make-pythonic

A Python code-refactoring command that replaces common patterns with simpler features from the Python standard library and more flexible function-based designs.

In plain words
What is it for?
It scans Python files and applies listed replacements such as dataclasses, context managers, function arguments, registries, and structural interfaces.
Why use it?
It helps reduce unnecessary class hierarchies, repeated branching, manual data-holder code, and other patterns that make Python harder to maintain.

Command

Install

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.

agentmods
npx agentmods add commands/mktoronto/python-clean-architecture/make-pythonic
Clone the repo
git clone --depth 1 https://github.com/MKToronto/python-clean-architecture
Per session 12 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 581 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00012 $0.00581
Opus 5 $0.00006 $0.00291
Sonnet 5 $0.00002 $0.00116
Haiku 4.5 $0.00001 $0.00058

Measured yesterday against content hash b30018a328cd, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

make-pythonic 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.

commands/make-pythonic.md · 46 lines

What it actually says

Analyze the code at $ARGUMENTS (or the current working directory if no path given) and apply Pythonic pattern replacements.

Process

  1. Read the code — Find and read ALL Python files in the target path recursively. Read every .py file.

  2. Identify non-Pythonic patterns — Look for these specific code smells:

    Code Smell Replace With
    ABC/abstract base class hierarchy Protocol (structural typing)
    Single-method abstract class Callable type alias
    Deep class inheritance / mixins Composition with Protocol interface
    Wrapper classes for configuration functools.partial
    Factory class hierarchies Closures or tuples of functions + partial
    Long if/elif switching behavior Strategy pattern — pass functions as args
    if/elif for object creation Registry pattern — dict[str, Callable] mapping
    Inline notification side effects Pub/Sub — subscribe(event, handler) / post_event()
    Duplicated algorithm across classes Template Method — free function + Protocol parameter
    try/finally for resource cleanup Context managers
    Manual __init__ for data holders @dataclass
    Bare string constants for options Enum or StrEnum
  3. Propose changes — For each finding, show:

    • File and line
    • Current pattern — what it does now
    • Pythonic replacement — what it should become
    • Before/after code — complete snippets ready to apply
  4. Ask before applying — Use AskUserQuestion to confirm: "Apply these changes?" Let the user review before any edits.

  5. Apply changes — Edit the files with the approved refactorings.

For detailed pattern guidance, consult:

  • ${CLAUDE_PLUGIN_ROOT}/skills/clean-architecture/references/pythonic-patterns.md (quick lookup table for all 25 patterns)
  • ${CLAUDE_PLUGIN_ROOT}/skills/clean-architecture/references/classes-and-dataclasses.md (for class → dataclass conversions)
  • ${CLAUDE_PLUGIN_ROOT}/skills/clean-architecture/references/decorators.md (for decorator patterns)
  • ${CLAUDE_PLUGIN_ROOT}/skills/clean-architecture/references/context-managers.md (for try/finally → context manager conversions)
  • ${CLAUDE_PLUGIN_ROOT}/skills/clean-architecture/references/patterns/ (full OOP → functional progressions per pattern)
Changes

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.

  1. yesterday First seen · 46 lines · 12 tokens per session scan A b30018a328cd

Subscribe to this mod's changes

make-pythonic is a command published in the GitHub repository MKToronto/python-clean-architecture (8 stars, last pushed 2mo ago), licensed MIT. It adds 12 tokens to every session and 581 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 2026-08-31.