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Iii Engine Config

OrganizationPopular
iii-hq
iii-engine-config

Configure a managed iii engine through worker-compose.yaml or a directly supervised engine through config.yaml. Use for engine ports, RBAC via the rbac-proxy worker, streams, sandboxes, and configuration storage.

Overview

Publisheriii-hq
Repositoryiii
Skill nameiii-engine-config
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Forks
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Bundled files
Instructions only
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 iii-hq on GitHub. Read the source before you install it.

Installation

Install the Iii Engine Config 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/iii-hq/iii/tree/main/skills/iii-engine-config
  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/iii-hq/iii.git /tmp/iii
mkdir -p .claude/skills
cp -r /tmp/iii/skills/iii-engine-config .claude/skills/iii-engine-config
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Iii Engine Config 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 Iii Engine Config 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 Iii Engine Config 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.

Engine Config

iii has two engine configuration modes. Do not mix them.

Managed Compose engine

The presence of engine: means that Compose owns the engine process. Engine worker values are direct mappings; there is no nested config: field.

yaml
namespace: orders
engine:
  url: ws://127.0.0.1:49134
  registration_namespace_grace_ms: 5000
  workers:
    configuration:
      adapter:
        name: fs
        config:
          directory: ./config
    iii-worker-manager:
      host: 127.0.0.1
      port: 49134
    iii-http-functions: {}
    iii-stream:
      host: 127.0.0.1
      port: 3112
    iii-sandbox:
      auto_install: true
containers: {}

Start it with:

bash
iii compose --namespace orders-daemon --up --file worker-compose.yaml

engine.url defaults to ws://127.0.0.1:49134 and uses Compose's ${VAR:-default} expansion. engine.workers stays opaque until the engine reads the generated YAML, so its values use ${VAR:default} and retain numeric types. Compose materializes an owner-only config under <project-dir>/.iii/compose/<daemon-namespace>/ and removes it after clean shutdown. With III_COMPOSE_STATE_DIR, it uses <state-root>/<project-slug>/<daemon-namespace>/. Changing engine: requires restarting Compose. Do not combine a managed file with explicit --engine.

Allowed engine worker base names are:

  • configuration
  • iii-worker-manager
  • iii-http-functions
  • iii-stream
  • iii-sandbox

Use #instance for another instance of an allowed worker. iii-engine-functions, iii-telemetry, and iii-observability are injected automatically and must not be declared.

HTTP, cron, queue, state, pubsub, bridge, application, and custom workers belong under containers:. Add registry packages with:

bash
iii trigger -n orders-daemon compose::add worker=state

RBAC with rbac-proxy

Keep the engine port internal and put the rbac-proxy worker in front of it when untrusted workers, browsers, or agents need to connect:

bash
iii trigger -n orders-daemon compose::add worker=rbac-proxy

rbac-proxy opens its own WebSocket port, speaks the worker protocol verbatim, and at the boundary authenticates each connection (rbac.auth_function_id), gates every invocation and trigger binding (rbac.expose_functions, plus allowed_functions / forbidden_functions from the auth result), namespaces a session's registrations (function_registration_prefix), runs middleware_function_id and the registration hooks, and filters engine::* discovery results to what the caller may invoke. Its settings live in the configuration worker under id rbac-proxy:

yaml
host: 0.0.0.0
port: 49200                        # the public RBAC port
engine_url: ws://127.0.0.1:49134   # the trusted internal engine listener
rbac:
  auth_function_id: my-project::auth-function
  expose_functions:
    - match("api::*")

RBAC is mandatory on untrusted networks: only the proxy's port may face one, never the engine port, and a public proxy must always set auth_function_id. Full schema: https://workers.iii.dev/workers/rbac-proxy.

Directly supervised engine

Keep list-shaped config.yaml only when systemd, Kubernetes, or another supervisor owns the engine:

yaml
workers:
  - name: configuration
    config:
      adapter:
        name: fs
        config:
          directory: ./config
  - name: iii-worker-manager
    config:
      host: 127.0.0.1
      port: 49134

Start the engine and external Compose daemon separately:

bash
iii --config config.yaml
iii compose --namespace orders-daemon --engine ws://127.0.0.1:49134 --up --file worker-compose.yaml

The external Compose file must omit engine:. III_URL may replace --engine. Direct config expansion uses ${VAR:default} and accepts only the same five engine-owned worker types. Any project worker stops startup/reload with UNSUPPORTED_CONFIG_WORKERS.

Security and operations

  • Bind the engine port to 127.0.0.1; expose only the rbac-proxy port.
  • Set rbac.auth_function_id on every public proxy and keep expose_functions narrow.
  • Keep secrets in environment-backed configuration; do not commit literal credentials.
  • Preserve configuration, stream, state, and queue storage paths during migrations.
  • Use compose::status for process ownership and engine::workers::list for live connections.
  • compose::add never edits engine: or restarts the engine.

When to Use

  • Use this skill for managed engine: maps, direct config.yaml, engine-owned workers, ports, adapters, RBAC via rbac-proxy, or engine lifecycle selection.
  • Use it when migrating engine worker blocks into Compose.

Boundaries

  • Project worker lifecycle belongs to Compose, not config.yaml or iii worker.
  • For function and trigger code, use iii-core-primitives.
  • For worker-specific HTTP, queue, cron, state, or pubsub behavior, use that worker's docs.

Frequently asked questions

What does the Iii Engine Config AI skill do?

Configure a managed iii engine through worker-compose.yaml or a directly supervised engine through config.yaml. Use for engine ports, RBAC via the rbac-proxy worker, streams, sandboxes, and configuration storage.

Why use Iii Engine Config on TypingMind?

Because you install it once and use it with any model. Iii Engine Config 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 Iii Engine Config in TypingMind?

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

Which AI models can use Iii Engine Config?

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 Iii Engine Config?

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

Is the Iii Engine Config AI skill free?

It is published on GitHub by iii-hq. Check the repository for licensing terms. 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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