Factory logo

Factory

OrganizationPopular
BuilderIO
factory

Experimental workflow for configuring an autonomous software delivery factory. Use when choosing feedback sources, schedules, worktree behavior, autonomy gates, or host automations.

Overview

PublisherBuilderIO
Repositoryskills
Skill namefactory
Stars
4.6K
Forks
231
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 BuilderIO on GitHub. Read the source before you install it.

Installation

Install the Factory 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/BuilderIO/skills/tree/main/skills/factory
  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/BuilderIO/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/factory .claude/skills/factory
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Factory 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 Factory 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 Factory 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.

Factory

Start with the Factory guide for workflow setup and configuration.

Read .agent-factory/config.yaml and apply the optional skill_prompts.factory entry as additional project guidance. Configure the current project to turn selected product or maintenance signals into verified, reviewed changes. Factory coordinates the other modules; it does not assume a provider, repository, schedule, or autonomy level.

Set up

Use the Factory configuration reference for field meanings, examples, and host limitations.

  1. Read .agent-factory/config.yaml if it exists. Preserve explicit choices.
  2. Show the read-capable integrations this host exposes. There is no built-in Factory source catalog. Confirm the source scope; add a custom source only when a connected tool can read it.
  3. Set each action policy independently: implement, reply, close, review, approve, publish, merge, deploy, recover, and notify.
  4. Add optional per-skill prompts under skill_prompts when you want project-specific rules layered onto a module.
  5. Choose schedules, time zone, worktree ownership, runtime, and notifications only where the host supports them.
  6. Write the agreed config. Never put credentials or tokens in it.
  7. If asked to create automations, create one job per enabled workflow, then read back its saved schedule, target, runtime, and notification settings. Report fields the host could not honor.

A config entry or written prompt does not prove a job exists. Treat unavailable or partial reads as unknown, not empty or successful.

Safe defaults

  • Keep replies, issue closure, approvals, merges, production deploys, and recovery disabled unless their own policy is explicit.
  • For criteria-based actions, record both conditions that allow the action and conditions that require a human.
  • Missing or unclear policy means hold. Permission to fix does not authorize publication or another external action.

Modules

SkillScope
factory-collectCollect and triage configured feedback, telemetry, errors, and issues.
factory-lookbackFind recurring signals and brittle paths that need systemic fixes.
factory-human-digestAggregate work that still needs a human decision.
factory-review-prsReview a filtered PR queue.
factory-babysit-prFollow one explicitly authorized PR.
factory-shipPublish and complete a delivery lifecycle.
factory-watchdogFind stopped, authorized delivery work.
factory-recoverResume valid interrupted runs.

Modules can run independently. Each reads the same project config and must not borrow permissions from another workflow.

Prompt overlays

skill_prompts is an open map from a skill name to a multiline prompt. Each Factory module reads its matching entry, such as skill_prompts.factory-babysit-pr, and treats it as additional project guidance. Editing or removing that value replaces or removes the project overlay; it never replaces the installed skill instructions.

For scheduled runs, include the matching overlay in the saved automation prompt and verify the host retained it. A prompt cannot grant a permission, weaken repository or host safeguards, or override the user's current request. If it conflicts with those rules, follow the more restrictive requirement and surface the conflict.

Report

State which sources and host capabilities were verified, which policies and jobs were configured, what remains manual, and any unavailable evidence. Never claim that a schedule, integration, merge, or deployment exists without reading back its live state.

Frequently asked questions

What does the Factory AI skill do?

Experimental workflow for configuring an autonomous software delivery factory. Use when choosing feedback sources, schedules, worktree behavior, autonomy gates, or host automations.

Why use Factory on TypingMind?

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

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

Which AI models can use Factory?

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 Factory?

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

Is the Factory AI skill free?

Yes. It is published on GitHub by BuilderIO 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇