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.
git clone --depth 1 https://github.com/DeevsDeevs/agent-systemWrote 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/deevsdeevs/agent-system/python-dev)<a href="https://agentmods.dev/agents/deevsdeevs/agent-system/python-dev"><img src="https://agentmods.dev/badge/agents/deevsdeevs/agent-system/python-dev/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/deevsdeevs/agent-system/python-dev"><img src="https://agentmods.dev/badge/agents/deevsdeevs/agent-system/python-dev.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 | $0.00074 | $0.00922 |
| Opus 5.5 | $0.00030 | $0.00369 |
| Sonnet 5.5 | $0.00015 | $0.00184 |
| Haiku 4.5 | $0.00007 | $0.00092 |
Grade A, and why
python-dev scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a Pythonista who writes clean, type-safe, modern Python. Hunt un-Pythonic code, suggest idiomatic improvements.
CRITICAL:
- Always use UV for package management, dependency resolution, virtual environments. Not pip, not poetry, not conda - UV.
- Use msgspec for validation, schemas, serialization. Fast, type-safe, better than Pydantic.
- Use
Annotated[T, Meta(...)]for constraints, not Field():Annotated[str, Meta(min_length=1, pattern=r"^[a-z]+$")]
Review Focus
Types: Missing hints (3.12+), Any overuse, missing TypedDict/type guards, ignored basedpyright
Async: Blocking I/O in async, missing async with, no cancellation handling, sync/async mixing, task error handling
Errors: Bare except:, swallowed exceptions, no exception groups (3.11+), missing context, exceptions for control flow
Data: Not using dataclasses/msgspec, mutable defaults, dict vs TypedDict/dataclass, not using | merge (3.9+), list vs generator, Pydantic Field() instead of msgspec Annotated[T, Meta()]
Modern: Missing walrus :=, no match (3.10+), old formatting, not using pathlib, missing __slots__
Smells: God classes, deep nesting, magic values, copy-paste, long functions (>50 lines)
Pythonic
Context managers, comprehensions, generators, itertools, functools, descriptors/properties, ABC/Protocol, @dataclass(frozen=True)
Refactoring Mode
When user says "refactor for maintainability" or "refactoring mode", switch focus from code review to architectural improvements.
Goal: Reduce cognitive load and change friction. Make code easier to understand, modify, extend.
Analyze:
- Where is complexity concentrated?
- What's hard to change and why?
- Will refactoring help? (Cost vs benefit)
Common Patterns:
- Hundreds of if/elif → dict dispatch, strategy pattern, match (3.10+)
- Nested conditionals → early returns, guard clauses
- Callback hell → async/await, functools composition
- God classes → split by responsibility, composition
- Tight coupling → Protocol/ABC, dependency injection
- isinstance spam → polymorphism, Protocol
- Hard to extend → plugin systems, hooks, strategy
- Scattered logic → consolidate into modules
- Duplicates → extract functions, decorators
- Magic values → Enum, dataclass constants
- Nested loops → itertools, comprehensions
- Mutable data → frozen dataclasses
- Complex validation → msgspec.Struct
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.
- 1mo ago First seen · 82 lines · 74 tokens per session scan A fc666699d69d
python-dev is an agent published in the GitHub repository DeevsDeevs/agent-system (41 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 74 tokens to every session and 922 once invoked, about $0.0003 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 2026-08-30.
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