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.
npx skills add andregusman-raiz/a-gusman-claude --skill ag-auditar-mcpgit clone --depth 1 https://github.com/andregusman-raiz/a-gusman-claudeWrote 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/andregusman-raiz/a-gusman-claude/ag-auditar-mcp)<a href="https://agentmods.dev/skills/andregusman-raiz/a-gusman-claude/ag-auditar-mcp"><img src="https://agentmods.dev/badge/skills/andregusman-raiz/a-gusman-claude/ag-auditar-mcp/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/andregusman-raiz/a-gusman-claude/ag-auditar-mcp"><img src="https://agentmods.dev/badge/skills/andregusman-raiz/a-gusman-claude/ag-auditar-mcp.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 | $0.00053 | $0.02054 |
| Opus 5.5 | $0.00021 | $0.00822 |
| Sonnet 5.5 | $0.00011 | $0.00411 |
| Haiku 4.5 | $0.00005 | $0.00205 |
Grade A, and why
ag-auditar-mcp 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 2mo 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 — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ag-auditar-mcp — auditoria da superficie MCP e de skills de terceiros
Por que existe (delimitacao vs ag-auditar-harness)
ag-auditar-harness / HCS.injection cobre codigo do harness: eval $(...) em hook,
bash -c "$var", curl | sh. Este skill cobre um vetor diferente e nao coberto:
texto que o modelo le como dado e obedece como instrucao.
Uma tool MCP anuncia um name e uma description em linguagem natural. O modelo le a
description antes de decidir chamar a tool. Instrucao escondida ali e obedecida sem
que nada apareca para o usuario — e injecao indireta entregue pela cadeia de suprimentos
(OWASP MCP03:2025, MITRE ATLAS AML.T0010 / AML.T0051.001). O mesmo vale para
o description: de qualquer SKILL.md de terceiro instalado no harness.
Quando invocar
- Antes de adicionar um MCP server novo (proprio ou de terceiro)
- Antes de instalar skills/plugins de terceiro — o
--scanroda no repo clonado, antes do install - Periodicamente, para pegar rug pull: um servidor ja aprovado cuja config/descricao muda depois
- Quando um agente tomou acao inesperada compativel com tool poisoning
Ferramenta local (offline, stdlib, nao executa MCP server)
S=~/Claude/.claude/scripts/mcp-baseline-audit.py
python3 $S # inventario + diff contra baseline
python3 $S --save-baseline # (re)arma deteccao de rug pull
python3 $S --scan-skills <dir> # varre SKILL.md de terceiros antes de instalar
python3 $S --json # machine-readable
python3 $S --strict # exit 2 se houver P0 (uso em gate/CI)
Baseline: ~/.claude/state/mcp-baseline.json (hash de command/args/url/chaves de
env e headers por servidor). Mudanca silenciosa nesse conjunto = P0 config mudou.
O que ele detecta:
| Sinal | Sev | Por que importa |
|---|---|---|
| Config de servidor mudou vs baseline | P0 | rug pull: aprovado num estado, rodando em outro |
| Instrucao ao assistente em descricao ("ignore previous", "nao conte ao usuario") | P0 | tool/skill poisoning |
| Caractere invisivel (ZWSP/ZWJ/BOM) ou bidi override | P0 | payload escondido do revisor humano |
Path de segredo (~/.ssh, id_rsa, .aws/credentials) em descricao |
P0 | alvo classico de exfiltracao |
curl | sh no start do servidor |
P0 | download+exec a cada boot |
Transporte http:// remoto sem TLS |
P0 | tool call em claro |
npx -y pkg@latest sem pin de versao |
P1 | codigo remoto novo a cada start, sem revisao |
Segredo literal em env/headers e config legivel por outros |
P1 | qualquer processo da maquina le — chmod 600 |
| Segredo literal em config ja 0600 | P2 | aceito: mover para env var nao melhora (ver abaixo) |
| Servidor novo desde o baseline | P1 | entrou sem passar por revisao |
| Homoglifo CYRILLIC+LATIN no nome | P1 | typosquat de tool confiavel |
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.
- 2mo ago First seen · 135 lines · 53 tokens per session scan F aebced019786
ag-auditar-mcp is a skill published in the GitHub repository andregusman-raiz/a-gusman-claude (18 stars, last pushed 1mo ago), licensed MIT. It adds 53 tokens to every session and 2,054 once invoked, about $0.0002 per session on Opus 5.5. 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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