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>
This commit is contained in:
2026-05-16 16:33:54 +08:00
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name: rag_search_answer
description: 收問題 → 從 KBDB semantic search → 把 top context 餵 claude 回答
flow:
- "input >> ON_SUCCESS >> search_kbdb"
- "search_kbdb >> ON_SUCCESS >> answer_with_context"
config:
search_kbdb:
component: kbdb_search
api_key: "{{api_key}}"
query: "{{input.question}}"
topK: 5
user_id: "{{input.user_id}}" # 可選,限定某用戶 namespace
answer_with_context:
component: claude_api
timeout_ms: 45000
_recipe_output_format: text
prompt: |
你是知識庫助手。根據下列 context 回答問題。
**規則**
1. 只用 context 內的資訊,不外推
2. context 沒講的,老實說「資料庫裡查不到」,不要編
3. 引用時標 [block_id],方便用戶追原始
Context:
{{search_kbdb.results}}
問題:{{input.question}}
回答: