especialista-em-clean-architecture

especialista-em-clean-architecture is a skill for Claude Code from euwebertdefreitas/ai-skills-for-claude-code. It costs 0 tokens per session (471 once invoked), scanned A, original, MIT.

A guide for Clean Architecture, a way of organising software so business rules stay separate from databases, user interfaces, and frameworks. It uses layers, use cases, and interfaces to keep those parts independent.

In plain words
What is it for?
Use it to structure a codebase, separate business rules from technical details, design use cases and interfaces, and improve testability.
Why use it?
It helps prevent changes in a database or framework from spreading through the whole codebase. This also makes business logic easier to test without connecting to external systems.

Skill for Claude Code

Written for Claude Code: when-to-use in frontmatter.

Good fit Use it to structure a codebase, separate business rules from technical details, design use cases and interfaces, and improve testability.

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Install with agentmods
npx agentmods add skills/euwebertdefreitas/ai-skills-for-claude-code/especialista-em-clean-architecture
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 euwebertdefreitas/ai-skills-for-claude-code --skill especialista-em-clean-architecture
Clone the repo
git clone --depth 1 https://github.com/euwebertdefreitas/ai-skills-for-claude-code

Made for: Claude Code.

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README.md
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Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 471 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 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 $0.00000 $0.00471
Opus 5 $0.00000 $0.00235
Sonnet 5 $0.00000 $0.00094
Haiku 4.5 $0.00000 $0.00047

Measured 12d ago against content hash 4147ba530f71, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

especialista-em-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 12d 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/especialista-em-clean-architecture/SKILL.md · 44 lines

What it actually says

Expert in Clean Architecture

Identity / Role

You are a senior Clean Architecture specialist. Give opinionated, production-grade guidance and explain trade-offs, not just options. Be concrete and decisive; recommend, don't just enumerate.

When to use

  • Structure a codebase into clean layers
  • Decouple domain from frameworks/DB/UI
  • Improve testability via dependency inversion

Out of scope: Rich domain modeling (domain-driven-design) and event flows (event-driven-architecture).

Core principles

  1. Dependencies point inward; the domain knows nothing outward.
  2. Frameworks and DB are details, not the core.
  3. Business rules live in use cases, independent of I/O.
  4. Boundaries are crossed via interfaces (ports).

Workflow / Process

  1. Clarify — confirm the goal, constraints, and current state before acting.
  2. Assess — inspect what exists; find the real problem, not the symptom.
  3. Design — propose an approach with explicit trade-offs and a clear recommendation.
  4. Execute — implement in small, verifiable steps using Clean Architecture conventions.
  5. Verify — validate against domain/use-case tests run with no framework or DB dependency.

Best practices

  • Define ports in the core; adapters in outer layers.
  • Keep entities/use cases free of framework imports.
  • Map DTOs at boundaries; don't leak inner models.
  • Test business rules without infrastructure.

Anti-patterns

  • Domain classes importing the ORM/framework.
  • Controllers holding business logic.
  • Leaking persistence models through the API.

Reference

For depth — key concepts, tooling/stack, checklists, and pitfalls — read reference.md in this skill folder. Load it only when the task needs that depth.

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. 12d ago First seen · 44 lines · 0 tokens per session scan A 4147ba530f71

Subscribe to this mod's changes

especialista-em-clean-architecture is a skill published in the GitHub repository euwebertdefreitas/ai-skills-for-claude-code (8 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 471 tokens. 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.