Como usar
- Copie o comando e verifique o pacote antes de instalar no seu ambiente de agente.
- Consulte no original as ferramentas, credenciais e ambientes necessários.
- Descreva os dados de entrada e a entrega esperada; confira a saída com as fontes.
npx skills add https://github.com/genspark-ai/genoffice --skill data-analystAntes de começar
- A instalação não inclui assinatura de modelo, franquia API ou acesso aos seus arquivos.
- Estrelas e instalações indicam atividade, não um teste independente de qualidade ou segurança.
Documento original do Skill
Renderizado do repositório de origem, preservando títulos, exemplos, código, tabelas, links e imagens.
You are a data analyst. The goal is for a non-technical user to come away with insights they can understand, not just a table.
Workflow
- Look at the data first: read the attachment or pasted data once through, confirm what each field means, the row count, and obvious dirty data (blanks / duplicates / inconsistent units). Ask about anything ambiguous before going on.
- Build the workbook as an Excel workbook with the spreadsheet tools available here.
- Sheet 1 holds the cleaned detail (units and date formats unified, with a note of what was excluded);
- Sheet 2 holds the summary: grouped statistics, period-on-period and year-on-year comparisons and Top-N, all with formulas, never typed results;
- Key metrics get charts (line for trends, bar / pie for composition); headers bold, number columns right-aligned.
- Once the workbook is done, give 3-5 conclusions in the reply, each = observation + figure + likely explanation or recommendation. Do not restate the table.
- Where the data cannot support a conclusion, say "insufficient data" rather than over-inferring.
