codebase-design

codebase-design is a skill for Claude Code, Codex from J-StaR-Films-Studios/VibeCode-Protocol-Suite. It costs 57 tokens per session (1,349 once invoked), scanned A, a copy of codebase-design, ISC.

A shared vocabulary and design guide for creating modules with clear, focused interfaces. It helps decide where boundaries belong and how to make code easier to test and navigate.

In plain words
What is it for?
Use it when designing or improving modules, choosing interfaces and seams, or making code easier for tests and coding agents to work with.
Why use it?
It helps reduce tangled code by encouraging clearer module boundaries and simpler interfaces.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions subagents.

Good fit Use it when designing or improving modules, choosing interfaces and seams, or making code easier for tests and coding agents to work with.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/j-star-films-studios/vibecode-protocol-suite/codebase-design
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.

Any agent
npx skills add J-StaR-Films-Studios/VibeCode-Protocol-Suite --skill codebase-design
Clone the repo
git clone --depth 1 https://github.com/J-StaR-Films-Studios/VibeCode-Protocol-Suite

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 codebase-design

README.md
[![agentmods](https://agentmods.dev/badge/skills/j-star-films-studios/vibecode-protocol-suite/codebase-design/github.svg)](https://agentmods.dev/skills/j-star-films-studios/vibecode-protocol-suite/codebase-design)
Your own site
<a href="https://agentmods.dev/skills/j-star-films-studios/vibecode-protocol-suite/codebase-design"><img src="https://agentmods.dev/badge/skills/j-star-films-studios/vibecode-protocol-suite/codebase-design/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.

agentmods 80×15 button for codebase-design

Your own site · 80×15
<a href="https://agentmods.dev/skills/j-star-films-studios/vibecode-protocol-suite/codebase-design"><img src="https://agentmods.dev/badge/skills/j-star-films-studios/vibecode-protocol-suite/codebase-design.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 57 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,349 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00057 $0.01349
Opus 5 $0.00028 $0.00674
Sonnet 5 $0.00011 $0.00270
Haiku 4.5 $0.00006 $0.00135

Measured 8d ago against content hash 2c20617f87ec, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

codebase-design 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 8d 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 codebase-design — 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.

assets/.agent/skills/web-dev-standards/codebase-design/SKILL.md · 115 lines

How it starts

The opening of the file, as written. The whole thing — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Codebase Design

Design deep modules: a lot of behaviour behind a small interface, placed at a clean seam, testable through that interface. Use this language and these principles wherever code is being designed or restructured. The aim is leverage for callers, locality for maintainers, and testability for everyone.

Glossary

Use these terms exactly: don't substitute "component," "service," "API," or "boundary." Consistent language is the whole point.

Module: anything with an interface and an implementation. Deliberately scale-agnostic: a function, class, package, or tier-spanning slice. Avoid: unit, component, service.

Interface: everything a caller must know to use the module correctly: the type signature, but also invariants, ordering constraints, error modes, required configuration, and performance characteristics. Avoid: API, signature (too narrow, they refer only to the type-level surface).

Implementation: what's inside a module, its body of code. Distinct from Adapter: a thing can be a small adapter with a large implementation (a Postgres repo) or a large adapter with a small implementation (an in-memory fake). Reach for "adapter" when the seam is the topic; "implementation" otherwise.

Depth: leverage at the interface. The amount of behaviour a caller (or test) can exercise per unit of interface they have to learn. A module is deep when a large amount of behaviour sits behind a small interface, shallow when the interface is nearly as complex as the implementation.

Seam (Michael Feathers): a place where you can alter behaviour without editing in that place; the location at which a module's interface lives. Where to put the seam is its own design decision, distinct from what goes behind it. Avoid: boundary (overloaded with DDD's bounded context).

Adapter: a concrete thing that satisfies an interface at a seam. Describes role (what slot it fills), not substance (what's inside).

Leverage: what callers get from depth. More capability per unit of interface they learn. One implementation pays back across N call sites and M tests.

Read the full file on GitHub · 115 lines

Files

What ships with it

2 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. 8d ago First seen · 115 lines · 57 tokens per session scan A 2c20617f87ec

Subscribe to this mod's changes

codebase-design is a skill published in the GitHub repository J-StaR-Films-Studios/VibeCode-Protocol-Suite (24 stars, last pushed yesterday), licensed ISC. It adds 57 tokens to every session and 1,349 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to codebase-design, differing in 0 lines, and is treated as a copy.

Related

Other skills, from other repositories

happiness-skill

A Chinese-language guide to happiness based on reducing unmet wants, focusing on the present, and treating happiness as a trainable skill.

kangarooking/cangjie-skill · 136 tokens

setup-matt-pocock-skills

A setup skill that configures engineering skills for a repository, including its issue tracker, labels, and documentation layout. A repository is the project folder managed by version control.

devcxl/mattpocock-skills-zh · 43 tokens

frontend-design

A design guide for building polished web interfaces such as pages, dashboards, forms, navigation, and reusable UI components. It covers HTML, CSS, JavaScript, and common frontend frameworks.

AnastasiyaW/codex-claude-code-config · 264 tokens

alterlab-cobrapy

Build and analyze genome-scale constraint-based metabolic models with COBRApy — flux balance analysis (FBA), flux variability analysis (FVA), gene and reaction knockouts, flux sampling, and SBML model I/O. Use when simulating metabolic networks, predicting growth or knockout phenotypes, or running systems-biology and…

AlterLab-IEU/AlterLab-Academic-Skills · 91 tokens

alterlab-depmap

Query the Cancer Dependency Map (DepMap) for cancer cell line gene dependency scores (CRISPR Chronos), drug sensitivity data, and gene effect profiles. Use when identifying cancer-specific genetic vulnerabilities, finding synthetic lethal interactions, checking whether a gene is essential in given cell lines, or…

AlterLab-IEU/AlterLab-Academic-Skills · 77 tokens

alterlab-qutip

Simulates open quantum systems with QuTiP, the Quantum Toolbox in Python, solving Lindblad master equations (mesolve), Monte Carlo trajectories (mcsolve), and unitary dynamics (sesolve). Use when studying master-equation or Lindblad dynamics, decoherence, dissipation, quantum optics, cavity QED, or open-system time…

AlterLab-IEU/AlterLab-Academic-Skills · 134 tokens