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Configuration

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iii-hq
configuration

Schema-validated, reactive registry for named configuration entries — the runtime configuration surface used by engine and Compose workers.

Overview

Publisheriii-hq
Repositoryiii
Skill nameconfiguration
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Bundled files
Instructions only
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  • 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 Configuration 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/engine/src/workers/configuration/skills
  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/engine/src/workers/configuration/skills .claude/skills/configuration
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Configuration 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 Configuration 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 Configuration 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.

configuration

The configuration worker is a server-side registry of named entries. Every entry has an id (e.g. iii-stream, billing-service), a human-readable name and description, a JSON Schema describing the value shape, and a JSON value validated against that schema. Workers call configuration::register once at startup to declare their schema and configuration::set to publish values; consumers call configuration::get / configuration::list to read and bind a configuration trigger to react to changes without polling.

The default fs adapter persists one YAML file per id under ./config and watches the directory for external edits, so manual edits surface as configuration:updated events. The bridge adapter delegates to a remote engine. The worker is engine-owned and may be configured at engine.workers.configuration.

A per-id TTL (off by default) cleans up entries whose last subscriber trigger has unregistered, scoped to the lifecycle of ephemeral workers that come and go without an explicit teardown step.

When to Use

  • A worker needs a typed, observable configuration surface other workers can read and validate against.
  • Two workers need to agree on the same configuration values without one polling the other or hardcoding a path on disk.
  • An operator should be able to edit a single YAML file (or the remote control plane) and have the change propagate to every subscriber without a worker restart.
  • A worker comes and goes (sandboxes, ephemeral consumers) and its configuration should be cleaned up automatically when no one is left subscribing.

Boundaries

  • Not a general-purpose key/value store — every entry must have a registered JSON Schema. Use the standalone state worker for free-form values.
  • No partial-update surface; set always replaces the whole value. Build the new value client-side and ship it in one call.
  • The bridge adapter cannot delete entries on the remote engine; cleanup over the bridge happens via TTL or directly on the source engine.
  • Over the bridge adapter, configuration::ensure is decided by the remote engine (the original candidate is forwarded there), so it requires a remote engine that exposes configuration::ensure; against an older remote it fails closed with ADAPTER_ERROR rather than falling back to an unsafe register.
  • Schemas are not version-checked across re-registrations — re-registering with an incompatible schema simply replaces it. Coordinate schema migrations out-of-band.

Migration and runtime overrides

Compose defaults to <namespace>-<container-key> without a hash (for example, default-harness). Invalid or over-64-character generated names require explicit config_name. Compose migrates only the exact previous namespace/key hash before starting a stopped worker. After hashed migration, only the default namespace adopts the exact bare container key, unless another container explicitly owns it. The bare source wins over an existing destination; configuration::migrate is the single operation, delegated through bridges to the authority. It returns { action, entry } with migrated, preserved (existing destination with absent source, or matching IDs with an existing entry), or missing (both source and destination absent). Before migration, Compose and every bridge hop query the read-only configuration::migration-capabilities and require source_priority_archive_revision: 1. Unknown or unavailable capabilities fail closed before invoking migration; upgrade the authority. It replaces the destination with the raw source entry, then archives the original source as <source>.yaml.bak. The previous destination is not backed up. .yaml.bak, .bak.yaml, and .bkup.yaml files are ignored during loading, watching and legacy directory migration. An existing identical backup permits cleanup recovery; a conflicting backup is never overwritten. Missing source is a no-write no-op. Unsupported adapters fail closed. Stop source consumers before migrating; do not share an fs directory between engine processes.

config_override is delivered through the existing service API. Compose reads the current configuration with configuration::get (raw: true), merges defaults and overrides, then calls configuration::set with flush: false before starting the worker. No snapshot file is delivered. III_CONFIG_NAME identifies the entry. Memory-only updates never write persistent config/<id>.yaml, and no delayed flush is scheduled. ensure and metadata registration preserve the active value without persisting it or notifying base defaults. An explicit set with default flush: true persists the complete submitted object, including override values if submitted. Both forms of set notify consumers; applying changes is the worker's responsibility. A new worker start merges the current GET value. Removing an override keeps the current value, not the old disk value. Stopping a worker does not clear active memory; restarting the configuration service loses unsaved values and reloads its adapter. Distinct concurrent overrides sharing one configuration id are not supported.

Functions

  • configuration::register — declare an id with name, description, JSON Schema, and an optional initial_value; idempotent re-registration replaces the schema and metadata.
  • configuration::ensure — atomically seed a default: create or refresh the id but write initial_value only when no non-null value is stored yet; an existing value (including false/0/"") is preserved verbatim and the seed is ignored. The race-free replacement for read-then-register when seeding from one or many workers. Fires configuration:registered on creation or configuration:updated on refresh, except while an execution injection is active: boot metadata must not deliver the base in place of the active value.
  • configuration::migrate — move an exact source id with source priority, preserving raw persisted values and metadata and archiving the source. On a successful move, source active memory follows the new id without being saved and replaces any destination override; the old id is no longer readable. With no persisted source, destination memory is preserved and orphan source memory is retired. Same-id migration preserves memory; failures retain it for retry. The response contains the persisted entry, while source :deleted and destination :registered events carry the active snapshot captured at commit. No-ops emit nothing.
  • configuration::set — replace the complete active value and emit configuration:updated. flush defaults to true, validating and persisting through the adapter for an already-registered id. flush: false changes memory only and may precede registration; validation uses the schema when available and normal GET validates again after registration. Explicit null is a value, not a request to clear memory.
  • configuration::get — read the current active entry by id; expands ${VAR:default} against live env unless raw: true.
  • configuration::list — enumerate every registered id with name, description, and schema; never returns the value.
  • configuration::schema — read schema/name/description for one id without exposing the value.

register, ensure, migrate, and set are the mutators; the read-side functions are cache-backed and cheap. Every mutator (plus delete) is linearized per store (the local fs store, one engine process), so a seed can never clobber a concurrent set and two racing seeds resolve to a single winner. Over the bridge adapter the authoritative store is the remote engine and its own linearization applies (the local cache is a best-effort mirror), so ensure is decided remotely, never against the local cache. Reads expand ${VAR:default} placeholders against the live process env on every call, so env changes propagate without restarts — pass raw: true to configuration::get when you need the stored template form.

Reactive triggers

Bind a configuration trigger when a function should run automatically on every register / set / delete — including external fs file edits and bridge-forwarded events from a remote engine. The engine invokes matching handlers asynchronously after each successful mutation and after TTL-driven cleanup, so a worker stays in sync with its configuration without polling.

Reach for it when:

  • A worker needs to reload in-memory state when its configuration is rewritten by another component or by an operator editing the YAML directly.
  • The same handler should run regardless of who edited the configuration (local SDK call, remote engine via the bridge adapter, or a file edit).

If you only need the new value inside the same function that wrote it, configuration::set already returns old_value / new_value — register a trigger only when a different worker should react.

How to bind

  1. Register a handler: iii.registerFunction('stream::on-config-change', handler).
  2. Register the trigger:
typescript
iii.registerTrigger({
  type: 'configuration',
  function_id: 'stream::on-config-change',
  config: {
    configuration_id: 'iii-stream',          // optional. Omit to receive every id.
    event_types: ['configuration:updated'],  // optional. Subset of configuration:registered|configuration:updated|configuration:deleted.
    // condition_function_id is also supported — see get function info.
  },
})

Mutations that fire triggers: configuration::register (:registered on first call, :updated on re-registration), configuration::ensure (:registered on creation, :updated on refresh), configuration::set (:updated), TTL cleanup (:deleted), and external fs create/edit/delete events. Reads do not fire triggers.

The worker also respects per-id TTL: when ttl_seconds > 0 is configured and the last trigger bound to a configuration_id is unregistered, the entry is deleted after the TTL elapses. A new trigger registration before the countdown fires aborts the cleanup.

For the event payload shape, call iii get function info on the trigger type or handler function id.

Frequently asked questions

What does the Configuration AI skill do?

Schema-validated, reactive registry for named configuration entries — the runtime configuration surface used by engine and Compose workers.

Why use Configuration on TypingMind?

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

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

Which AI models can use Configuration?

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 Configuration?

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

Is the Configuration 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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