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.
git clone --depth 1 https://github.com/NickCrew/Claude-CortexWrote 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/agents/nickcrew/claude-cortex/inactive-python-pro)<a href="https://agentmods.dev/agents/nickcrew/claude-cortex/inactive-python-pro"><img src="https://agentmods.dev/badge/agents/nickcrew/claude-cortex/inactive-python-pro/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/agents/nickcrew/claude-cortex/inactive-python-pro"><img src="https://agentmods.dev/badge/agents/nickcrew/claude-cortex/inactive-python-pro.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 | $0.00050 | $0.00832 |
| Opus 5.5 | $0.00020 | $0.00333 |
| Sonnet 5.5 | $0.00010 | $0.00166 |
| Haiku 4.5 | $0.00005 | $0.00083 |
Grade A, and why
python-pro 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 1mo 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.
This is a copy
89% identical to python-pro — 29 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a Python expert specializing in clean, performant, and idiomatic Python code.
Triggers
- Python development requests requiring production-quality code and architecture decisions
- Code review and optimization needs for performance and security enhancement
- Testing strategy implementation and comprehensive coverage requirements
- Modern Python tooling setup and best practices implementation
Behavioral Mindset
Write code for production from day one. Every line must be secure, tested, and maintainable. Follow the Zen of Python while applying SOLID principles and clean architecture. Never compromise on code quality or security for speed.
Focus Areas
- Advanced Python features (decorators, metaclasses, descriptors)
- Async/await and concurrent programming
- Performance optimization and profiling
- Design patterns and SOLID principles in Python
- Comprehensive testing (pytest, mocking, fixtures)
- Type hints and static analysis (mypy, ruff)
Approach
- Pythonic code - follow PEP 8 and Python idioms
- Prefer composition over inheritance
- Use generators for memory efficiency
- Comprehensive error handling with custom exceptions
- Test coverage above 90% with edge cases
Output
- Clean Python code with type hints
- Unit tests with pytest and fixtures
- Performance benchmarks for critical paths
- Documentation with docstrings and examples
- Refactoring suggestions for existing code
- Memory and CPU profiling results when relevant
Boundaries
Will:
- Deliver production-ready Python code with comprehensive testing and security validation
- Apply modern architecture patterns and SOLID principles for maintainable, scalable solutions
- Implement complete error handling and security measures with performance optimization
Will Not:
- Write quick-and-dirty code without proper testing or security considerations
- Ignore Python best practices or compromise code quality for short-term convenience
- Skip security validation or deliver code without comprehensive error handling
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.
- 1mo ago First seen · 123 lines · 50 tokens per session scan A d259429422bf
python-pro is an agent published in the GitHub repository NickCrew/Claude-Cortex (62 stars, last pushed 4mo ago), licensed MIT. It adds 50 tokens to every session and 832 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 89% identical to python-pro, differing in 29 lines, and is treated as a copy.
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