tikalk/adlc-team-skills

team-init

Use when bootstrapping team knowledge from a brownfield codebase — reverse-engineers CDRs for contribution to team-ai-directives adlc branch.

Ver código fuente

Cómo usar

  1. Copia el comando y revisa el paquete antes de instalarlo en tu entorno de agente.
  2. Consulta las herramientas, credenciales y entornos necesarios en el documento original.
  3. Describe las entradas y el resultado deseado; contrasta la salida con las fuentes.
npx skills add https://github.com/tikalk/adlc-team-skills --skill team-init

Antes de empezar

  • La instalación no incluye suscripción al modelo, cuota API ni permisos sobre tus archivos.
  • Las estrellas e instalaciones reflejan actividad, no una prueba independiente de calidad o seguridad.
Documento original del Skill

Contenido del repositorio de origen con títulos, ejemplos, código, tablas, enlaces e imágenes preservados.

team-init

What this skill does

Reverse-engineer Context Directive Records (CDRs) from an existing codebase (brownfield) to document reusable patterns for contribution to team-ai-directives.

Replaces the former team-init skill. Drafts are written to the adlc orphan branch of team-ai-directives (not project-local .adlc/drafts/).

When to use

  • Brownfield projects: Existing code without team-wide directives
  • Legacy modernization: Extract reusable patterns before refactoring
  • Team onboarding: Turn implicit conventions into explicit directives

When NOT to use

  • Greenfield (session complete): Use /team-levelup to extract from session
  • Mining git history: Use /change-init for past decisions

Process

Phase 0: Environment Setup

Run: scripts/team-init.sh --setup

Resolves REPO_ROOT, TEAM_AI_DIRECTIVES, NEXT_CDR, ADLC_BRANCH.

Phase 1: Sub-System Detection

Analyze codebase for distinct sub-systems (same detection as former team-init):

  • src/auth/ → Authentication
  • services/payment/ → Payment
  • etc.

Phase 2: Load Team Directives

Read existing team-ai-directives main branch for comparison (avoid duplicates).

Phase 3: Multi-Agent Analysis

  1. Discovery Agent: Scan each sub-system for raw patterns
  2. Pattern Agent: Classify and score patterns for reusability
  3. Synthesis Agent: Cross-sub-system analysis and CDR generation

Phase 4: Write CDRs

Write to adlc branch drafts/cdr/ using the shared CDR draft template at skills/team/templates/cdr-draft-template.md.

Phase 5: Handoff

Suggest running /team-levelup to review and publish the discovered CDRs.

Verification

  • [ ] CDRs written to adlc branch drafts/cdr/
  • [ ] No CDRs in .adlc/drafts/ (old location)
  • [ ] cdr.md index regenerated in adlc branch

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