refactor-functional-patterns

refactor-functional-patterns is a skill for Claude Code, Codex from mickeyyaya/refactoring-skills. It costs 56 tokens per session (2,678 once invoked), scanned A, original, MIT.

A code-review guide for functional programming patterns, such as pure functions, immutable data, collection transformations, and function composition. Functional programming reduces hidden changes and side effects in code.

In plain words
What is it for?
Use it to review code and suggest patterns such as map, filter, reduce, higher-order functions, currying, and pattern matching.
Why use it?
It helps identify shared-state bugs, repeated null checks, tangled data processing, and functions that mix calculations with input or output.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

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 skills/mickeyyaya/refactoring-skills/refactor-functional-patterns
Any agent
npx skills add mickeyyaya/refactoring-skills --skill refactor-functional-patterns
Clone the repo
git clone --depth 1 https://github.com/mickeyyaya/refactoring-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for refactor-functional-patterns

README.md
[![agentmods](https://agentmods.dev/badge/skills/mickeyyaya/refactoring-skills/refactor-functional-patterns.svg)](https://agentmods.dev/skills/mickeyyaya/refactoring-skills/refactor-functional-patterns)
Your own site
<a href="https://agentmods.dev/skills/mickeyyaya/refactoring-skills/refactor-functional-patterns"><img src="https://agentmods.dev/badge/skills/mickeyyaya/refactoring-skills/refactor-functional-patterns.svg" alt="Measured on agentmods" height="20"></a>
Per session 56 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,678 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 5.1 $0.00056 $0.02678
Opus 5 $0.00028 $0.01339
Sonnet 5 $0.00011 $0.00536
Haiku 4.5 $0.00006 $0.00268

Measured 5d ago against content hash 104d02a55d42, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

refactor-functional-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 5d 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.

skills/refactor-functional-patterns/SKILL.md · 328 lines

How it starts

The opening of the file, as written. The whole thing — 328 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Refactor: Functional Programming Patterns

Overview

FP patterns produce code that is predictable, testable, and composable by eliminating shared mutable state and side effects.

When to use: State mutation bugs, hidden dependencies, untestable functions, complex data pipelines, repeated null-check boilerplate, functions mixing computation and I/O.

Quick Reference

Pattern Core Idea Primary Red Flag
Pure Functions Same input → same output, no side effects Accessing global state inside business logic
Immutability Never mutate, always create new push, pop, or property assignment on existing objects
Map/Filter/Reduce Declarative collection transforms Manual loops accumulating results
Function Composition Build pipelines from small functions Deeply nested function calls f(g(h(x)))
Higher-Order Functions Functions that take/return functions Copy-pasted blocks differing by one operation
Currying / Partial Application Fix some arguments, defer the rest Repeatedly passing the same first argument
Functors / Monads Chainable containers for optional/error values Nested null checks, try-catch pyramids
Pattern Matching Destructure and branch on data shape instanceof chains or long type-checking conditionals

Patterns in Detail

1. Pure Functions

Red Flags: Reading global/process.env in computation; I/O mixed into business logic; parameter mutation (arr.push(x)); Date.now()/Math.random() in deterministic functions.

// BEFORE — reads global state + side effect
let taxRate = 0.2;
function calculateTotal(price: number): number {
  const total = price * (1 + taxRate);
  console.log(`total: ${total}`);
  return total;
}

// AFTER — pure: only uses arguments
function calculateTotal(price: number, taxRate: number): number {
  return price * (1 + taxRate);
}
# Python equivalent
def calculate_total(price: float, tax_rate: float) -> float:
    return price * (1 + tax_rate)

Read the full file on GitHub · 328 lines

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. 5d ago First seen · 328 lines · 56 tokens per session scan A 104d02a55d42

Subscribe to this mod's changes

refactor-functional-patterns is a skill published in the GitHub repository mickeyyaya/refactoring-skills (6 stars, last pushed 5mo ago), licensed MIT. It adds 56 tokens to every session and 2,678 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 2026-08-31.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

next-partial-prefetching-adoption

Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…

vercel/next.js · 103 tokens

chronicle

Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…

microsoft/vscode · 72 tokens

imagegen

Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…

openai/codex · 113 tokens