For AI agents: a documentation index is available at the root level at /llms.txt and /llms-full.txt. Append /llms.txt to any URL for a page-level index, or .md for the markdown version of any page.
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User GuideDeveloper GuidesAPI Reference
User GuideDeveloper GuidesAPI Reference
  • Getting Started
    • What is Runtype?
    • Creating your account
    • Platform keys vs. BYOK
    • Understanding the Runtype UI
    • Quickstart: Social Media Post Generator
    • Quickstart: From Agent to Chat Widget
  • Dashboard
    • What is the Dashboard?
    • Daily executions
  • Playground
    • What is the Playground?
  • Products & Surfaces
    • What are Products?
    • What are Surfaces?
    • Creating a product
    • Setting up a chat surface
    • Setting up an API surface
    • Setting up an MCP surface
    • Setting up an A2A surface
    • Setting up a Slack surface
    • Setting up a webhook surface
    • MCP authentication
    • Authenticating with product API keys
    • Embedding the chat widget (script tag)
    • Embedding the chat widget (React)
    • Surface orchestration modes
    • Product views
    • Adding capabilities to a product
    • Connecting external agents
    • How A2A works
    • Connecting to MCP clients
    • Scoping API keys to capabilities
    • Auto-generated OpenAPI spec
    • Calling your API endpoints
    • Client tokens and domain restrictions
    • AI-powered theme generation
    • Widget theming and customization
    • Product versioning and status
  • Flows
    • What are Flows?
    • Creating and editing flows
    • Flow step types overview
    • Agent and flow templates
    • Using prompt steps
    • Using transform-data steps
    • Using conditional steps
    • Using fetch-url and api-call steps
    • Using record steps (upsert/retrieve)
    • Flow variables and templates
    • Flow versioning and publishing
    • Running flows in batch
    • Handling batch failures
    • Debugging flows
  • Agents
    • What are Agents?
    • Creating and configuring agents
    • Agent tools
  • Records
    • What are Records?
    • Creating and managing records
    • Using records in flows
    • Filtering and searching records
  • Tools
    • What are Tools?
    • Built-in tools
    • Creating custom tools
    • Creating external tools
    • Runtime tools
  • Evals
    • What are Evals?
    • Running an eval
    • Interpreting eval results
  • Schedules
    • What are Schedules?
    • Automating batch processing
  • Logs
    • What are Logs?
    • Working with logs
  • Integrations
    • Connecting AI model providers
    • Slack integration
    • Google Workspace integration
    • GitHub integration
    • Linear integration
    • Weaviate (vector search)
    • Firecrawl (web scraping)
    • Exa (web search)
    • Braintrust (tracing)
  • Settings
    • What's in Settings?
    • Available AI models
    • What are Organizations?
    • Managing AI models
    • Managing API keys
    • Managing secrets
    • Billing and plans
    • Usage data
    • Team members and permissions
    • Appearance and preferences
    • Integrations (PostHog, Weaviate, Daytona)
  • Troubleshooting & FAQ
    • FAQ
    • Rate limits and usage
    • Managing Runtype with Claude
    • Agent skills
    • Flow execution failures
    • Common errors and solutions
    • Authentication issues
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On this page
  • Accessing usage data
  • Key metrics
  • Cost optimization tips
  • Use cheaper models when possible
  • Reduce max tokens
  • Cache API responses
  • Batch processing
  • Monitor and optimize prompts
  • Understanding provider billing
  • Next steps
Settings

Usage data

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Team members and permissions

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Monitor Flow executions, AI token usage, and costs to understand and optimize your Runtype spending.

Accessing usage data

  1. Go to Settings → Usage
  2. View usage analytics with charts and breakdowns
  3. Switch between 7-day, 30-day, or 90-day views

Key metrics

The Usage tab shows several chart views:

  • Spend over time — Track spending trends
  • Spend by category — See where costs are distributed
  • Spend by model — Identify which models drive the most cost
  • Spend by tool — See tool-level cost attribution
  • Executions over time — Monitor execution volume

Usage data refreshes automatically. The tab shows a friendly empty state until you have run your first Flow or Agent.

Cost optimization tips

Use cheaper models when possible

GPT-5.4 Nano is significantly cheaper than GPT-5.4 for simple tasks.

Reduce max tokens

Lower max tokens limits prevent unnecessarily long responses.

Cache API responses

Store results in Records instead of making duplicate API calls.

Batch processing

Process multiple items per execution to amortize overhead costs.

Monitor and optimize prompts

Shorter, more focused prompts reduce input token costs.

Understanding provider billing

When using BYOK:

  • Runtype estimates costs based on token usage
  • Actual charges come from providers (OpenAI, Anthropic, etc.)
  • Check provider dashboards for precise billing
  • Runtype’s estimates help predict costs but aren’t invoices

Next steps

  • Billing and plans to manage your subscription
  • Connecting AI model providers for BYOK setup
  • Running an Eval to test cheaper model alternatives
  • Working with Logs to investigate expensive executions