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 tatagoncalvesof/imperatriz-toolkit --skill skill-lancamento-digitalgit clone --depth 1 https://github.com/tatagoncalvesof/imperatriz-toolkitWrote 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/tatagoncalvesof/imperatriz-toolkit/skill-lancamento-digital)<a href="https://agentmods.dev/skills/tatagoncalvesof/imperatriz-toolkit/skill-lancamento-digital"><img src="https://agentmods.dev/badge/skills/tatagoncalvesof/imperatriz-toolkit/skill-lancamento-digital/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/tatagoncalvesof/imperatriz-toolkit/skill-lancamento-digital"><img src="https://agentmods.dev/badge/skills/tatagoncalvesof/imperatriz-toolkit/skill-lancamento-digital.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 | $0.00090 | $0.02361 |
| Opus 5 | $0.00045 | $0.01180 |
| Sonnet 5 | $0.00018 | $0.00472 |
| Haiku 4.5 | $0.00009 | $0.00236 |
Grade A, and why
skill-lancamento-digital scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 210 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Lançamento Digital
Gerar materiais completos para lançamentos digitais no mercado brasileiro — cronograma, emails, copy, WhatsApp, redes sociais — usando a metodologia consagrada de lançamento (baseada na Product Launch Formula adaptada para o Brasil).
Contexto do Mercado Brasileiro
O lançamento digital brasileiro segue uma estrutura testada e validada:
- Antecipação antes do evento principal
- CPL (Conteúdo de Pré-Lançamento) em 3-4 aulas/lives gratuitas
- Abertura e fechamento de carrinho com prazo definido (5-7 dias)
- Urgência e escassez como gatilhos de decisão
- WhatsApp como canal #1 de engajamento e conversão
- Plataformas de venda: Hotmart, Eduzz, Kiwify, Monetizze
- Moeda: R$ (Real brasileiro)
- Tom: próximo, empático, transformacional, com autoridade
Fases do Lançamento
Fase 1 — Definição do Produto (Dia -30 a -25)
Coletar informações essenciais antes de gerar qualquer material:
- Nome do produto (curso, mentoria, programa, imersão)
- Público-alvo (avatar detalhado: dor, desejo, objeções)
- Transformação prometida (de onde para onde)
- Preço e condições (à vista, parcelado, bônus early bird)
- Data de abertura e fechamento do carrinho
- Formato do CPL (lives no Instagram, aulas gravadas, evento presencial)
- Canais disponíveis (email, WhatsApp, Instagram, Telegram)
- Bônus oferecidos (listar todos com valor percebido)
- Garantia (7 dias, 15 dias, 30 dias)
- Link de vendas (Hotmart/plataforma)
Fase 2 — Pré-Lançamento (Dia -25 a -8)
Objetivo: aquecer a audiência e gerar antecipação.
Gerar os seguintes materiais:
- Sequência de posts para redes sociais (ver
references/social-media-calendar.md) - Emails de aquecimento e convite para o evento (ver
references/emails-lancamento.md, seção Pré-Lançamento) - Mensagens de WhatsApp para lista de espera (ver
references/whatsapp-sequences.md, seção Pré-Lançamento) - Cronograma detalhado dia a dia (ver
references/cronograma-lancamento.md, Fase 2)
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago First seen · 210 lines · 90 tokens per session scan A 6938375e3388
skill-lancamento-digital is a skill published in the GitHub repository tatagoncalvesof/imperatriz-toolkit (2 stars, last pushed 3mo ago), licensed MIT. It adds 90 tokens to every session and 2,361 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 2026-08-31.
Other skills, from other repositories
codex-setup
Initialize sd0x-dev-flow infrastructure for Codex CLI and other non-Claude agents. Generates AGENTS.md, installs the commit-msg hook, copies runner scripts. The pre-push gate is opt-in via --with-push-gate. Use when setting up a new project or after updating skills.
smart-rebase
Smart partial rebase for squash-merge repositories. Auto-detect which commits to keep/drop when base branch was squash-merged into target. Use when: user says 'rebase', 'partial rebase', 'base already merged', 'smart rebase', or /smart-rebase. Not for: simple git rebase (the developer runs it — Claude never executes…
test-review
Test coverage review via Codex exec. Use when: reviewing test sufficiency, identifying coverage gaps, test quality audit. Not for: generating tests (use codex-test-gen), code review (use codex-code-review). Output: coverage analysis + gap report.
debug
Interactive debugging workflow with hypothesis-driven probe loop. Use when: unknown bugs, script errors, silent failures, troubleshooting. Not for: known bugs (use bug-fix), GitHub issue analysis (use issue-analyze), code understanding (use code-explore). Output: debug report with probe journal + root cause + fix.
runbook
Generate and update feature release runbooks from existing docs and codebase. Use when: creating operational runbook, release handbook, deployment checklist, pre-release preparation. Not for: incident response (v2), code review (use codex-code-review), architecture design (use architecture).
feature-dev
Feature development workflow. Use when: implementing features, writing code, running dev loop. Not for: understanding code (use code-explore), reviewing code (use codex-code-review). Output: implemented feature + tests + review gate.