const agentDefinition = {
  id: "planner",
  displayName: "Peter Plan",
  publisher: "codebuff",
  version: "0.0.1",
  model: "openai/gpt-5-chat",
  toolNames: [
    "spawn_agents",
    "read_files",
    "end_turn",
    "set_output"
  ],
  spawnableAgents: [
    "codebuff/file-explorer@0.0.2",
    "codebuff/web-researcher@0.0.1",
    "codebuff/docs-researcher@0.0.1",
    "codebuff/thinker-gpt-5-high@0.0.1"
  ],
  inputSchema: {
    prompt: {
      type: "string",
      description: "The task to plan for"
    }
  },
  includeMessageHistory: true,
  outputMode: "structured_output",
  spawnerPrompt: `Creates comprehensive plans by exploring the codebase, doing research on the web, and thinking deeply. You can also use it get deep answer to any question. This is a slow agent -- prefer to use it for complex tasks that require thinking.`,
  systemPrompt: `You are an expert programmer, architect, researcher, and general problem solver.
You spawn agents to help you gather information which will be used to create a plan.

{CODEBUFF_FILE_TREE_PROMPT}
{CODEBUFF_KNOWLEDGE_FILES_CONTENTS}`,
  instructionsPrompt: `You are gathering information which will be used to create a plan.
  
- It's helpful to spawn a file-explorer to find all the relevant parts of the codebase. In parallel as part of the same spawn_agents tool call, you may also spawn a web-researcher or docs-researcher to search the web or technical documentation for relevant information.
- After you are satisfied with the information you have gathered from these agents, stop and use the end_turn tool. The plan will be created in a separate step. Do not spawn thinker-gpt-5-high in this step.`,
  stepPrompt: ``,
  handleSteps: function* ({ prompt }) {
    const { agentState } = yield "STEP_ALL", messagesBlob = agentState.messageHistory.slice(2).map((message) => typeof message.content === "string" ? message.content : message.content.map((content) => content.type === "text" ? content.text : "").join(`
`)).join(`
`);
    yield {
      toolName: "read_files",
      input: {
        paths: parseFilePathsFromToolResult(messagesBlob)
      }
    };
    const { toolResult: deepThinkerToolResult } = yield {
      toolName: "spawn_agents",
      input: {
        agents: [
          {
            agent_type: "thinker-gpt-5-high",
            prompt: `Create a clear implementation plan for the following task, with a focus on simplicity and making the minimal changes necessary for an awesome implementation. Prompt: ${prompt}`
          }
        ]
      }
    };
    yield {
      toolName: "set_output",
      input: {
        plan: deepThinkerToolResult
      }
    };
    function parseFilePathsFromToolResult(content) {
      const filePaths = [], filePathRegex = /(?:^|\s|\*\s*)((?:[\w-]+\/)*[\w.-]+\.[a-zA-Z]{1,4})(?=\s|$|,|\.|:)/gm;
      let match;
      while ((match = filePathRegex.exec(content)) !== null) {
        const filePath = match[1];
        if (filePath && !filePath.startsWith("http") && !filePath.includes("@") && filePath.length > 3 && filePath.split("/").length <= 10)
          filePaths.push(filePath);
      }
      const backtickPathRegex = /`([^`]+\.[a-zA-Z]{1,4})`/g;
      while ((match = backtickPathRegex.exec(content)) !== null) {
        const filePath = match[1];
        if (filePath && !filePath.startsWith("http") && !filePath.includes("@"))
          filePaths.push(filePath);
      }
      return [...new Set(filePaths)];
    }
  }
}