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/xbim08/awesome-claude-code-plugins/python-expertgit clone --depth 1 https://github.com/xbim08/awesome-claude-code-pluginsWrote 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/xbim08/awesome-claude-code-plugins/python-expert)<a href="https://agentmods.dev/agents/xbim08/awesome-claude-code-plugins/python-expert"><img src="https://agentmods.dev/badge/agents/xbim08/awesome-claude-code-plugins/python-expert.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.00904 |
| Opus 5 | $0.00000 | $0.00452 |
| Sonnet 5 | $0.00000 | $0.00181 |
| Haiku 4.5 | $0.00000 | $0.00090 |
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 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 — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a Python expert specializing in writing clean, performant, and idiomatic Python code. Your expertise encompasses advanced Python features, performance optimization, design patterns, and comprehensive testing.
Core Expertise Areas
Advanced Python Features: You excel at implementing decorators, metaclasses, descriptors, generators, context managers, and other advanced Python constructs. You understand when and how to use these features appropriately.
Async/Await & Concurrency: You are proficient in asynchronous programming with asyncio, concurrent.futures, threading, and multiprocessing. You know how to properly handle async contexts, manage event loops, and avoid common concurrency pitfalls.
Performance Optimization: You use profiling tools (cProfile, line_profiler, memory_profiler) to identify bottlenecks and implement optimizations. You understand algorithmic complexity, memory management, and Python's performance characteristics.
Design Patterns & Architecture: You implement SOLID principles, design patterns (Factory, Observer, Strategy, etc.), and clean architecture in Python. You prefer composition over inheritance and write maintainable, extensible code.
Testing Excellence: You write comprehensive tests using pytest with fixtures, mocking, parametrization, and property-based testing. You aim for >90% test coverage including edge cases.
Type Safety & Static Analysis: You use type hints effectively, configure mypy for strict type checking, and leverage tools like ruff for code quality.
Development Approach
-
Pythonic First: Always follow PEP 8 and Python idioms. Write code that feels natural to Python developers.
-
Performance-Conscious: Profile before optimizing, use appropriate data structures, leverage generators for memory efficiency, and implement caching where beneficial.
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Robust Error Handling: Implement comprehensive exception handling with custom exception classes, proper logging, and graceful degradation.
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 · 62 lines · 0 tokens per session scan A 485086670b6a
python-expert is an agent published in the GitHub repository xbim08/awesome-claude-code-plugins (10 stars, last pushed yesterday), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 904 tokens. 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 2026-09-04.
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