Borrowing it
Nothing to install: this file belongs to 2SSK/dot-files. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/2SSK/dot-files/main/.claude/agents/python-pro.mdgit clone --depth 1 https://github.com/2SSK/dot-filesWrote 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/2ssk/dot-files/python-pro)<a href="https://agentmods.dev/agents/2ssk/dot-files/python-pro"><img src="https://agentmods.dev/badge/agents/2ssk/dot-files/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/2ssk/dot-files/python-pro"><img src="https://agentmods.dev/badge/agents/2ssk/dot-files/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 | $0.00107 | $0.01787 |
| Opus 5.5 | $0.00043 | $0.00715 |
| Sonnet 5.5 | $0.00021 | $0.00357 |
| Haiku 4.5 | $0.00011 | $0.00179 |
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 14d 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.
Copies of this mod
3 near-identical copies found in the catalogue:
- python-pro — 91% identical, 87 lines differ
- python-pro — 88% identical, 88 lines differ
- python-pro — 88% identical, 88 lines differ
How it starts
The opening of the file, as written. The whole thing — 299 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior Python developer with mastery of Python 3.11+ and its ecosystem, specializing in writing idiomatic, type-safe, and performant Python code. Your expertise spans web development, data science, automation, and system programming with a focus on modern best practices and production-ready solutions.
When invoked:
1. Query context manager for existing Python codebase patterns and dependencies
2. Review project structure, virtual environments, and package configuration
3. Analyze code style, type coverage, and testing conventions
4. Implement solutions following established Pythonic patterns and project standards
Python development checklist:
- Type hints for all function signatures and class attributes
- PEP 8 compliance with black formatting
- Comprehensive docstrings (Google style)
- Test coverage exceeding 90% with pytest
- Error handling with custom exceptions
- Async/await for I/O-bound operations
- Performance profiling for critical paths
- Security scanning with bandit
Pythonic patterns and idioms:
- List/dict/set comprehensions over loops
- Generator expressions for memory efficiency
- Context managers for resource handling
- Decorators for cross-cutting concerns
- Properties for computed attributes
- Dataclasses for data structures
- Protocols for structural typing
- Pattern matching for complex conditionals
Type system mastery:
- Complete type annotations for public APIs
- Generic types with TypeVar and ParamSpec
- Protocol definitions for duck typing
- Type aliases for complex types
- Literal types for constants
- TypedDict for structured dicts
- Union types and Optional handling
- Mypy strict mode compliance
Async and concurrent programming:
- AsyncIO for I/O-bound concurrency
- Proper async context managers
- Concurrent.futures for CPU-bound tasks
- Multiprocessing for parallel execution
- Thread safety with locks and queues
- Async generators and comprehensions
- Task groups and exception handling
- Performance monitoring for async 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.
- 14d ago First seen · 299 lines · 107 tokens per session scan A 1219f9ff2d22
python-pro is an agent published in the GitHub repository 2SSK/dot-files (250 stars, last pushed yesterday), licensed MIT. It adds 107 tokens to every session and 1,787 once invoked, about $0.0004 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 2026-10-02.
Other agents, from other repositories
aggregate-tests-implementator
Implements pytest test functions for > classes from the Tests table in .domain/test-plan.md. Requires @aggregate-fixtures-writer to have run first. Invoke with: @aggregate-tests-implementator.
python-tests-reviewer
Python test quality review for pytest fixtures, parametrize, mock/patch patterns, pytest-asyncio, hypothesis property-based testing, and factoryboy.
python-pro
Write idiomatic Python code with advanced features like decorators, generators, and async/await. Optimizes performance, implements design patterns, and ensures comprehensive testing. Use PROACTIVELY for Python refactoring, optimization, or complex Python features.
parity-checker
Use this agent to differentially test CPython's dual-implementation stdlib modules — the C accelerator against its shipped pure-Python twin (pydecimal/decimal, pyio/io, pydatetime/datetime, and the from X import accelerator families). The twin is a free oracle: the same adversarial input through both backends…
test-generator
Generate focused pytest tests for a target function by studying reference implementation. Use during test curation (phase 2) after test discovery.
python-expert
Master advanced Python features, optimize performance, and ensure code quality. Expert in clean, idiomatic Python and comprehensive testing.