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.
git clone --depth 1 https://github.com/linofcp007/advogado-ptWrote 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/commands/linofcp007/advogado-pt/parecer)<a href="https://agentmods.dev/commands/linofcp007/advogado-pt/parecer"><img src="https://agentmods.dev/badge/commands/linofcp007/advogado-pt/parecer/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/commands/linofcp007/advogado-pt/parecer"><img src="https://agentmods.dev/badge/commands/linofcp007/advogado-pt/parecer.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 | $0.00021 | $0.00311 |
| Opus 5 | $0.00010 | $0.00156 |
| Sonnet 5 | $0.00004 | $0.00062 |
| Haiku 4.5 | $0.00002 | $0.00031 |
Grade A, and why
parecer 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 8d 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.
What it actually says
Ativa a skill advogado-pt. Produz um parecer jurídico estruturado sobre a situação em $ARGUMENTS, seguindo o formato de parecer do SKILL.md (SITUAÇÃO · ENQUADRAMENTO · POSIÇÃO · OPÇÕES · RECOMENDAÇÃO · PRAZOS).
Parte do template parecer-juridico (via tool MCP obter_template com nome: parecer-juridico, ou lê assets/templates/parecer-juridico.md). Cita diplomas/artigos com rigor e sinaliza o nível de confiança quando a citação for determinante.
EN: Activate the advogado-pt skill. Produce a structured legal opinion on the situation in $ARGUMENTS, following the opinion format in SKILL.md (SITUATION · FRAMEWORK · POSITION · OPTIONS · RECOMMENDATION · DEADLINES). Start from the parecer-juridico template (via the obter_template MCP tool with nome: parecer-juridico, or read assets/templates/parecer-juridico.md). Cite statutes/articles precisely and flag the confidence level when a citation is decisive.
Exemplos · Examples: "preciso de um parecer sobre rescindir este contrato", "give me a written legal opinion on this dispute".
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.
- 8d ago First seen · 13 lines · 21 tokens per session scan A f719feae6e55
parecer is a command published in the GitHub repository linofcp007/advogado-pt (0 stars, last pushed 1mo ago), licensed MIT. It adds 21 tokens to every session and 311 once invoked, about $0.0001 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.
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rescisao
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checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.