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 skills add KunanonJ/ai-skills-hub --skill refactoring-patternsgit clone --depth 1 https://github.com/KunanonJ/ai-skills-hubWrote 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/skills/kunanonj/ai-skills-hub/refactoring-patterns)<a href="https://agentmods.dev/skills/kunanonj/ai-skills-hub/refactoring-patterns"><img src="https://agentmods.dev/badge/skills/kunanonj/ai-skills-hub/refactoring-patterns/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/skills/kunanonj/ai-skills-hub/refactoring-patterns"><img src="https://agentmods.dev/badge/skills/kunanonj/ai-skills-hub/refactoring-patterns.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 | $0.00120 | $0.03374 |
| Opus 5.5 | $0.00048 | $0.01350 |
| Sonnet 5.5 | $0.00024 | $0.00675 |
| Haiku 4.5 | $0.00012 | $0.00337 |
Grade A, and why
refactoring-patterns 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 — 217 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Refactoring Patterns Framework
A disciplined approach to improving the internal structure of existing code without changing its observable behavior. Every refactoring follows the same loop: verify tests pass, apply one small structural change, verify tests still pass.
Core Principle
Refactoring is not rewriting. It is a sequence of small, behavior-preserving transformations, each backed by tests. You never change what the code does — only how it is organized. Big-bang rewrites fail because they combine structural change with behavioral change, making it impossible to know which broke things.
The foundation: Bad code is a natural consequence of delivering under time pressure, not a character flaw. Code smells are objective signals of degraded structure; the smell catalog tells you where to look, and the refactoring catalog tells you what to do.
Scoring
Goal: 10/10. When reviewing or refactoring code, rate structural quality 0-10: a 10/10 means no obvious smells remain, each function does one thing, names reveal intent, duplication is eliminated, and tests cover the refactored paths. Always give the current score and the specific refactorings needed to reach 10/10.
The Refactoring Patterns Framework
Six areas of focus for systematically improving code structure:
1. Code Smells as Triggers
Core concept: Code smells are surface indicators of deeper structural problems — not bugs, but signals that the design makes code harder to understand, extend, or maintain. Each smell maps to named refactorings that fix it.
Why it works: Named smells give teams objective criteria instead of subjective "I don't like this" — "This is Feature Envy" points directly at the fix.
Key insights:
- Smells cluster into five families: Bloaters, Object-Orientation Abusers, Change Preventers, Dispensables, Couplers
- Long Method is the most common smell; Duplicate Code is the most expensive
- A method that needs a comment to explain what it does is a smell — extract and name the block instead
- Shotgun Surgery (one change, many classes) and Divergent Change (one class, many reasons to change) are opposite signals of misplaced responsibilities
- Primitive Obsession — raw strings/ints instead of small domain objects — spreads errors and duplication
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 217 lines · 120 tokens per session scan A e8dfc30cac2b
refactoring-patterns is a skill published in the GitHub repository KunanonJ/ai-skills-hub (5 stars, last pushed 1mo ago), licensed MIT. It adds 120 tokens to every session and 3,374 once invoked, about $0.0005 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 2026-09-03.
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test-driven-development
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gentle-ai-bench
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go-testing
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ijfw-tdd
RED-GREEN-REFACTOR enforcement. Use when implementing a feature or bugfix before writing implementation code. Trigger: tdd, test first, red green refactor, /ijfw-tdd.