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journey-rag

Use as the RAG build stage of the Butterbase journey. Implements the RAG section of 02-plan.md by delegating to rag-dev. Calls manage_rag_content (create_collection, ingest_document). Skipped if the plan has no knowledge-base feature.

AI 与智能体534skills/journey-rag/SKILL.md

安装

把这段话发给 Claude Code、Codex 或 Cursor。智能体会先检查安全性,你确认后才安装。

读取 https://funcoding.ai/skills/butterbase-ai/butterbase-skills/journey-rag/install.md ,按里面的步骤帮我安装这个 Skill。

SKILL.md

Journey: RAG

Stage 3g of the guided journey. Create RAG collections and ingest initial documents.

When to use

  • Dispatched by journey when current_stage: rag.
  • Directly via /butterbase-skills:journey-rag.
  • Skipped (annotated (n/a)) if the plan has no RAG section.

Preflight

If docs/butterbase/03-preflight.md is missing, older than 24 hours, or 00-state.md has app_id: null, invoke butterbase-skills:journey-preflight first. Wait for it to return successfully before proceeding.

Inputs

  • docs/butterbase/02-plan.md — the RAG section.
  • docs/butterbase/00-state.md — for app_id.

Procedure

  1. Refresh docs. Call butterbase_docs with topic: "rag". For ingestion + retrieval patterns, also WebFetch https://docs.butterbase.ai/ai/rag. Skip if cache is fresh.

  2. Read the RAG section. Print it back: "About to set up RAG: collections=<list>. Proceed?". Wait for yes.

  3. Invoke butterbase-skills:rag-dev via the Skill tool with the RAG plan and app_id. The wrapped skill calls manage_rag_content action: create_collection, then ingest_document for any seed sources the user provides.

  4. Smoke: call rag_query with a representative question and show the user the top hit.

  5. Append one line to docs/butterbase/04-build-log.md: <ISO timestamp> rag manage_rag_content ok

  6. Tick - [x] rag in 00-state.md, set current_stage: to the next unchecked stage.

  7. Return to journey orchestrator (or ask "Continue to the next stage? (yes/no)").

Outputs

  • Created RAG collections, ingested seed docs.
  • One line in 04-build-log.md.

Anti-patterns

  • ❌ Ingesting huge document sets in a single call — chunk and poll get_document_status.
  • ❌ Skipping the smoke rag_query — silent embedding failures are common.

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