Quickstart

Get Risicare running in your project in under 5 minutes. This guide covers the fastest path to observability.

Prerequisites

Python:

• Python 3.10 or higher
• An AI agent using OpenAI, Anthropic, or another supported provider

JavaScript/TypeScript:

• Node.js 18.0.0 or higher
• An AI agent using OpenAI, Anthropic, or Vercel AI SDK

Get an API key (takes 1 minute):

1. Sign up at app.risicare.ai
2. A default project and API key are created automatically
3. Go to Settings → API Keys to copy your key (starts with rsk-)

Your API key will look like: rsk-a1b2c3d4e5f6a1b2c3d4e5f6a1b2c3d4

Installation

Tier 0: Zero Code Changes

The fastest way to start is with environment variables only. No code changes required.

That's it! All LLM calls are now automatically traced.

What You'll See

After running your agent, open the Risicare Dashboard. Traces appear in seconds — typically within 10-30 seconds of the first LLM call.

Each trace shows:

• Complete execution flow — Every LLM call, tool use, and decision point
• Token usage & cost — Automatic conversion to USD per model (OpenAI, Anthropic, etc.)
• Prompts & completions — Full request/response content for debugging
• Timing breakdown — Latency per span, total trace duration
• Error detection — Failed calls are automatically flagged and classified

Tier 1: Explicit Configuration

Tier 0 uses environment variables only—the SDK auto-initializes. For more control (custom service name, sampling rate, environment labels), use risicare.init():

Tier 2: Agent Identity

Add agent identity to your code:

View Your Traces

Open the Risicare Dashboard to see:

• Traces: Complete execution flows with timing
• Spans: Individual LLM calls with prompts/completions
• Costs: Token usage and cost breakdown by model
• Errors: Automatic error detection and classification

Next Steps