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 skills/tao12345666333/ankaloop/python-expertnpx skills add tao12345666333/ankaloop --skill python-expertgit clone --depth 1 https://github.com/tao12345666333/ankaloopWrote 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/skills/tao12345666333/ankaloop/python-expert)<a href="https://agentmods.dev/skills/tao12345666333/ankaloop/python-expert"><img src="https://agentmods.dev/badge/skills/tao12345666333/ankaloop/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 | $0.00011 | $0.00270 |
| Opus 5 | $0.00005 | $0.00135 |
| Sonnet 5 | $0.00002 | $0.00054 |
| Haiku 4.5 | $0.00001 | $0.00027 |
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 5d 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
Python Expert Skill
When working with Python code, apply these advanced patterns and best practices:
Code Style
- Follow PEP 8 guidelines
- Use type hints for function signatures
- Prefer f-strings for string formatting
- Use meaningful variable and function names
Modern Python Features
- Use dataclasses for data containers
- Prefer pathlib over os.path
- Use context managers for resource management
- Leverage generators for memory efficiency
- Use structural pattern matching (Python 3.10+)
Error Handling
- Use specific exception types
- Provide meaningful error messages
- Log errors appropriately
- Consider using Result types for expected failures
Testing
- Write unit tests with pytest
- Use fixtures for test setup
- Mock external dependencies
- Aim for high test coverage
Project Structure
project/
├── src/
│ └── package/
│ ├── __init__.py
│ └── module.py
├── tests/
│ └── test_module.py
├── pyproject.toml
└── README.md
Packaging
- Use pyproject.toml for configuration
- Define clear dependencies
- Use semantic versioning
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.
- 5d ago First seen · 52 lines · 11 tokens per session scan A 272884f43c4f
python-expert is a skill published in the GitHub repository tao12345666333/ankaloop (44 stars, last pushed 6d ago), licensed Apache-2.0. It adds 11 tokens to every session and 270 once invoked, about $0.0001 per session on Opus 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 2026-08-30.
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