const agentDefinition = {
  id: "thinker-best-of-n",
  displayName: "Best-of-N Thinker",
  publisher: "codebuff",
  version: "0.0.1",
  model: "anthropic/claude-sonnet-4.5",
  toolNames: [
    "spawn_agents",
    "set_messages",
    "set_output"
  ],
  spawnableAgents: [
    "codebuff/thinker@0.0.5",
    "codebuff/thinker-selector@0.0.1"
  ],
  inputSchema: {
    params: {
      type: "object",
      properties: {
        n: {
          type: "number",
          description: "Number of parallel thinker agents to spawn. Defaults to 5. Use fewer for simple questions and max of 10 for complex questions."
        }
      }
    },
    prompt: {
      type: "string",
      description: "The problem you are trying to solve"
    }
  },
  includeMessageHistory: true,
  outputMode: "structured_output",
  spawnerPrompt: `Generates deep thinking by orchestrating multiple thinker agents, selects the best thinking output. Use this to help solve a hard problem. You must first gather all the relevant context *BEFORE* spawning this agent, as it can only think.`,
  systemPrompt: ``,
  instructionsPrompt: ``,
  stepPrompt: ``,
  handleSteps: function* handleStepsSonnet({
  agentState,
  prompt,
  params
}) {
  const n = Math.min(10, Math.max(1, params?.n ?? 5)), messages = agentState.messageHistory.concat();
  messages.pop();
  yield {
    toolName: "set_messages",
    input: {
      messages
    },
    includeToolCall: !1
  };
  const { toolResult: thinkersResult1 } = yield {
    toolName: "spawn_agents",
    input: {
      agents: Array.from({ length: n }, () => ({
        agent_type: "thinker",
        prompt
      }))
    },
    includeToolCall: !1
  }, thinkersResult = extractSpawnResults(thinkersResult1), letters = "ABCDEFGHIJKLMNOPQRSTUVWXYZ", thoughts = thinkersResult.map((content, index) => ({
    id: letters[index],
    content
  })), { toolResult: selectorResult } = yield {
    toolName: "spawn_agents",
    input: {
      agents: [
        {
          agent_type: "thinker-selector",
          params: { thoughts }
        }
      ]
    },
    includeToolCall: !1
  }, selectorOutput = extractSpawnResults(selectorResult)[0];
  if ("errorMessage" in selectorOutput) {
    yield {
      toolName: "set_output",
      input: { error: selectorOutput.errorMessage }
    };
    return;
  }
  const { thoughtId } = selectorOutput, chosenThought = thoughts.find((thought) => thought.id === thoughtId);
  if (!chosenThought) {
    yield {
      toolName: "set_output",
      input: { error: "Failed to find chosen thinking output." }
    };
    return;
  }
  yield {
    toolName: "set_output",
    input: {
      response: chosenThought.content
    },
    includeToolCall: !1
  };
  function extractSpawnResults(results) {
    if (!results)
      return [];
    return results.filter((result) => result.type === "json").map((result) => result.value).flat().map((result) => result.value.value ?? {
      errorMessage: result.value.errorMessage ?? "Error extracting spawn results"
    });
  }
},
  mcpServers: {},
  inheritParentSystemPrompt: true
}