architect-create-llm-test
Create an LLM response test
Use this when the user wants to assert that the agent's reply to a turn matches a natural-language success condition. This is a single-turn response judgement. If they instead want to verify which tool fires, use the tool-test skill; if they want a multi-turn role-played conversation, use the simulation-test skill. For a DOM or Architect-style agent whose first action is almost always starting a procedure, prefer a simulation test instead, since a single-turn LLM test only grades that first action and returns useless verdicts.
Host https://api.elevenlabs.io, header xi-api-key: $API_KEY. The engineer supplies $API_KEY, $AGENT_ID, and $BRANCH_ID where relevant.
1. Gather context first
Read only what you need to ground the test, in parallel where independent:
GET /v1/convai/agents/$AGENT_ID?branch_id=$BRANCH_ID- to ground the success condition in the agent's actual behavior: its first message, system prompt, and any required disclosures. A condition like "greets the user" is worthless if you do not know what the greeting is supposed to be.- List existing tests to avoid a near-duplicate and to copy the naming convention already in use.
If the user is turning a real bad call into a regression test, read the conversation (GET /v1/convai/conversations?agent_id=$AGENT_ID, then GET /v1/convai/conversations/{conversation_id}) and lift the transcript into chat_history. Conversation reads carry customer PII; do not copy them into other systems or logs, and respect zero-retention-mode accounts.