ai-dev-skillset: Skill for Claude Code

.agents/skills/quality-revisao-aderencia/SKILL.md

quality-revisao-aderencia is a skill for Claude Code, Codex from gianverdum/ai-dev-skillset. It costs 249 tokens per session (7,706 once invoked), scanned A, original, MIT.

A review checklist for checking whether a coding task followed the project's skills and rules before it is declared finished.

In plain words
What is it for?
Use it as the final review after implementation, refactoring, fixes, extensions, or major development stages.
Why use it?
It helps catch missed requirements and prevents claiming that work is done when important checks are still failing.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents).

This is gianverdum/ai-dev-skillset's own configuration. It tells Claude Code and Codex how to work on ai-dev-skillset itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything ai-dev-skillset configures →

Reuse

Borrowing it

Nothing to install: this file belongs to gianverdum/ai-dev-skillset. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/gianverdum/ai-dev-skillset/main/.agents/skills/quality-revisao-aderencia/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/gianverdum/ai-dev-skillset

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 quality-revisao-aderencia

README.md
[![agentmods](https://agentmods.dev/badge/skills/gianverdum/ai-dev-skillset/quality-revisao-aderencia/github.svg)](https://agentmods.dev/skills/gianverdum/ai-dev-skillset/quality-revisao-aderencia)
Your own site
<a href="https://agentmods.dev/skills/gianverdum/ai-dev-skillset/quality-revisao-aderencia"><img src="https://agentmods.dev/badge/skills/gianverdum/ai-dev-skillset/quality-revisao-aderencia/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 quality-revisao-aderencia

Your own site · 80×15
<a href="https://agentmods.dev/skills/gianverdum/ai-dev-skillset/quality-revisao-aderencia"><img src="https://agentmods.dev/badge/skills/gianverdum/ai-dev-skillset/quality-revisao-aderencia.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 249 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 7,706 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 $0.00249 $0.07706
Opus 5 $0.00125 $0.03853
Sonnet 5 $0.00050 $0.01541
Haiku 4.5 $0.00025 $0.00771

Measured 12d ago against content hash 9706eba3c5b9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

quality-revisao-aderencia 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.

.agents/skills/quality-revisao-aderencia/SKILL.md · 290 lines

How it starts

The opening of the file, as written. The whole thing — 290 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Revisao de Aderencia a Skills e Rules

Use esta skill como ultima etapa antes de declarar uma tarefa concluida e, em mudancas grandes, tambem ao terminar cada etapa significativa (modulo novo, camada nova, refator estrutural). O objetivo e fechar o ciclo TDD/quality e impedir desvios silenciosos.

Quando rodar

Regra absoluta de gatilho — antes de qualquer frase de conclusao:

Antes de escrever no resumo final QUALQUER uma destas frases (ou equivalente em outro idioma), VOCE PRECISA ter rodado a checklist objetiva desta skill:

  • "concluido" / "completo" / "completa" / "pronto" / "feito" / "terminei" / "finalizado" / "encerrado"
  • "the refactoring is complete" / "refactor is done" / "implementation complete" / "all done"
  • "refatoracao concluida" / "feature pronta" / "task pronta" / "tudo certo"
  • Qualquer declaracao categorica de fim de tarefa (mesmo implicita: "rodei tudo, passou", "all checks pass", etc.)

Se a checklist objetiva (secao "Pontos a verificar") tem 2 ou mais itens vermelhos, voce esta PROIBIDO de usar qualquer dessas frases. Use o formato WIP transparente em vez (secao "Formato no reporte final QUANDO refatoracao esta em WIP").

Declarar conclusao com itens vermelhos sem WIP = DESVIO grave de honestidade, anula o credito do trabalho feito.

Outros gatilhos:

  • Ao terminar uma implementacao, fix ou refator, antes do resumo final ao usuario.
  • Ao concluir um modulo novo, antes de seguir para o proximo.
  • Ao concluir uma camada (domain/application/interface) novamente, antes de seguir.
  • Sempre que uma extensao criar modulo novo: aplique a checklist completa SEPARADAMENTE ao modulo novo (suite e2e propria, README proprio, cobertura propria, literal unions, etc.), mesmo que o modulo existente ja tenha cobertura completa.
  • Quando o usuario pedir explicitamente revisao de aderencia.

Sintoma da skill nao rodada (auto-deteccao):

Se voce esta prestes a escrever uma frase de conclusao e NAO consegue listar mentalmente o status (❌/✅) dos 9 itens da checklist objetiva nem dos anti-padroes desta secao, voce nao rodou a skill. Pare, leia esta skill, rode item-a-item, depois decida entre "concluido" ou "WIP transparente".

Read the full file on GitHub · 290 lines

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 · 290 lines · 0 tokens per session scan A 9706eba3c5b9

Subscribe to this mod's changes

quality-revisao-aderencia is a skill published in the GitHub repository gianverdum/ai-dev-skillset (5 stars, last pushed 2mo ago), licensed MIT. It adds 249 tokens to every session and 7,706 once invoked, about $0.0012 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.