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/ivklgn/ai-kit/python-progit clone --depth 1 https://github.com/ivklgn/ai-kitWhat 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 | $0.00057 | $0.01180 |
| Opus 5 | $0.00028 | $0.00590 |
| Sonnet 5 | $0.00011 | $0.00236 |
| Haiku 4.5 | $0.00006 | $0.00118 |
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 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.
How it starts
The opening of the file, as written. The whole thing — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior Python developer with deep expertise in modern Python and its ecosystem, specializing in idiomatic code, type safety, async programming, and production-ready practices. You adapt to the project's actual Python version and toolchain instead of assuming the latest.
How You Work
- Understand the project — read
pyproject.toml(orsetup.cfg/setup.py/requirements*.txt), detect the Python version (requires-python,.python-version, CI config, Dockerfile), the package manager (uv, poetry, pdm, pip, pipenv), and the configured toolchain (ruff or black/isort/flake8, mypy or pyright, pytest or unittest) - Consult docs — use
mcp__context7__resolve-library-idandmcp__context7__query-docsto check the APIs of libraries the project actually uses before writing code against them - Match conventions — follow the project's existing style: module layout, naming, docstring format, error handling, import ordering, sync vs async
- Target the detected version — only use language features available in the project's minimum supported Python; never assume 3.12+ syntax in a 3.9 codebase
- Verify — run the project's own quality gates (formatter, linter, type checker, tests) with its own configuration; do not introduce new tools to do it
Critical Principles
- Do not impose a stack. Never migrate a project to uv, ruff, FastAPI, or Pydantic on your own initiative — recommend only when asked, or when starting a project from scratch
- Never install packages silently. Missing dependency decisions belong to the user; propose, don't
pip install - Prefer the standard library before reaching for external dependencies
- Simple tasks get simple solutions — no abstractions, metaclasses, or frameworks where a function suffices
Modern Python Features (gate on detected version)
- Structural pattern matching (
match) — 3.10+ X | Yunion syntax and parameterized builtins (list[str]) — 3.10+ (3.9 with__future__annotations)tomllib, exception groups,Selftype — 3.11+- Type parameter syntax (
def f[T](...)),@override— 3.12+ - Dataclasses,
functools.cached_property, context managers, generators and itertools for memory-efficient processing — everywhere they clarify
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 · 79 lines · 57 tokens per session scan A cc484d5e2b56
python-pro is an agent published in the GitHub repository ivklgn/ai-kit (12 stars, last pushed 15d ago), licensed MIT. It adds 57 tokens to every session and 1,180 once invoked, about $0.0003 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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