balanced-coupling

balanced-coupling is a skill for Claude Code, Codex from nwiizo/cargo-coupling. It costs 31 tokens per session (1,147 once invoked), scanned A, original, MIT.

A reference guide for judging how strongly software parts depend on each other and how costly those dependencies are to change.

In plain words
What is it for?
Use it to analyse coupling patterns, review designs, and interpret architecture-analysis results.
Why use it?
It gives architecture reviews a shared way to spot coupling that may make systems harder to modify.

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/nwiizo/cargo-coupling/balanced-coupling
Any agent
npx skills add nwiizo/cargo-coupling --skill balanced-coupling
Clone the repo
git clone --depth 1 https://github.com/nwiizo/cargo-coupling

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 balanced-coupling

README.md
[![agentmods](https://agentmods.dev/badge/skills/nwiizo/cargo-coupling/balanced-coupling.svg)](https://agentmods.dev/skills/nwiizo/cargo-coupling/balanced-coupling)
Your own site
<a href="https://agentmods.dev/skills/nwiizo/cargo-coupling/balanced-coupling"><img src="https://agentmods.dev/badge/skills/nwiizo/cargo-coupling/balanced-coupling.svg" alt="Measured on agentmods" height="20"></a>
Per session 31 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,147 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 $0.00031 $0.01147
Opus 5 $0.00015 $0.00574
Sonnet 5 $0.00006 $0.00229
Haiku 4.5 $0.00003 $0.00115

Measured 3d ago against content hash 033c670e9099, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

balanced-coupling 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.

.claude/skills/balanced-coupling/SKILL.md · 116 lines

How it starts

The opening of the file, as written. The whole thing — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Balanced Coupling Model Reference

Based on Vlad Khononov's "Balancing Coupling in Software Design".

The Balance Rule

MODULARITY = STRENGTH XOR DISTANCE
COMPLEXITY = STRENGTH AND DISTANCE
BALANCE = (STRENGTH XOR DISTANCE) OR NOT VOLATILITY
  • Modularity emerges when strength and distance counterbalance
  • Complexity emerges when both are equal (both high or both low)
  • Pragmatic: unbalanced coupling is tolerable if volatility is low

Three Dimensions

1. Integration Strength (Knowledge Shared)

From most to least intrusive:

Level Knowledge Type Implicit/Explicit
Intrusive Implementation details, private interfaces Implicit, fragile
Functional Business rules, functional specifications Often implicit
Model Domain/business model, data structures Explicit but broad
Contract Integration contracts, facades Most explicit, stable

Key insight: Intrusive and Functional coupling are often implicit — they exist without anyone realizing. Contract coupling is explicit by design.

2. Distance (Cost of Change)

Multiple dimensions contribute to distance:

  • Code structure: methods → objects → modules → crates → services
  • Organizational: same team vs different teams (Conway's Law)
  • Runtime: synchronous (tight) vs asynchronous (loose)
  • Lifecycle: shared deployments vs independent deployments

Distance is fractal: the same rules apply at every abstraction level.

3. Volatility (Probability of Change)

Determined by DDD subdomain classification, not just git history:

Subdomain Volatility Reason
Core High Competitive advantage, constantly optimized
Supporting Low Boring CRUD/ETL, rarely changes
Generic Low Solved problems, stable implementations

Important: distinguish essential vs accidental volatility. Accidental volatility comes from poor design, not business needs.

Read the full file on GitHub · 116 lines

Files

What ships with it

1 file 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 · 116 lines · 31 tokens per session scan A 033c670e9099

Subscribe to this mod's changes

balanced-coupling is a skill published in the GitHub repository nwiizo/cargo-coupling (96 stars, last pushed 6d ago), licensed MIT. It adds 31 tokens to every session and 1,147 once invoked, about $0.0002 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 2026-09-01.

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

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

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens