Journey Idea logo

Journey Idea

Organization
butterbase-ai
journey-idea

Use as stage 1 of the Butterbase journey, when the user has only a rough idea ("I want to build something that..."). Conducts a concrete, one-question-at-a-time brainstorm that surfaces who the user is, what they do first, what the must-haves are, and inline-tags Butterbase capabilities (→ manage_schema, → deploy_function, etc.). Produces docs/butterbase/01-idea.md.

Overview

Publisherbutterbase-ai
Repositorybutterbase-skills
Skill namejourney-idea
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 Idea 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-idea
  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-idea .claude/skills/journey-idea
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Journey Idea 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 Idea 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 Idea 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: Idea brainstorm

Stage 1 of the guided journey. Turn a vague idea into a written brief with capability tags.

When to use

  • Dispatched by journey when current_stage: idea.
  • Directly via /butterbase-skills:idea.

Inputs

None required. Optionally reads any existing 01-idea.md to resume.

Procedure — questioning discipline

Follow the cross-cutting rules from the spec:

  • One question at a time. Never batch.
  • Multiple-choice preferred, with 2–4 concrete options.
  • Concrete, not abstract.
  • Recommend when a Butterbase primitive is obvious.
  • Tag inline. When a feature surfaces, append the capability tag immediately (→ manage_schema, → deploy_function, → manage_storage, → manage_oauth, → manage_rag_content, → manage_realtime, → manage_durable_objects, → manage_ai, → create_agent).
  • Write as you go. After each answered question, append the decision to 01-idea.md so progress survives a crash.

Walk through these questions in order. Do not skip — but adapt the wording.

  1. "In one sentence, what is the painful thing your user does today that this replaces?"
  2. "Who is the first user? ① solo creator ② small team ③ end customers of a business ④ Other"
  3. "What is the first action they take in the app?"
  4. "If we could ship only ONE screen, which one?"
  5. "Do two different users see different data when they log in? (yes → user-scoped data → manage_rls; no → shared → simpler)"
  6. "Are there files/images involved? (yes → manage_storage; no → skip)"
  7. "Does anything happen on a schedule or in response to an external event? (yes → deploy_function cron/webhook; no → skip)"
  8. "Is there a knowledge base / search-over-documents feature? (yes → manage_rag_content; no → skip)"
  9. "Does the UI need live updates or presence? (yes → manage_realtime; no → skip)"
  10. "Any chat rooms / multiplayer / per-user-actor state? (yes → manage_durable_objects; no → skip)"
  11. "Any LLM features (chat, embeddings, summarisation)? (yes → manage_ai; no → skip)"
  12. "Any multi-step LLM+tool workflows the user triggers (e.g. 'summarise my orders', 'auto-tag a doc', 'research and reply')? (yes → create_agent; no → skip)". If yes, also ask: "Will the agent need external MCP servers (e.g. GitHub, Slack, custom MCP)?" and "Visibility: ① only the developer ② any logged-in user ③ unauthenticated public — note: public + write tools requires explicit safety acknowledgement."
  13. "Are you planning to publish this app as a public template others can clone? (yes / unlisted-public / no)". Set publish_as_template: <yes|unlisted|no> in 00-state.md front-matter. Public templates require a README with clone instructions and butterbase repo push to sync the source tree — flag this so plan and the publish stage know to plan for it.

If hackathon_mode: true in 00-state.md: after question 4, also ask:

  • "Hackathon deadline (ISO date/time)?" — write to 00-state.md front-matter.
  • After each subsequent feature ask "Can this ship in time, or move to a 'post-hackathon' section?"

01-idea.md format

markdown
# Idea

**One-liner:** <user's answer to Q1>

**First user:** <Q2>
**First action:** <Q3>
**One screen:** <Q4>

## Must-haves
- <feature> → <capability tag>
- ...

## Post-hackathon (nice-to-have)
- ...

## Capability map
| Capability | Used? | Why |
|---|---|---|
| manage_schema | yes | core data model |
| manage_rls | yes | user-scoped data |
| manage_oauth | yes | Google sign-in |
| manage_storage | no | no files |
| deploy_function | yes | daily-digest cron |
| manage_ai | no | |
| manage_rag_content | no | |
| manage_realtime | no | |
| manage_durable_objects | no | |
| create_agent | no | |
| publish_as_template | no | set true if user plans to share this app publicly |

Toolchain note

At the end of the idea write-up, also note in one line that the build will use:

  • @butterbase/sdk for any frontend / Node app code
  • @butterbase/cli for the local dev loop (scaffolding, logs, key generation)
  • The MCP tools (this plugin) for orchestrating provisioning, deployments, integrations

This sets expectations before plan makes specific package choices.

Outputs

  • Writes docs/butterbase/01-idea.md.
  • Ticks - [x] idea and bumps current_stage: plan, last_updated in 00-state.md.

Anti-patterns

  • ❌ "Tell me more about your app." Use the concrete questions above.
  • ❌ Asking 3 questions at once.
  • ❌ Accepting "all of the above" in hackathon mode — force prioritisation.
  • ❌ Moving on before writing 01-idea.md to disk.

Frequently asked questions

What does the Journey Idea AI skill do?

Use as stage 1 of the Butterbase journey, when the user has only a rough idea ("I want to build something that..."). Conducts a concrete, one-question-at-a-time brainstorm that surfaces who the user is, what they do first, what the must-haves are, and inline-tags Butterbase capabilities (→ manage_schema, → deploy_function, etc.). Produces docs/butterbase/01-idea.md.

Why use Journey Idea on TypingMind?

Because you install it once and use it with any model. Journey Idea 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 Idea in TypingMind?

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

Which AI models can use Journey Idea?

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 Idea?

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

Is the Journey Idea 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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