custom-metrics

Custom Metrics for Configs

Full lifecycle management of custom business metrics: create metric definitions via API, track events via SDK, retrieve metric data, and manage metrics programmatically.

Prerequisites

• LaunchDarkly SDK initialized (see sdk)
• LaunchDarkly API token with writer role for metric management
• Understanding of built-in agent metrics (see built-in-metrics)

API Key Detection

Before prompting the user for an API key, try to detect it automatically:

1. Check Claude MCP config - Read ~/.claude/config.json and look for mcpServers.launchdarkly.env.LAUNCHDARKLY_API_KEY
2. Check environment variables - Look for LAUNCHDARKLY_API_KEY, LAUNCHDARKLY_API_TOKEN, or LD_API_KEY
3. Prompt user - Only if detection fails, ask the user for their API key

import os
import json
from pathlib import Path

def get_launchdarkly_api_key():
    """Auto-detect LaunchDarkly API key from Claude config or environment."""
    # 1. Check Claude MCP config
    claude_config = Path.home() / ".claude" / "config.json"
    if claude_config.exists():
        try:
            config = json.load(open(claude_config))
            api_key = config.get("mcpServers", {}).get("launchdarkly", {}).get("env", {}).get("LAUNCHDARKLY_API_KEY")
            if api_key:
                return api_key
        except (json.JSONDecodeError, IOError):
            pass

    # 2. Check environment variables
    for var in ["LAUNCHDARKLY_API_KEY", "LAUNCHDARKLY_API_TOKEN", "LD_API_KEY"]:
        if os.environ.get(var):
            return os.environ[var]

    return None

Metrics Lifecycle Overview

Step	Method	Purpose
1. Create	API	Define metric in LaunchDarkly
2. Track	SDK	Send events to the metric
3. Get	API	Retrieve metric definition/data
4. Update	API	Modify metric properties
5. Delete	API	Remove metric

1. Create Metric (API)

Required fields for numeric custom metrics:

• successCriteria - Must be one of: "HigherThanBaseline", "LowerThanBaseline"
• unit - e.g., "count", "percent", "milliseconds"