Borrowing it
Nothing to install: this file belongs to andrewesweet/ropey. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/andrewesweet/ropey/main/.agents/skills/clean-architecture/SKILL.mdgit clone --depth 1 https://github.com/andrewesweet/ropeyWrote 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/andrewesweet/ropey/clean-architecture)<a href="https://agentmods.dev/skills/andrewesweet/ropey/clean-architecture"><img src="https://agentmods.dev/badge/skills/andrewesweet/ropey/clean-architecture/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/andrewesweet/ropey/clean-architecture"><img src="https://agentmods.dev/badge/skills/andrewesweet/ropey/clean-architecture.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 | $0.03197 |
| Opus 5 | $0.00060 | $0.01598 |
| Sonnet 5 | $0.00024 | $0.00639 |
| Haiku 4.5 | $0.00012 | $0.00320 |
Grade A, and why
clean-architecture 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 9d 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 — 206 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Clean Architecture Framework
A disciplined approach to structuring software so that business rules remain independent of frameworks, databases, and delivery mechanisms. Apply these principles when designing system architecture, reviewing module boundaries, or advising on dependency management.
Core Principle
Source code dependencies must point inward — toward higher-level policies. Nothing in an inner circle can know anything about an outer circle. This single rule produces systems that are testable and independent of frameworks, UI, database, and any external agency. Business rules are what matter; databases, web frameworks, and delivery mechanisms are details — when details depend on policies, you can defer decisions, swap implementations, and test business logic in isolation.
Scoring
Goal: 10/10. Rate any architecture 0-10 against the principles below. Report the current score and the specific improvements needed to reach 10/10.
1. Dependency Rule and Concentric Circles
Core concept: Organize the architecture as concentric circles — Entities (enterprise business rules) innermost, then Use Cases (application business rules), then Interface Adapters, with Frameworks and Drivers outermost. Source code dependencies always point inward.
Why it works: When high-level policies don't depend on low-level details, you can swap the database, web framework, or API style without touching business logic — the system becomes resilient to the most volatile parts of the stack.
Key insights:
- Inner circles cannot mention outer circle names — no classes, functions, variables, or data formats from outside
- Data crossing a boundary must be in the form most convenient for the inner circle, never dictated by the outer
- Dependency Inversion (interfaces defined inward, implemented outward) is the mechanism that enforces the rule
- The number of circles is not fixed — four is typical; the rule stays the same
- Frameworks are details, not architecture — they belong in the outermost circle
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.
- 9d ago First seen · 206 lines · 120 tokens per session scan A 21ba9755dbfd
clean-architecture is a skill published in the GitHub repository andrewesweet/ropey (0 stars, last pushed 2mo ago), licensed MIT. It adds 120 tokens to every session and 3,197 once invoked, about $0.0006 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
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…
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…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
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…