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Dashboard azure devops

Skill falercia/deep-claude/skills/dashboard-azure-devops

Skill para gerar dashboards executivos a partir de dados do Azure DevOps. Acionar quando usuário pedir "dashboard Azure DevOps", "métricas do sprint", "indicadores de engenharia", "DORA metrics", "velocity do time" ou similar, em contexto de gestão de engenharia.From its SKILL.md

Install
npx -y skills add falercia/deep-claude --skill dashboard-azure-devops

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SKILL.md

2.5 KB, 634 tokens by cl100k_base, as published. Nobody here has run it

Dashboard Azure DevOps

Quando ativar

Acione quando o usuário pedir indicadores executivos de engenharia a partir do Azure DevOps:

  • "Gera um dashboard das sprints recentes"
  • "Indicadores de velocity"
  • "DORA metrics do time"
  • "Lead time, MTTR, deployment frequency"
  • "Visão executiva da engenharia"
  • "Relatório quinzenal para diretoria"

Não ative para:

  • Operações de criação/edição em ADO (use MCP específico)
  • Debug de pipelines (use ferramenta de CI)
  • Gestão de bugs individuais (use UI do ADO)

O que faz

Produz visão executiva consolidada com 4 blocos:

  1. DORA Metrics: Deployment Frequency, Lead Time for Changes, MTTR, Change Failure Rate
  2. Velocity e previsibilidade: story points concluídos, previsibilidade vs planejado, debt acumulada
  3. Quality: bugs em aberto, bugs por severidade, escape rate (bugs em produção)
  4. Síntese executiva: 3-5 frases para CTO/CFO

Configurações

<contexto>
  <organizacao>{{nome_da_org}}</organizacao>
  <projetos>{{lista_de_projetos}}</projetos>
  <periodo>{{semana | quinzena | mes | trimestre}}</periodo>
  <audiencia>{{tech_leads | C_level}}</audiencia>
</contexto>

Dependências

Skill assume acesso ao Azure DevOps via:

  • API REST com PAT (Personal Access Token)
  • Ou MCP oficial do Azure DevOps (quando disponível)

Configure credenciais antes de uso.

Saída esperada

Tabela executiva + comentário curto + sinalização de alertas (red flags).

Exemplo de bloco DORA:

MétricaValorTendênciaStatus
Deployment Frequency4.2/dia↑ vs sprint anteriorElite
Lead Time for Changes1.8 dias→ estávelHigh
MTTR4.5h↓ melhorouElite
Change Failure Rate8%↑ piorouHigh

Síntese: time mantém cadência elite em deployment frequency e MTTR; CFR subiu 3 pontos no último ciclo, sugerindo revisar testes de regressão antes de release.

Modelo recomendado

  • Claude Sonnet (suficiente para análise estruturada)
  • Temperature 0.0 (consistência em métricas)

Conexões

  • Cap 9 — Claude Code (uso em pipeline)
  • Cap 35 — LLMOps (observabilidade)
  • Cap 22 — Tool Use (chamadas a APIs externas)

What ships with it: 1 file

1.4 KB alongside SKILL.md

Gives 0 of the 12 instructions most containers cloud skills give in 634 tokens

Counted across 607 of the 657 authors here whose files we hold, read 2026-08-07

  • Run containers as a non-root userin 66 of 607, across 46 files
  • Use multi-stage buildsin 53 of 607, across 44 files
  • Use Promise.all for independent operationsin 47 of 607, across 13 files
  • Import directly instead of barrel filesin 46 of 607, across 12 files
  • Use ternary instead of AND for conditionalsin 45 of 607, across 12 files
  • Use Set or Map for O(1) lookupsin 42 of 607, across 10 files
  • Create a .dockerignore filein 41 of 607, across 31 files
  • Read individual rule files for detailsin 39 of 607, across 9 files
  • Copy dependency files before source codein 36 of 607, across 23 files
  • Authenticate server actions like API routesin 35 of 607, across 7 files
  • Use next/dynamic for heavy componentsin 34 of 607, across 9 files
  • Use React.cache for per-request deduplicationin 34 of 607, across 10 files

Said here and by no other author read

  • produce consolidated executive view with four blocks
  • calculate dora metrics
  • calculate velocity and predictability metrics
  • calculate quality metrics including open bugs and escape rate
  • write executive synthesis of 3 to 5 sentences
  • output executive table with short comments and red flags

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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