SKILL.md
Config Online Evaluations
Attach judges to config variations for automatic quality scoring using LLM-as-a-judge methodology. Judges evaluate responses and return scores between 0.0 and 1.0.
Prerequisites
- LaunchDarkly account with AgentControl enabled
- The remotely hosted LaunchDarkly MCP server configured in your environment
- Existing config with variations (use
configs-createskill) - To run judges from your application:
launchdarkly-ai-server0.3.0+ (Python) or@launchdarkly/ai-node0.3.0+ (Node.js), plus a provider handler package for each provider your configs and judges use
API Access
Use the LaunchDarkly MCP server tools for every step in the workflow: they authenticate via OAuth and need no token. The REST API is only for scripts and CI that can't use MCP (see Scripting without MCP). In that case, ask the user to paste an API access token for this session and substitute it for {api_token} in the examples below. Do not search environment variables, .env files, or agent/MCP config files for credentials.