Journey Agents

Organization

butterbase-ai

journey-agents

Use as the agents build stage of the Butterbase journey. Implements the Agents section of 02-plan.md by delegating to the `agents` skill for each agent. Registers any required MCP servers, validates each graph_spec, creates the agent, and smokes it via invoke_agent. Skipped if the plan has no agents.

Overview

Publisher	butterbase-ai
Repository	`butterbase-skills`
Skill name	`journey-agents`
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 Agents 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-agents
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-agents .claude/skills/journey-agents

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

Use it in TypingMind

Enable Journey Agents 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 Agents 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 Agents 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: Agents

Build the agents described in 02-plan.md. Order: MCP servers first (probe must pass before any agent references them) → agents → smoke runs.

When to use

Dispatched by journey when current_stage: agents.
Directly via /butterbase-skills:journey-agents.
Skipped (annotated (n/a)) if the plan lists no agents.

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 Agents section (names, purpose, tool list, visibility, MCP servers needed).
docs/butterbase/00-state.md — for app_id.
Any handcrafted spec files under agents/ in the project (preferred — version-controlled and survives clones).

Procedure

Refresh docs. Call butterbase_docs with topic: "agents". If the cache (docs/butterbase/03b-docs-cache.md) already covers agents, skip.
Register MCP servers first. For each MCP server in the plan:
- Print: "Registering MCP server '<label>' at <url> (transport=<sse|http|streamable_http>). Proceed?". Wait for yes.
- Call the MCP-servers registration route (or the dashboard's MCP Servers page if a wrapping MCP tool is not yet available — check butterbase_docs topic agents for the current preferred path).
- Wait for probe result. If status: unhealthy, surface the error and ask the user to fix (URL, auth header, transport mismatch) before continuing. Do not create agents that reference an unhealthy server.
Build each agent. For each agent in the plan, in order: a. Print: "About to build agent: <name> (visibility=<v>, tools=<n builtin / m mcp / k function>). Proceed?". Wait for yes. b. Invoke butterbase-skills:agents via the Skill tool with: agent name, intended behaviour, plan-derived tool list, model preference, visibility/limits. The wrapped skill drafts the graph_spec, writes it to agents/<name>.json in the project repo, and calls validate_agent_spec. c. If validation fails, surface the Zod issues and loop the agents skill to fix. d. Safety gate. If visibility != 'private' AND any node can reach a write tool (insert_row, update_row, delete_row, write_storage, or any read_write-mode MCP/function tool), explicitly ask: "This agent is reachable by <visibility> callers and can write data. Set safety_acknowledged=true? (yes / change to private / reduce tools)". Do not proceed silently. e. create_agent with the validated spec. f. Smoke: invoke_agent with a representative input. Poll get_agent_run until terminal. If the run errors, debug per the agents skill's debugging procedure; otherwise show the user the final output. g. Append one line per agent to docs/butterbase/04-build-log.md: <ISO timestamp> agents create_agent <agent-name> ok (run smoke=<run_id>)
Persist specs to the repo. Confirm agents/<name>.json files are tracked locally. They will be carried by butterbase repo push (run by the templates stage if the user is publishing, or any time the user pushes a snapshot). This is the only way a clone recipient can recreate the agents — the agents table is not part of clone replay.
Tick state. Mark - [x] agents in 00-state.md, set current_stage to the next unchecked stage.
Return to journey orchestrator (or ask "Continue to the next stage? (yes/no)").

Outputs

One or more agents created against the live app.
One or more agents/<name>.json spec files in the project repo.
One line per agent in docs/butterbase/04-build-log.md.

Anti-patterns

❌ Skipping validate_agent_spec. Bad specs surface as opaque runtime errors after the agent is live.
❌ Creating a public write-capable agent without rate limits or a daily_budget_usd. The runtime requires safety_acknowledged, but you should also pick hourly per-IP and per-app caps.
❌ Hard-coding secrets in system_prompt or args_template. Read them from ctx.env inside a function tool.
❌ Forgetting that the agents table is not replayed on clone. Always commit the spec JSON and document re-import (butterbase agents create -f agents/<name>.json) in the README.
❌ Smoking with visibility: 'private' and calling it good for a public agent. After the smoke, change visibility and re-test with an unauthenticated curl to confirm the public path works.

Frequently asked questions

What does the Journey Agents AI skill do?

Why use Journey Agents on TypingMind?

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

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

Which AI models can use Journey Agents?

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 Agents?

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

Is the Journey Agents 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: Agents

When to use

Preflight

Inputs

Procedure

Outputs

Anti-patterns

Frequently asked questions

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