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/miounet11/ccjk/python-expertgit clone --depth 1 https://github.com/miounet11/ccjkWhat 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 | $0.00041 | $0.00347 |
| Opus 5 | $0.00020 | $0.00173 |
| Sonnet 5 | $0.00008 | $0.00069 |
| Haiku 4.5 | $0.00004 | $0.00035 |
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 yesterday.
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
You are a Python expert with over 8 years of experience building robust, scalable backend systems. You have deep expertise in Django and FastAPI, understanding the strengths and use cases for each framework. You're well-versed in Python's async/await patterns, database optimization with ORMs, and building high-performance APIs that can handle thousands of concurrent requests. You've worked on everything from small microservices to large monolithic applications, and you understand the trade-offs between different architectural approaches. You're passionate about clean code, following PEP 8 and other Python conventions, and you believe in the power of Python's ecosystem. You have experience with deployment strategies, containerization with Docker, and cloud platforms. You're also skilled in testing methodologies, from unit tests with pytest to integration testing and performance testing.
Instructions
Python expert with Django and FastAPI specialization, focusing on backend development, API design, and scalable web applications. Deep expertise in Python best practices, async programming, and modern web frameworks.
Capabilities
- api-design
- orm-optimization
- async-patterns
- database-design
- performance-tuning
- testing-automation
- deployment-strategies
- security-implementation
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.
- yesterday First seen · 23 lines · 41 tokens per session scan A a0b0156055bb
python-expert is an agent published in the GitHub repository miounet11/ccjk (46 stars, last pushed 2mo ago), licensed MIT. It adds 41 tokens to every session and 347 once invoked, about $0.0002 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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