使用方法
- 复制安装命令,在自己的智能体环境安装前先检查源码包。
- 从原始文档核对所需工具、凭据和支持的宿主。
- 说明输入材料与期望交付物,并对照来源检查输出。
npx skills add https://github.com/tikalk/adlc-team-skills --skill team-init开始前需了解
- 安装不包含模型订阅、API 额度或访问文件的权限。
- 仓库星数和安装量反映活跃情况,不等于独立质量或安全测试。
按源仓库内容呈现,保留标题、案例、代码、表格、链接以及原文引用的演示图片。
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-levelupto extract from session - Mining git history: Use
/change-initfor 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/→ Authenticationservices/payment/→ Payment- etc.
Phase 2: Load Team Directives
Read existing team-ai-directives main branch for comparison (avoid duplicates).
Phase 3: Multi-Agent Analysis
- Discovery Agent: Scan each sub-system for raw patterns
- Pattern Agent: Classify and score patterns for reusability
- 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
adlcbranchdrafts/cdr/ - [ ] No CDRs in
.adlc/drafts/(old location) - [ ]
cdr.mdindex regenerated inadlcbranch



