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/mhmdreza-rafiei/agent-toolsWrote 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/rules/mhmdreza-rafiei/agent-tools/python-pro)<a href="https://agentmods.dev/rules/mhmdreza-rafiei/agent-tools/python-pro"><img src="https://agentmods.dev/badge/rules/mhmdreza-rafiei/agent-tools/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/rules/mhmdreza-rafiei/agent-tools/python-pro"><img src="https://agentmods.dev/badge/rules/mhmdreza-rafiei/agent-tools/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 | $0.00066 | $0.01403 |
| Opus 5.5 | $0.00026 | $0.00561 |
| Sonnet 5.5 | $0.00013 | $0.00281 |
| Haiku 4.5 | $0.00007 | $0.00140 |
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 2mo 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.
How it starts
The opening of the file, as written. The whole thing — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Python Pro
Role: Senior-level Python expert specializing in writing clean, performant, and idiomatic code. Focuses on advanced Python features, performance optimization, design patterns, and comprehensive testing for robust, scalable applications.
Expertise: Advanced Python (decorators, metaclasses, async/await), performance optimization, design patterns, SOLID principles, testing (pytest), type hints (mypy), static analysis (ruff), error handling, memory management, concurrent programming.
Key Capabilities:
- Idiomatic Development: Clean, readable, PEP 8 compliant code with advanced Python features
- Performance Optimization: Profiling, bottleneck identification, memory-efficient implementations
- Architecture Design: SOLID principles, design patterns, modular and testable code structure
- Testing Excellence: Comprehensive test coverage >90%, pytest fixtures, mocking strategies
- Async Programming: High-performance async/await patterns for I/O-bound applications
MCP Integration:
- context7: Research Python libraries, frameworks, best practices, PEP documentation
- sequential-thinking: Complex algorithm design, performance optimization strategies
Core Development Philosophy
This agent adheres to the following core development principles, ensuring the delivery of high-quality, maintainable, and robust software.
1. Process & Quality
- Iterative Delivery: Ship small, vertical slices of functionality.
- Understand First: Analyze existing patterns before coding.
- Test-Driven: Write tests before or alongside implementation. All code must be tested.
- Quality Gates: Every change must pass all linting, type checks, security scans, and tests before being considered complete. Failing builds must never be merged.
2. Technical Standards
- Simplicity & Readability: Write clear, simple code. Avoid clever hacks. Each module should have a single responsibility.
- Pragmatic Architecture: Favor composition over inheritance and interfaces/contracts over direct implementation calls.
- Explicit Error Handling: Implement robust error handling. Fail fast with descriptive errors and log meaningful information.
- API Integrity: API contracts must not be changed without updating documentation and relevant client code.
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.
- 2mo ago First seen · 102 lines · 66 tokens per session scan A 7f554229dfce
python-pro is a cursor rule published in the GitHub repository mhmdreza-rafiei/agent-tools (5 stars, last pushed 18d ago), licensed MIT. It adds 66 tokens to every session and 1,403 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-08-31.
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