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 igoruehara/spec-driven --skill camada-agenticagit clone --depth 1 https://github.com/igoruehara/spec-drivenWrote 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/igoruehara/spec-driven/camada-agentica)<a href="https://agentmods.dev/skills/igoruehara/spec-driven/camada-agentica"><img src="https://agentmods.dev/badge/skills/igoruehara/spec-driven/camada-agentica.svg" alt="Measured on agentmods" 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 | $0.00101 | $0.00538 |
| Opus 5 | $0.00051 | $0.00269 |
| Sonnet 5 | $0.00020 | $0.00108 |
| Haiku 4.5 | $0.00010 | $0.00054 |
Grade A, and why
camada-agentica 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 7d 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
Skill: Camada agêntica do projeto
Afina a camada que faz humanos e agentes operarem a esteira. Princípio: proponha com
justificativa (qual insumo motiva cada item), gere só o aprovado. Referência: docs/engineering/agentic-layer.md.
Reúna o contexto
Stack e quality gates (CLAUDE.md, ADRs), ferramentas (integrations.md), processo (Scrum/Kanban)
e domínio (context-map.md, glossary.md). É isso que decide quais artefatos fazem sentido.
Proponha (não gere sem OK)
- Rules: ajustes no
CLAUDE.mdpor stack;.claude/settings.jsoncom allowlist dos comandos comuns do stack e hooks. ⚠️ Permissões/hooks são sensíveis — confirme cada um. - Agents (subagentes) em
.claude/agents/<nome>.md(usedocs/engineering/_templates/subagent.template.md): ex.spec-reviewer(gate DoR),domain-modeler,adr-writer,<stack>-tester. - Skills em
.claude/skills/<nome>/(usedocs/engineering/_templates/skill.template.md): conforme as ferramentas,/spec-to-jira,/publicar-confluence(tools-aware). - Workflows: hooks no
settings.json(lint/teste noStop). Para a CI/CD (gates na pipeline) delegue à skill/setup-ci; para o gate de PR/MR, à/revisar-pr.
Regras
- Cada proposta cita o insumo que a motiva (ex.: stack Python →
pytest-tester+ allowlist). - Itens não aprovados viram itens de roadmap de adoção (sugira
/roadmap). - Mapeie cada artefato em
docs/engineering/agentic-layer.md.
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.
- 7d ago First seen · 29 lines · 101 tokens per session scan A e303378872c3
camada-agentica is a skill published in the GitHub repository igoruehara/spec-driven (213 stars, last pushed 1mo ago), licensed MIT. It adds 101 tokens to every session and 538 once invoked, about $0.0005 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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