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 skills/matteocervelli/llms/python-quality-checkernpx skills add matteocervelli/llms --skill python-quality-checkergit clone --depth 1 https://github.com/matteocervelli/llmsWhat 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 | $0.00042 | $0.03836 |
| Opus 5 | $0.00021 | $0.01918 |
| Sonnet 5 | $0.00008 | $0.00767 |
| Haiku 4.5 | $0.00004 | $0.00384 |
Grade A, and why
python-quality-checker 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 today.
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.
How it starts
The opening of the file, as written. The whole thing — 731 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Python Quality Checker Skill
Purpose
This skill provides comprehensive Python code quality validation including formatting (Black), type checking (mypy), linting (flake8/ruff), security analysis (bandit), and complexity analysis. Ensures code meets Python best practices and project standards.
When to Use
- Validating Python code quality before commit
- Running pre-commit quality checks
- CI/CD quality gate validation
- Code review preparation
- Ensuring PEP 8 compliance
- Type safety validation
- Security vulnerability detection
Quality Check Workflow
1. Environment Setup
Verify Tools Installed:
# Check Python version
python --version
# Check quality tools
black --version
mypy --version
flake8 --version
bandit --version
# Or install missing tools
pip install black mypy flake8 bandit ruff
Install Development Dependencies:
# Install all dev tools
pip install -e ".[dev]"
# Or from requirements
pip install -r requirements-dev.txt
Deliverable: Quality tools ready
2. Code Formatting Check (Black)
Check Formatting:
# Check if code is formatted
black --check src/ tests/
# Check with diff
black --check --diff src/ tests/
# Check specific files
black --check src/tools/feature/core.py
# Check with color output
black --check --color src/ tests/
Auto-Format Code:
# Format all code
black src/ tests/
# Format specific directory
black src/tools/feature/
# Format with specific line length
black --line-length 100 src/
# Preview changes without applying
black --check --diff src/
Configuration (pyproject.toml):
[tool.black]
line-length = 88
target-version = ['py311']
include = '\.pyi?$'
extend-exclude = '''
/(
# Directories
\.eggs
| \.git
| \.venv
| build
| dist
)/
'''
Deliverable: Formatting validation report
3. Type Checking (mypy)
Run Type Checks:
# Check entire codebase
mypy src/
# Check specific module
mypy src/tools/feature/
# Check with stricter settings
mypy --strict src/
# Show error codes
mypy --show-error-codes src/
# Generate HTML report
mypy --html-report mypy-report/ src/
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.
- today First seen · 731 lines · 42 tokens per session scan A c097e6c1cdb6
python-quality-checker is a skill published in the GitHub repository matteocervelli/llms (25 stars, last pushed 3mo ago), licensed MIT. It adds 42 tokens to every session and 3,836 once invoked, about $0.0002 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 2026-09-01.
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