TurnKit

Build durable Ruby AI agents with turns, tools, skills, and Rails persistence.

Installation

Add this line to your application's Gemfile:

gem "turnkit"

Run:

bundle install

Quick Start

Set a provider key:

export ANTHROPIC_API_KEY=...

Create an agent:

require "turnkit"

agent = TurnKit::Agent.new(
  name: "helper",
  instructions: "Answer briefly."
)

Ask a question:

turn = agent.conversation.ask("Explain Ruby blocks in one sentence.")
puts turn.output_text

Usage

Models

Set the default model:

TurnKit.default_model = "claude-sonnet-4-5"

Use OpenAI:

export OPENAI_API_KEY=...

Set an OpenAI model:

TurnKit.default_model = "gpt-4.1-mini"

Conversations

Create a conversation:

agent = TurnKit::Agent.new(
  name: "writer",
  instructions: "Write clear release notes."
)

Add context:

conversation = agent.conversation(subject: "v1 launch")
conversation.say("Mention faster tool execution.")

Run the agent:

turn = conversation.run!
puts turn.output_text

Tools

Create a tool:

class SaveReport < TurnKit::Tool
  description "Save a report."
  usage_hint "Use when the user asks to persist a report."
  parameter :title, :string, required: true
  parameter :body, :string, required: true

  def self.ends_turn? = true
  def self.completion_message(result) = "Saved #{result.fetch("report_id")}."

  def call(title:, body:, context:)
    { report_id: "rep_1", title: title, body: body }
  end
end

Use the tool:

agent = TurnKit::Agent.new(
  name: "reporter",
  instructions: "Save reports when asked.",
  tools: [SaveReport]
)

Ask for tool use:

turn = agent.conversation.ask("Save a short status report.")
puts turn.output_text

Skills

Load a skill:

skill = TurnKit::Skill.from_file("skills/research.md")

Use the skill:

agent = TurnKit::Agent.new(
  name: "researcher",
  skills: [skill]
)

Sub-agents

Create a sub-agent:

writer = TurnKit::Agent.new(
  name: "writer",
  description: "Draft concise copy."
)

Delegate to it:

editor = TurnKit::Agent.new(
  name: "editor",
  sub_agents: [writer]
)

Ask the parent agent:

turn = editor.conversation.ask("Ask the writer for three headlines.")
puts turn.output_text

Usage and costs

Inspect token usage:

turn.usage.total_tokens
conversation.usage.total_tokens
agent.usage.total_tokens

Inspect costs:

turn.cost.total
conversation.cost.total
agent.cost.total

Use RubyLLM registry prices by default.

Override model rates:

TurnKit.cost_rates = {
  "my-model" => {
    input: 0.25,
    output: 1.00,
    cached_input: 0.05,
    cache_creation: 0.25
  }
}

Override cost calculation:

TurnKit.cost_calculator = ->(usage, model) do
  {
    input: usage.input_tokens * 0.25 / 1_000_000.0,
    output: usage.output_tokens * 1.00 / 1_000_000.0
  }
end

Limit turn cost:

agent = TurnKit::Agent.new(
  name: "analyst",
  cost_limit: 0.25
)

Prompt caching

Enable prompt caching:

TurnKit.prompt_cache = :auto

Disable prompt caching:

TurnKit.prompt_cache = :off

Split custom prompts:

agent = TurnKit::Agent.new(
  name: "cached",
  system_prompt: [
    "Stable instructions and tool guidance.",
    TurnKit::SystemPrompt::CACHE_BOUNDARY,
    "Dynamic subject and live context."
  ].join("\n")
)

Custom clients

Create a client:

class MyClient < TurnKit::Client
  def chat(model:, messages:, tools:, instructions:, temperature: nil, metadata: nil)
    TurnKit::Result.new(
      text: "provider response",
      model: model,
      usage: TurnKit::Usage.new(
        input_tokens: 100,
        output_tokens: 20,
        cached_tokens: 80,
        cache_write_tokens: 100
      )
    )
  end
end

Use the client:

TurnKit.client = MyClient.new

Split cache sections:

stable, dynamic = TurnKit::SystemPrompt.split_cache_boundary(instructions)

Rails

Install Rails persistence:

bin/rails generate turnkit:install

Run migrations:

bin/rails db:migrate

Configure Rails:

TurnKit.store = TurnKit::ActiveRecordStore.new

Reconcile stale turns:

TurnKit.reconcile_stale!

Options

Configure defaults:

TurnKit.default_model = "claude-sonnet-4-5"
TurnKit.max_iterations = 25
TurnKit.timeout = 300
TurnKit.max_depth = 3
TurnKit.max_tool_executions = 100
TurnKit.cost_limit = nil
TurnKit.cost_rates = {}
TurnKit.cost_calculator = nil
TurnKit.prompt_cache = :auto

Override an agent:

agent = TurnKit::Agent.new(
  name: "analyst",
  model: "gpt-4.1-mini",
  max_iterations: 10,
  timeout: 60,
  cost_limit: 0.25
)

Option	Description
default_model	Set the default RubyLLM model.
client	Set the model client.
store	Set the conversation store.
max_iterations	Limit model calls per turn.
timeout	Limit seconds per root turn.
max_tool_executions	Limit tool calls per root turn.
cost_limit	Limit cost per root turn.
cost_rates	Override prices by model.
cost_calculator	Override cost calculation.
prompt_cache	Use provider prompt caching.

Contributing

Report bugs and open pull requests on GitHub:

https://github.com/samuelcouch/turnkit

Run tests:

bundle exec rake test

License

See the MIT License.