GROWTH-ENGINE -- Crescimento Exponencial

Overview

This public intake copy packages

plugins/antigravity-awesome-skills-claude/skills/growth-engine

https://github.com/sickn33/antigravity-awesome-skills

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses

metadata.json

ORIGIN.md

GROWTH-ENGINE -- Crescimento Exponencial

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: How It Works, Pirate Metrics (Aarrr) Para Auri, Checklist Seo Para Landing Page Auri, Keywords Estrategicas Auri, Amazon Skill Store Optimization, Tipos De Viral Loops Para Auri.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• When you need specialized assistance with this domain
• The task is unrelated to growth engine
• A simpler, more specific tool can handle the request
• The user needs general-purpose assistance without domain expertise
• Use when the request clearly matches the imported source intent: Motor de crescimento para produtos digitais -- growth hacking, SEO, ASO, viral loops, email marketing, CRM, referral programs e aquisicao organica.
• Use when the operator should preserve upstream workflow detail instead of rewriting the process from scratch.

Operating Table

metadata.json

ORIGIN.md

SKILL.md

SKILL.md

## Related Skills

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. Confirm the user goal, the scope of the imported workflow, and whether this skill is still the right router for the task.
2. Read the overview and provenance files before loading any copied upstream support files.
3. Load only the references, examples, prompts, or scripts that materially change the outcome for the current request.
4. Execute the upstream workflow while keeping provenance and source boundaries explicit in the working notes.
5. Validate the result against the upstream expectations and the evidence you can point to in the copied files.
6. Escalate or hand off to a related skill when the work moves out of this imported workflow's center of gravity.
7. Before merge or closure, record what was used, what changed, and what the reviewer still needs to verify.

Imported Workflow Notes

Imported: Overview

Motor de crescimento para produtos digitais -- growth hacking, SEO, ASO, viral loops, email marketing, CRM, referral programs e aquisicao organica. Ativar para: criar estrategia de growth, SEO tecnico, ASO para app stores, programa de referral, email marketing, viral coefficient, funil de aquisicao, conteudo para crescimento organico, campanhas de lancamento.

Imported: How It Works

O melhor marketing e um produto que as pessoas amam. -- Sam Altman Crescimento real comeca com um produto que vale a pena recomendar.

Examples

Example 1: Ask for the upstream workflow directly

Use @growth-engine to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @growth-engine against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @growth-engine for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @growth-engine using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• Provide clear, specific context about your project and requirements
• Review all suggestions before applying them to production code
• Combine with other complementary skills for comprehensive analysis
• Keep the imported skill grounded in the upstream repository; do not invent steps that the source material cannot support.
• Prefer the smallest useful set of support files so the workflow stays auditable and fast to review.
• Keep provenance, source commit, and imported file paths visible in notes and PR descriptions.
• Point directly at the copied upstream files that justify the workflow instead of relying on generic review boilerplate.

Imported Operating Notes

Imported: Best Practices

• Provide clear, specific context about your project and requirements
• Review all suggestions before applying them to production code
• Combine with other complementary skills for comprehensive analysis

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in

plugins/antigravity-awesome-skills-claude/skills/growth-engine

metadata.json

ORIGIN.md

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated

SKILL.md

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Related Skills

• @github-issue-creator

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @github-workflow-automation

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @gitlab-automation

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @gitlab-ci-patterns

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

references

references/n/a

examples

examples/n/a

scripts

scripts/n/a

agents

agents/n/a

assets

assets/n/a

Imported Reference Notes

Imported: Pirate Metrics (Aarrr) Para Auri

AQUISICAO: Como as pessoas descobrem a Auri? Meta: 10.000 visitantes/mes -> 1.000 cadastros Canais: SEO, Product Hunt, Influencers tech, PR

ATIVACAO:   Quando o usuario experimenta o primeiro valor?
            Meta: 60% completam primeira conversa em 24h
            Metrica: First Conversation Rate (FCR)

RETENCAO:   As pessoas voltam?
            Meta: D7 = 30%, D30 = 15%, D90 = 8%
            Metrica: WAC (Weekly Active Conversationalists)

RECEITA:    As pessoas pagam?
            Meta: 8% trial->Pro conversao
            Metrica: MRR, ARPU, LTV

REFERENCIA: As pessoas indicam?
            Meta: NPS > 50, Viral Coefficient > 0.3
            Metrica: Referrals per user, K-factor

Imported: Checklist Seo Para Landing Page Auri

<meta property="og:title" content="Auri -- IA de Voz para Alexa">
<meta property="og:description" content="O primeiro assistente de voz
com raciocinio real. Powered by Claude.">

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "SoftwareApplication",
  "name": "Auri",
  "operatingSystem": "Amazon Alexa",
  "applicationCategory": "AI Assistant",
  "offers": {"@type": "Offer", "price": "0"},
  "aggregateRating": {"@type": "AggregateRating",
                         "ratingValue": "4.8", "ratingCount": "127"}
}
</script>

Imported: Keywords Estrategicas Auri

High Intent (converter): - "skill alexa inteligente" - "assistente alexa com ia" - "como usar claude no alexa"

Informacional (educar):
- "assistente de voz ia brasil"
- "melhor skill alexa portugues"

Long tail (baixa competicao):
- "alexa responder perguntas complexas"
- "skill alexa analise de negocios"

Imported: Amazon Skill Store Optimization

skill_name: "Auri -- IA de Voz Inteligente" invocation: "auri"

short_description: >
  Auri transforma seu Alexa em um assistente verdadeiramente inteligente.
  Powered by Claude AI -- pensa, recorda e evolui com voce.

long_description: >
  Chega de respostas rasas. Auri e o primeiro assistente de voz com
  raciocinio real para o mercado brasileiro.

  O QUE A AURI FAZ:
  - Analisa problemas de negocio complexos
  - Recorda conversas anteriores (memoria real)
  - Oferece perspectivas de especialistas
  - Aprende suas preferencias ao longo do tempo

  COMO COMECAR: Diga "Alexa, abrir Auri" e comece a conversar naturalmente.

example_phrases:
  - "Alexa, abrir Auri"
  - "Me ajuda a decidir entre essas duas opcoes de negocio"
  - "Analisa esse problema para mim"

keywords: "ia, inteligencia artificial, assistente inteligente, claude, negocios"

Imported: Tipos De Viral Loops Para Auri

Loop 1: WORD-OF-MOUTH ORGANICO Trigger: usuario tem conversa impressionante com Auri Acao: comenta com amigos/nas redes Meta: cada usuario traz 0.3 novos usuarios (K=0.3)

Loop 2: SHARE DE INSIGHTS
Trigger: Auri gera insight especialmente bom
Acao: botao "Compartilhar esse insight" -> post pronto para redes
Meta: 5% das conversas geram um share

Loop 3: REFERRAL PROGRAM
Incentivo: Ganhe 1 mes Pro por cada amigo que assinar
Meta: 10% dos usuarios Pro indicam pelo menos 1 pessoa

Imported: Calculadora De Viral Coefficient

def calculate_k_factor(percent_who_invite, invites_per_user, conversion_rate): k = percent_who_invite * invites_per_user * conversion_rate if k >= 1: status = "Crescimento viral (cada usuario traz mais de 1)" elif k >= 0.5: status = "Bom (crescimento acelerado)" elif k >= 0.2: status = "Ok (crescimento suportado)" else: status = "Baixo (crescimento lento)" return {"k_factor": round(k, 2), "status": status, "interpretation": f"Cada 100 usuarios trazem {int(k*100)} novos"}

Imported: Sequencia De Onboarding (7 Dias)

Dia 0 -- Boas-vindas (imediato apos cadastro) Assunto: "Bem-vindo a Auri. Aqui esta como comecar." Body: Tutorial em 3 passos, link para primeira conversa, dica de uso

Dia 1 -- Ativacao (se nao fez primeira conversa)
Assunto: "Sua Auri esta esperando voce"
Body: Os 3 tipos de perguntas que mais impressionam, CTA urgente

Dia 3 -- Educacao
Assunto: "O que 100 usuarios da Auri descobriram essa semana"
Body: Case real + insight surpreendente + feature escondida

Dia 7 -- Upsell (se usou pelo menos 3x)
Assunto: "Voce esta usando 80% do limite gratuito"
Body: O que Pro desbloqueia, oferta especial por 48h, prova social

Dia 14 -- Reativacao (se parou de usar)
Assunto: "Saudade, [nome]. O que aconteceu?"
Body: Pergunta genuina, link para retorno facil, nova feature

Imported: Estrategia De Lancamento

1 semana antes: - Pedir a hunters influentes para cacar o produto - Preparar assets: logo, tagline, screenshots, video demo 60s - Warm up: posts no X/LinkedIn sobre o problema que Auri resolve - Recrutar 50 early adopters para upvotar no lancamento

Dia de lancamento (meia-noite PT):
- Post no X: demo impressionante + link PH
- Email para toda waitlist: "Estamos no Product Hunt hoje!"
- Mensagem no Telegram/Discord de comunidades tech BR
- Ficar online o dia todo respondendo comentarios

Posicionamento: Tagline: "The Alexa skill that actually thinks"

Imported: 7. Comandos

Imported: Common Pitfalls

• Using this skill for tasks outside its domain expertise
• Applying recommendations without understanding your specific context
• Not providing enough project context for accurate analysis

Imported: Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.