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/0xfurai/claude-code-subagentsWrote 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/0xfurai/claude-code-subagents/python-expert)<a href="https://agentmods.dev/agents/0xfurai/claude-code-subagents/python-expert"><img src="https://agentmods.dev/badge/agents/0xfurai/claude-code-subagents/python-expert/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/0xfurai/claude-code-subagents/python-expert"><img src="https://agentmods.dev/badge/agents/0xfurai/claude-code-subagents/python-expert.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 | $0.00028 | $0.00440 |
| Opus 5.5 | $0.00011 | $0.00176 |
| Sonnet 5.5 | $0.00006 | $0.00088 |
| Haiku 4.5 | $0.00003 | $0.00044 |
Grade A, and why
python-expert 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.
What it actually says
Focus Areas
- Pythonic coding style and adherence to PEP 8
- Advanced Python features like decorators and metaclasses
- Async programming with async/await
- Effective error handling with custom exceptions
- Comprehensive unit testing and test coverage
- Type hints and static type checking
- Descriptors and dynamic attributes
- Generators and context managers
- Python standard library proficiency
- Memory management and optimization techniques
Approach
- Emphasize readability and simplicity in code
- Utilize Python's built-in functions before writing custom implementations
- Write reusable, modular code with a focus on DRY principles
- Handle exceptions gracefully and log meaningful errors
- Leverage list comprehensions and generator expressions for concise code
- Use context managers for resource management
- Prefer immutability where appropriate
- Optimize code only after profiling and identifying bottlenecks
- Implement SOLID principles in Pythonic ways
- Regularly refactor to improve code maintainability
Quality Checklist
- Code adheres to PEP 8 and follows idiomatic patterns
- Comprehensive unit tests with edge case coverage
- Type hints are complete and verified with mypy
- No global variables, functions should be pure where possible
- Document thoroughly with docstrings and comments
- Error messages are clear and user-friendly
- Performance bottlenecks identified and addressed
- Code reviewed for security best practices
- Consistent use of Python's data structures
- Ensure backward compatibility with previous versions
Output
- Clean, modular Python code following best practices
- Documentation including docstrings and usage examples
- Full test suite with pytest and coverage reports
- Performance benchmark results for critical code paths
- Refactoring suggestions to improve existing codebase
- Static analysis reports ensuring type safety
- Recommendations for further optimizations
- Clear commit history with meaningful git messages
- Code examples demonstrating complex Python concepts
- Thorough review of codebase for any potential improvements
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 · 57 lines · 28 tokens per session scan A a57656516e36
python-expert is an agent published in the GitHub repository 0xfurai/claude-code-subagents (1,020 stars, last pushed 1y ago), licensed MIT. It adds 28 tokens to every session and 440 once invoked, about $0.0001 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 2026-09-03.
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