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 ricneves-ai/flowgrammers-skills --skill caio-advisorgit clone --depth 1 https://github.com/ricneves-ai/flowgrammers-skillsWrote 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/ricneves-ai/flowgrammers-skills/caio-advisor)<a href="https://agentmods.dev/skills/ricneves-ai/flowgrammers-skills/caio-advisor"><img src="https://agentmods.dev/badge/skills/ricneves-ai/flowgrammers-skills/caio-advisor/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/ricneves-ai/flowgrammers-skills/caio-advisor"><img src="https://agentmods.dev/badge/skills/ricneves-ai/flowgrammers-skills/caio-advisor.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 | $0.00127 | $0.01776 |
| Opus 5.5 | $0.00051 | $0.00710 |
| Sonnet 5.5 | $0.00025 | $0.00355 |
| Haiku 4.5 | $0.00013 | $0.00178 |
Grade A, and why
caio-advisor 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 1mo 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 — 153 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Assessor de CAIO (Chief AI Officer)
Frameworks para liderança de IA corporativa: estratégia, governança, plataforma, segurança, ROI e conformidade regulatória no contexto brasileiro.
Palavras-chave
CAIO, Chief AI Officer, estratégia de IA, IA corporativa, IA generativa, LLM, LLMOps, MLOps, AI governance, responsible AI, AI safety, AI Act, PL 2338/23, Marco Legal da IA, LGPD, build vs buy, ROI de IA, copilots, agentes
Responsabilidades Principais
1. Estratégia de IA Corporativa
IA sem estratégia vira pilha de POCs abandonadas. O CAIO conecta IA à estratégia de negócios.
Framework 3 horizontes:
- H1 (0-6m): Produtividade interna — copilots, atendimento, busca interna
- H2 (6-18m): Produtos existentes — features de IA, personalização, automação
- H3 (18-36m): Modelos de negócio novos — IA como produto, agentes autônomos
Princípios:
- IA não é estratégia. Resultado de negócio é.
- Priorize por valor × viabilidade × risco
- Construa plataforma uma vez, use em N casos
- Meça ROI em todos os casos — mate o que não performa
2. Priorização de Casos de Uso
Nem todo problema merece IA. Use o framework VUR:
V — Valor
- Receita incremental ou custo reduzido
- Quantifique em R$/ano (não em "eficiência")
- Verifique com dono de P&L antes de investir
U — Usabilidade (Viabilidade)
- Dados disponíveis, limpos, com volume suficiente?
- Tolerância a erro (crítico = menos IA, mais humano no loop)
- Integração com sistemas legados
R — Risco
- Regulatório (LGPD, setorial — ANVISA, BACEN, CVM)
- Reputacional (alucinação, viés, privacidade)
- Operacional (degradação, concept drift, dependência de fornecedor)
Scorecard: cada dimensão de 1-5. Priorize os casos >= 12/15.
3. Build vs. Buy vs. Partner
Framework decisório:
| Critério | Build | Buy (SaaS) | Partner |
|---|---|---|---|
| Diferenciação competitiva | Alta | Baixa | Média |
| Dados sensíveis/proprietários | Sim | Não | Depende |
| Escala de uso | Alto volume | Início/baixo | Pilotos |
| Time interno | Sênior + estável | Qualquer | Híbrido |
| Time-to-value | 6-12m | 2-4 semanas | 1-3m |
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.
- 1mo ago First seen · 153 lines · 127 tokens per session scan A 6b783e461a2f
caio-advisor is a skill published in the GitHub repository ricneves-ai/flowgrammers-skills (116 stars, last pushed 1mo ago), licensed MIT. It adds 127 tokens to every session and 1,776 once invoked, about $0.0005 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.
Other skills, from other repositories
prowler-compliance
Creates, syncs, audits and manages Prowler compliance frameworks end-to-end. Covers the two supported JSON schemas (universal multi-provider and legacy per-provider), the SDK model tree (legacy attribute classes, universal ComplianceFramework, ConfigRequirements guardrails), output formatters (legacy per-framework +…
policy
Define and enforce decision policies, compliance rules, and exceptions over Semantica graphs. Uses ContextGraph.checkdecisionrules/enforcedecisionpolicy and context.PolicyEngine.
ai-ethics-review
Conduct a structured ethical review of an AI or ML feature, model, or product. Use when preparing to deploy an AI system, assessing algorithmic risk, auditing a model for bias, or producing a responsible AI impact assessment. Produces a structured ethics review covering fairness, transparency, privacy, safety…
open-weights
Use when choosing an open-weight LLM and clearing it for use — which family and size fit the task, the hardware and the budget, and above all whether the license permits shipping. Owns the license-class map (OSI-open versus custom-community versus non-commercial), the always-verify-the-model-card rule, size-to-VRAM…
801-regulations-eu-ai-act
Use when reviewing, designing, or modifying Java enterprise systems that use AI, LLMs, AI agents, RAG, tool calling, workflow automation, or model-based decision support and need EU AI Act regulatory awareness. This should trigger for requests such as Review a Java AI system for EU AI Act controls; Design governance…
813-regulations-iso-42001
Use when reviewing, designing, or modifying Java enterprise systems that use GenAI, LLMs, AI-assisted coding, RAG, AI agents, generated code, generated dependencies, prompt workflows, external model providers, or AI-enabled business logic and need ISO/IEC 42001 AI management system-aware engineering guidance. Part of…