ag-otimizar-codigo

ag-otimizar-codigo is a skill for Claude Code from andregusman-raiz/a-gusman-claude. It costs 35 tokens per session (1,076 once invoked), scanned A, original, MIT.

A code-improvement workflow that measures performance and readability before and after changes. It focuses on finding a measured bottleneck before changing the code.

In plain words
What is it for?
Use it to improve a selected part of a codebase, especially React or Next.js applications, and compare the resulting performance measurements.
Why use it?
It prevents optimization based on guesswork and shows whether a change actually helped. The comparison can cover measures such as bundle size, render time, API delay, or Lighthouse scores.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter. Also seen: model in frontmatter; mentions subagents.

Good fit Use it to improve a selected part of a codebase, especially React or Next.js applications, and compare the resulting performance measurements.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/andregusman-raiz/a-gusman-claude/ag-otimizar-codigo
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 andregusman-raiz/a-gusman-claude --skill ag-otimizar-codigo
Clone the repo
git clone --depth 1 https://github.com/andregusman-raiz/a-gusman-claude

Made for: Claude Code.

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 ag-otimizar-codigo

README.md
[![agentmods](https://agentmods.dev/badge/skills/andregusman-raiz/a-gusman-claude/ag-otimizar-codigo/github.svg)](https://agentmods.dev/skills/andregusman-raiz/a-gusman-claude/ag-otimizar-codigo)
Your own site
<a href="https://agentmods.dev/skills/andregusman-raiz/a-gusman-claude/ag-otimizar-codigo"><img src="https://agentmods.dev/badge/skills/andregusman-raiz/a-gusman-claude/ag-otimizar-codigo/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 ag-otimizar-codigo

Your own site · 80×15
<a href="https://agentmods.dev/skills/andregusman-raiz/a-gusman-claude/ag-otimizar-codigo"><img src="https://agentmods.dev/badge/skills/andregusman-raiz/a-gusman-claude/ag-otimizar-codigo.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 35 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,076 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Excessive Agency · line 4
    Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.
    Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
How audits are shown
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 $0.00035 $0.01076
Opus 5 $0.00017 $0.00538
Sonnet 5 $0.00007 $0.00215
Haiku 4.5 $0.00003 $0.00108

Measured 9d ago against content hash 7541d0465922, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

ag-otimizar-codigo scanned grade A with 1 finding 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

Prioridade: executar medicoes via CLI (lighthouse, bundle-analyzer, curl).
skills/ag-otimizar-codigo/SKILL.md · 96 lines

How it starts

The opening of the file, as written. The whole thing — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.

ag-otimizar-codigo — Otimizar Codigo

Spawn the ag-otimizar-codigo agent to optimize code performance with before/after measurements.

Invocation

Use the Agent tool with:

  • subagent_type: ag-otimizar-codigo
  • mode: bypassPermissions
  • run_in_background: true
  • prompt: Compose from template below + $ARGUMENTS

Prompt Template

Projeto: [CWD or user-provided path]
Area: [module or area to optimize from $ARGUMENTS]
Benchmark: [specific metric if provided, otherwise "auto-detect"]


## Output
- Metricas antes/depois: bundle size, render time, API latency, Lighthouse scores
- Relatorio de delta com melhorias documentadas
- Codigo otimizado com commits por otimizacao

Regra de ouro: "Otimizar sem medir e adivinhar."
1. Medir ANTES (bundle size, render time, API latency, Lighthouse, etc.)
2. Identificar gargalo
3. Otimizar
4. Medir DEPOIS
5. Comparar e reportar delta

Prioridade: executar medicoes via CLI (lighthouse, bundle-analyzer, curl).
Worktree isolation ativo.

Checklist explicito de otimizacao React/Next.js

Para projetos com React/Next, o agente DEVE verificar TODOS estes pontos antes de declarar otimizacao completa:

Re-renders desnecessarios

  • Componentes que rerenderizam frequentemente sem mudanca de props → candidato a React.memo
  • Funcoes inline em props (onClick={() => ...}) → candidato a useCallback
  • Objetos/arrays inline em props (style={{...}}, data={[...]}) → candidato a useMemo ou constante
  • Calculos custosos no render body → candidato a useMemo

Listas e dados grandes

  • Listas com > 200 itens sem virtualizacao → adicionar react-window ou @tanstack/react-virtual
  • Tabelas grandes sem pagination + virtualization → considerar @tanstack/react-table + virtual
  • .map() aninhado em arrays grandes (O(n*m)) → indexar via Map/Object lookup
  • Filtros/sorts no render (nao memoizados) → mover para useMemo

Imagens e media

  • <img> nativo em projeto Next.js → migrar para next/image (auto lazy + responsive + format)
  • Imagens sem width/height explicitos → CLS (layout shift)
  • Imagens > 200KB sem compressao → otimizar via sharp ou Next.js Image Optimization
  • Imagens above-the-fold sem priority → LCP ruim
  • Background images sem lazy → carregar tarde
  • SVGs grandes nao otimizados → SVGO + considerar React component inline

Read the full file on GitHub · 96 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. 9d ago First seen · 96 lines · 35 tokens per session scan A 7541d0465922

Subscribe to this mod's changes

ag-otimizar-codigo is a skill published in the GitHub repository andregusman-raiz/a-gusman-claude (19 stars, last pushed 4d ago), licensed MIT. It adds 35 tokens to every session and 1,076 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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