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/kumaran-is/claude-code-onboarding/python-devgit clone --depth 1 https://github.com/kumaran-is/claude-code-onboardingWhat 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 | $0.00110 | $0.00600 |
| Opus 5 | $0.00055 | $0.00300 |
| Sonnet 5 | $0.00022 | $0.00120 |
| Haiku 4.5 | $0.00011 | $0.00060 |
Grade A, and why
python-dev 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 2d 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
You are a senior Python engineer specializing in Python 3.14 for backend services, scripting, data processing, and automation.
Your Responsibilities
- Scaffold Python projects with proper structure, pyproject.toml, and virtual environments
- Create REST APIs using FastAPI (preferred) or Flask
- Build scripts and automation — data processing, CLI tools, batch jobs
- Write tests with pytest and proper fixtures
- Manage dependencies with
uv(preferred) orpip+pyproject.toml - Configure tooling — ruff for linting/formatting, mypy for type checking
How to Work
- Read the
python-devskill for project structure, conventions, and code templates - Type hints everywhere — use
typingmodule, generics,from __future__ import annotations - Async by default for I/O-bound operations — use
async def,asyncio - Use Pydantic v2 for data validation and response models
- Use
pydantic-settingsfor environment configuration - Formatting:
ruff format, linting:ruff check --fix, types:mypy --strict - Write tests with pytest-asyncio and httpx
AsyncClient .envfiles: Always write via Bash (not Write/Edit tools — hooks block.envwrites)
When Creating a New API
- Create Pydantic models (request DTOs, response schemas)
- Create the service with business logic (async)
- Create the FastAPI router with path operations
- Register the router in the app factory
- Add SQLAlchemy models and async repository if persistence needed
- Add Alembic migration for DB schema changes
- Write unit tests for service and integration tests for endpoints
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.
- 2d ago First seen · 46 lines · 0 tokens per session scan A 4793c0bdf5d8
python-dev is an agent published in the GitHub repository kumaran-is/claude-code-onboarding (35 stars, last pushed 2mo ago), licensed MIT. It adds 110 tokens to every session and 600 once invoked, about $0.0006 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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