docs(registry): seed 10 examples + 5 skills (LI SDD M3.1 + M3.3)

對應 .agents/specs/llm-interface/ Milestone 3.1 + 3.3。

registry/examples/ — 10 個可直接 push 的 workflow 範本：
  starter:    webhook-to-http
  common:     cron-watcher, llm-classify, rag-search-answer, daily-digest
  external:   email-summary (gmail+claude+telegram), pdf-to-blocks,
              github-issue-bot
  advanced:   parallel-fanout (trigger_workflow fan-out),
              error-retry (try_catch+wait pattern)

  每個含：workflow.yaml（可直接 push）+ description.md（解決什麼問題 /
  改成你自己的 / 學到什麼）+ tags.json（搜尋用）

registry/skills/ — 5 個 AI playbook（markdown）：
  build_watcher_workflow            — cron + filter + trigger 模式
  debug_paused_workflow             — claude_api callback paused 怎麼追
  migrate_http_to_trigger_workflow  — 從 self-fetch 換 trigger_workflow
  rag_with_arcrun                   — KBDB + claude_api 組裝 RAG
  add_new_wasm_component            — TinyGo 寫 + 部署全流程

兩者差異：
  examples = 可直接拿來改的 YAML
  skills = 面對 X 問題該怎麼想 + 該用哪個 example

兩者後續：CI 自動同步進 KBDB（type=workflow-example / type=agent-skill），
MCP arcrun_search_examples / arcrun_list_skills 走 KBDB semantic search。
（CI sync 是 M3.4 工作）

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

registry/examples/parallel-fanout/workflow.yaml

@@ -0,0 +1,35 @@
+name: parallel_fanout
+description: 一份輸入分發多個子 workflow 並行處理（trigger_workflow 模式）
+
+flow:
+  - "input >> ON_SUCCESS >> dispatch_to_summary"
+  - "input >> ON_SUCCESS >> dispatch_to_translate"
+  - "input >> ON_SUCCESS >> dispatch_to_classify"
+
+config:
+  # 三個並行子 workflow 觸發。各自獨立執行、互不影響、不等彼此
+  # cypher-executor 處理 fan-out：三條邊同源 (input) → 三個目標各自跑
+  dispatch_to_summary:
+    component: trigger_workflow
+    workflow_name: "llm_classify_example"   # 改成你的 summary workflow
+    api_key: "{{api_key}}"
+    input:
+      api_key: "{{api_key}}"
+      text: "{{input.text}}"
+
+  dispatch_to_translate:
+    component: trigger_workflow
+    workflow_name: "your_translate_workflow"
+    api_key: "{{api_key}}"
+    input:
+      api_key: "{{api_key}}"
+      text: "{{input.text}}"
+      target_lang: "{{input.target_lang}}"
+
+  dispatch_to_classify:
+    component: trigger_workflow
+    workflow_name: "llm_classify_example"
+    api_key: "{{api_key}}"
+    input:
+      api_key: "{{api_key}}"
+      text: "{{input.text}}"