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 commands/mktoronto/python-clean-architecture/extract-god-classgit clone --depth 1 https://github.com/MKToronto/python-clean-architectureWhat 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 | $0.00013 | $0.00391 |
| Opus 5 | $0.00006 | $0.00196 |
| Sonnet 5 | $0.00003 | $0.00078 |
| Haiku 4.5 | $0.00001 | $0.00039 |
Grade A, and why
extract-god-class 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
Analyze the code at $ARGUMENTS (or the current working directory if no path given) for god classes and generate the split.
Process
-
Read the code — Find and read ALL Python files in the target path recursively. Read every
.pyfile. -
Identify god classes — A class is a god class if it has any of:
- Too many distinct responsibilities (doing more than one thing)
- Methods that cluster into unrelated groups
- Too many instance variables
- Methods that don't use most of the class's state
-
Analyze responsibilities — For each god class:
- Group methods by the data they access and the responsibility they serve
- Identify natural boundaries between responsibilities
- Determine which methods belong together
- Name each responsibility group
-
Propose extraction — Show:
- Original class — file, line count, responsibilities found
- Proposed split — one new class per responsibility group with:
- Class name
- Methods it takes
- Its
__init__parameters - Complete code for the new class
- Updated original — the slimmed-down class that composes the extracted ones
- Updated callers — any files that need import changes
-
Ask before applying — Use AskUserQuestion to confirm the split. The user may want to adjust which methods go where.
-
Apply changes — Create the new files and update the original class and its callers.
Principles: P1 High Cohesion, P4 Composition over Inheritance. Consult ${CLAUDE_PLUGIN_ROOT}/skills/clean-architecture/references/design-principles.md for refactoring recipes.
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 · 40 lines · 13 tokens per session scan A 154d89c98727
extract-god-class is a command published in the GitHub repository MKToronto/python-clean-architecture (8 stars, last pushed 2mo ago), licensed MIT. It adds 13 tokens to every session and 391 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.
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