reducing-entropy

A manually activated approach for reducing the total amount of code in a project. It focuses on what can be removed while still keeping the required behaviour.

In plain words
What is it for?
Reviewing a proposed change for deletions, simplifying implementations, measuring code before and after, and removing code when the feature can still work without it.
Why use it?
It helps prevent a codebase from growing through unnecessary functions, files, and workarounds. Success is judged by the final code size, not by how little effort the change took.

Skill for Claude CodeCodex

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/softaworks/agent-toolkit/reducing-entropy
Any agent
npx skills add softaworks/agent-toolkit --skill reducing-entropy
Clone the repo
git clone --depth 1 https://github.com/softaworks/agent-toolkit

Made for: Claude Code, Codex.

Per session 37 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 597 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 100% copy Near-identical to another mod 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 $0.00037 $0.00597
Opus 5 $0.00018 $0.00298
Sonnet 5 $0.00007 $0.00119
Haiku 4.5 $0.00004 $0.00060

Measured 3d ago against content hash 50958820599a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

reducing-entropy 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 3d 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.

Origin

This is a copy

100% identical to reducing-entropy — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/reducing-entropy/SKILL.md · 82 lines

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.

Reducing Entropy

More code begets more code. Entropy accumulates. This skill biases toward the smallest possible codebase.

Core question: "What does the codebase look like after?"

Before You Begin

Load at least one mindset from references/

  1. List the files in the reference directory
  2. Read frontmatter descriptions to pick which applies
  3. Load at least one
  4. State which you loaded and its core principle

Do not proceed until you've done this.

The Goal

The goal is less total code in the final codebase - not less code to write right now.

  • Writing 50 lines that delete 200 lines = net win
  • Keeping 14 functions to avoid writing 2 = net loss
  • "No churn" is not a goal. Less code is the goal.

Measure the end state, not the effort.

Three Questions

1. What's the smallest codebase that solves this?

Not "what's the smallest change" - what's the smallest result.

  • Could this be 2 functions instead of 14?
  • Could this be 0 functions (delete the feature)?
  • What would we delete if we did this?

2. Does the proposed change result in less total code?

Count lines before and after. If after > before, reject it.

  • "Better organized" but more code = more entropy
  • "More flexible" but more code = more entropy
  • "Cleaner separation" but more code = more entropy

3. What can we delete?

Every change is an opportunity to delete. Ask:

  • What does this make obsolete?
  • What was only needed because of what we're replacing?
  • What's the maximum we could remove?

Red Flags

  • "Keep what exists" - Status quo bias. The question is total code, not churn.
  • "This adds flexibility" - Flexibility for what? YAGNI.
  • "Better separation of concerns" - More files/functions = more code. Separation isn't free.
  • "Type safety" - Worth how many lines? Sometimes runtime checks in less code wins.
  • "Easier to understand" - 14 things are not easier than 2 things.

When This Doesn't Apply

  • The codebase is already minimal for what it does
  • You're in a framework with strong conventions (don't fight it)
  • Regulatory/compliance requirements mandate certain structures

Read the full file on GitHub · 82 lines

Files

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.

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. 3d ago First seen · 82 lines · 37 tokens per session scan A 50958820599a

Subscribe to this mod's changes

reducing-entropy is a skill published in the GitHub repository softaworks/agent-toolkit (2,413 stars, last pushed 6mo ago), licensed MIT. It adds 37 tokens to every session and 597 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to reducing-entropy, differing in 0 lines, and is treated as a copy.