provide test cases.