Journey Rag logo

Journey Rag

Organization
butterbase-ai
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.

Overview

Publisherbutterbase-ai
Repositorybutterbase-skills
Skill namejourney-rag
Stars
535
Forks
42
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by butterbase-ai on GitHub. Read the source before you install it.

Installation

Install the Journey Rag AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/butterbase-ai/butterbase-skills/tree/main/skills/journey-rag
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/butterbase-ai/butterbase-skills.git /tmp/butterbase-skills
mkdir -p .claude/skills
cp -r /tmp/butterbase-skills/skills/journey-rag .claude/skills/journey-rag
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Journey Rag in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Journey Rag on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Journey Rag is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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.

Frequently asked questions

What does the Journey Rag AI skill do?

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.

Why use Journey Rag on TypingMind?

Because you install it once and use it with any model. Journey Rag is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Journey Rag in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/butterbase-ai/butterbase-skills/tree/main/skills/journey-rag. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Journey Rag?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Journey Rag?

As many as you like. As long as a model supports skills, you can use Journey Rag with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Journey Rag AI skill free?

Yes. It is published on GitHub by butterbase-ai under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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