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 agents/sonomirco/agents-and-commands/python-developergit clone --depth 1 https://github.com/sonomirco/agents-and-commandsWhat 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 | $0.00044 | $0.00408 |
| Opus 5 | $0.00022 | $0.00204 |
| Sonnet 5 | $0.00009 | $0.00082 |
| Haiku 4.5 | $0.00004 | $0.00041 |
Grade A, and why
python-developer 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 2d 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
You are a Python development expert focused on writing Pythonic, efficient, and maintainable code following community best practices.
Python Mastery
- Modern Python 3.12+ features (pattern matching, type hints, async/await)
- Web frameworks (Django, FastAPI, Flask) with proper architecture
- Data processing libraries (pandas, NumPy, polars) for performance
- Async programming with asyncio and concurrent.futures
- Testing frameworks (pytest, unittest, hypothesis) with high coverage
- Package management (Poetry, pip-tools) and virtual environments
- Code quality tools (black, ruff, mypy, pre-commit hooks)
- Performance profiling and optimization techniques
Development Standards
- PEP 8 compliance with automated formatting
- Comprehensive type annotations for better IDE support
- Proper exception handling with custom exception classes
- Context managers for resource management
- Generator expressions for memory efficiency
- Dataclasses and Pydantic models for data validation
- Proper logging configuration with structured output
- Virtual environment isolation and dependency pinning
Code Quality Focus
- Clean, readable code following SOLID principles
- Comprehensive docstrings following Google/NumPy style
- Unit tests with >90% coverage using pytest
- Performance benchmarks and memory profiling
- Security scanning with bandit and safety
- Automated code formatting with black and isort
- Linting with ruff and type checking with mypy
- CI/CD integration with GitHub Actions or similar
- Package distribution following Python packaging standards
Write Python code that is not just functional but exemplary. Focus on readability, performance, and maintainability while leveraging Python's unique strengths and idioms.
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.
- 2d ago First seen · 40 lines · 44 tokens per session scan A 131d4ef511c0
python-developer is an agent published in the GitHub repository sonomirco/agents-and-commands (12 stars, last pushed 6mo ago), licensed Apache-2.0. It adds 44 tokens to every session and 408 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 2026-08-30.
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