What is ag-benchmark-qualidade?

A quality benchmark orchestrator for comparing an application’s AI output with a direct baseline. It runs scenarios, uses several evaluators, scores eight dimensions, and applies a plan-do-check-act improvement cycle.

Use it with an application URL to run all scenarios, selected scenarios, or a quick or full benchmark and calculate comparative quality results.

It shows whether an application performs comparably to a reference system, rather than judging the application in isolation.

ag-benchmark-qualidade — Skill for Claude Code by andregusman-raiz

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-benchmark-qualidade

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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/andregusman-raiz/a-gusman-claude/ag-benchmark-qualidade/github.svg)](https://agentmods.dev/skills/andregusman-raiz/a-gusman-claude/ag-benchmark-qualidade)

Your own site

<a href="https://agentmods.dev/skills/andregusman-raiz/a-gusman-claude/ag-benchmark-qualidade"><img src="https://agentmods.dev/badge/skills/andregusman-raiz/a-gusman-claude/ag-benchmark-qualidade/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/andregusman-raiz/a-gusman-claude/ag-benchmark-qualidade"><img src="https://agentmods.dev/badge/skills/andregusman-raiz/a-gusman-claude/ag-benchmark-qualidade.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 52 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,190 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. 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.

Model	Per session	Once invoked
Fable 5.1	$0.00052	$0.01190
Opus 5	$0.00026	$0.00595
Sonnet 5	$0.00010	$0.00238
Haiku 4.5	$0.00005	$0.00119

Measured 12d ago against content hash 4a1f8f24cbd2, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

ag-benchmark-qualidade 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/ag-benchmark-qualidade/SKILL.md · 95 lines

How it starts

The opening of the file, as written. The whole thing — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.

ag-benchmark-qualidade — QAT-Benchmark (Qualidade Comparativa)

Papel

O Benchmark Orchestrator: executa ciclo completo Plan-Do-Check-Act de QAT-Benchmark. Compara qualidade dos outputs da app contra baseline de mercado (Claude API direto), usando dual-run, triple-scorer com Judge Jury, e 8 dimensoes.

Diferenca de ag-testar-qualidade-qat: ag-testar-qualidade-qat avalia qualidade ABSOLUTA. ag-benchmark-qualidade avalia qualidade RELATIVA (parity). Diferenca de ag-testar-ux-qualidade: ag-testar-ux-qualidade avalia qualidade VISUAL/UI. ag-benchmark-qualidade avalia conteudo AI comparativamente. Diferenca de ag-criar-cenario-benchmark: ag-criar-cenario-benchmark CRIA cenarios. ag-benchmark-qualidade EXECUTA e orquestra PDCA.

Invocacao

/ag-benchmark-qualidade https://app.vercel.app                    # Standard mode, todos cenarios
/ag-benchmark-qualidade https://app.vercel.app BM-01,BM-03        # Cenarios especificos
/ag-benchmark-qualidade https://app.vercel.app all full            # Full jury (3 judges x 2 pos)
/ag-benchmark-qualidade https://app.vercel.app all smoke           # 5 cenarios core, rapido

Pre-requisitos

Estrutura tests/qat-benchmark/ no projeto (copiar de ~/.claude/shared/templates/qat-benchmark/)
QAT_BENCHMARK_BASE_URL ou URL no argumento
QAT_BENCHMARK_ANTHROPIC_KEY configurado (baseline + judge)
playwright-cli disponivel (app adapter)
URL da app acessivel

Ciclo PDCA

PLAN: Preflight + carregar KB (baselines, failure-patterns, learnings)
      Selecionar cenarios com anti-contaminacao (30% fixed + 70% rotatable)
DO:   Dual-run (app via Playwright + baseline via Claude API)
      Triple-score: L1-L2 rule-based → L3 Judge Jury → L4 functional
      Short-circuit: se L1 falha, skip jury (~30% economia)
CHECK: Classificar falhas (INFRA/FEATURE/QUALITY/BUSINESS/RUBRIC/FLAKY/BASELINE)
       Calcular Parity Index overall e por dimensao
       Comparar com baselines historicos, detectar regressoes
ACT:   Atualizar baselines, registrar failure patterns, adicionar learnings
       Gerar report PDCA com parity e classificacao

Read the full file on GitHub · 95 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.

12d ago First seen · 95 lines · 52 tokens per session scan A 4a1f8f24cbd2

Subscribe to this mod's changes

ag-benchmark-qualidade is a skill published in the GitHub repository andregusman-raiz/a-gusman-claude (19 stars, last pushed 4d ago), licensed MIT. It adds 52 tokens to every session and 1,190 once invoked, about $0.0003 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 2026-08-30.

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