Journey Deploy

Organization

butterbase-ai

journey-deploy

Use as the deploy-verification stage of the Butterbase journey, after journey-frontend (or after any build stage if there is no frontend). Smoke-tests the deployed app — hits the live URL, invokes any deployed functions, checks auth round-trip. Writes results to docs/butterbase/04-build-log.md. Blocks journey-submit if smoke fails.

Overview

Publisher	butterbase-ai
Repository	`butterbase-skills`
Skill name	`journey-deploy`
Stars	535
Forks	42
Bundled files	Instructions only
License	MIT
Links	Skill source Repository

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/butterbase-ai/butterbase-skills/tree/main/skills/journey-deploy
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.

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-deploy .claude/skills/journey-deploy

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Journey Deploy 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 Deploy 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 Deploy 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: Deploy verification

Stage 4 of the guided journey. Verify the deployed app actually works end-to-end.

When to use

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

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/00-state.md — for app_id, deployed_url.
docs/butterbase/02-plan.md — for the function list to smoke.
docs/butterbase/04-build-log.md — to know what shipped.

Procedure

Refresh docs. Call butterbase_docs with topic: "frontend". For end-to-end smoke patterns, also WebFetch https://docs.butterbase.ai/deploy. Skip if cache is fresh.

For each check, log a one-line result to 04-build-log.md. Halt on the first ✗ and ask the user to fix or skip.

Frontend reachable. If deployed_url is set, fetch it via Bash curl -sS -o /dev/null -w "%{http_code}" <url>. Expect 200. Log <ISO> deploy curl 200 ok or ... <code> fail.
Functions respond. For each function in the plan with HTTP trigger, call mcp__butterbase__invoke_function with a representative payload. Expect 2xx. Log per function.
Auth round-trip (if configured). If the plan included OAuth, prompt the user: "Open <deployed_url>, click 'Sign in with <provider>', and confirm you land logged-in. Did it work? (yes/no)". Log the answer.
Function logs clean. Call mcp__butterbase__manage_function action: get_logs for the most recent invocations. Show the user any error-level lines. Ask: "Anything concerning here? (no → continue, yes → fix and re-run)".
If all checks pass, tick - [x] deploy in 00-state.md, set current_stage: submit (if hackathon_mode: true) or current_stage: done (otherwise).
Return to journey orchestrator.

Outputs

Multiple lines in 04-build-log.md.
Updated 00-state.md.

Anti-patterns

❌ Treating a 200 from the frontend root as proof the app works — actually invoke a function.
❌ Skipping the auth round-trip check just because OAuth is configured server-side — judges will try to log in.

Frequently asked questions

What does the Journey Deploy AI skill do?

Why use Journey Deploy on TypingMind?

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

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

Which AI models can use Journey Deploy?

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 Deploy?

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

Is the Journey Deploy 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Journey: Deploy verification

When to use

Preflight

Inputs

Procedure

Outputs

Anti-patterns

Frequently asked questions

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