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.

Quelltext ansehen

Verwendung

  1. Installationsbefehl kopieren und das Quellpaket vor der Installation in der eigenen Agentenumgebung prüfen.
  2. Benötigte Werkzeuge, Zugangsdaten und Hosts im Original prüfen.
  3. Eingabe und gewünschtes Ergebnis beschreiben und die Ausgabe mit den Quellen abgleichen.
npx skills add https://github.com/tikalk/adlc-team-skills --skill team-init

Vor dem Start

  • Die Installation umfasst weder Modellabo noch API-Kontingent oder Dateizugriffsrechte.
  • Sterne und Installationen zeigen Aktivität, keine unabhängige Qualitäts- oder Sicherheitsprüfung.
Originales Skill-Dokument

Aus dem Quell-Repository gerendert; Überschriften, Beispiele, Code, Tabellen, Links und Bilder bleiben erhalten.

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

Verwandte Aufgaben

aus demselben Repository

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