TASK_TOOL_DESCRIPTION = 'Launch an ephemeral subagent to handle complex, multi-step independent tasks with isolated context windows.\n\nAvailable agent types and the tools they have access to:\n{available_agents}\n\nWhen using the Task tool, you must specify a subagent_type parameter to select which agent type to use.\n\n## Usage notes:\n1. Launch multiple agents concurrently whenever possible, to maximize performance; to do that, use a single message with multiple tool uses\n2. When the agent is done, it will return a single message back to you. The result returned by the agent is not visible to the user. To show the user the result, you should send a text message back to the user with a concise summary of the result.\n3. Each agent invocation is stateless. You will not be able to send additional messages to the agent, nor will the agent be able to communicate with you outside of its final report. Therefore, your prompt should contain a highly detailed task description for the agent to perform autonomously and you should specify exactly what information the agent should return back to you in its final and only message to you.\n4. The agent\'s outputs should generally be trusted\n5. Clearly tell the agent whether you expect it to create content, perform analysis, or just do research (
search,
file reads,
web fetches,
etc.), since it is not aware of the user\'s intent\n6. If the agent description mentions that it should be used proactively, then you should try your best to use it without the user having to ask for it first. Use your judgement.\n7. When only the general-purpose agent is provided, you should use it for all tasks. It is great for isolating context and token usage, and completing specific, complex tasks, as it has all the same capabilities as the main agent.\n\n### Example usage of the general-purpose agent:\n\n<example_agent_descriptions>\n"general-purpose": use this agent for general purpose tasks, it has access to all tools as the main agent.\n</example_agent_descriptions>\n\n<example>\nUser: "I want to conduct research on the accomplishments of Lebron James, Michael Jordan, and Kobe Bryant, and then compare them."\nAssistant: *Uses the task tool in parallel to conduct isolated research on each of the three players*\nAssistant: *Synthesizes the results of the three isolated research tasks and responds to the User*\n<commentary>\nResearch is a complex, multi-step task in it of itself.\nThe research of each individual player is not dependent on the research of the other players.\nThe assistant uses the task tool to break down the complex objective into three isolated tasks.\nEach research task only needs to worry about context and tokens about one player, then returns synthesized information about each player as the Tool Result.\nThis means each research task can dive deep and spend tokens and context deeply researching each player, but the final result is synthesized information, and saves us tokens in the long run when comparing the players to each other.\n</commentary>\n</example>\n\n<example>\nUser: "Analyze a single large code repository for security vulnerabilities and generate a report."\nAssistant: *Launches a single `task` subagent for the repository analysis*\nAssistant: *Receives report and integrates results into final summary*\n<commentary>\nSubagent is used to isolate a large, context-heavy task, even though there is only one. This prevents the main thread from being overloaded with details.\nIf the user then asks followup questions, we have a concise report to reference instead of the entire history of analysis and tool calls, which is good and saves us time and money.\n</commentary>\n</example>\n\n<example>\nUser: "Schedule two meetings for me and prepare agendas for each."\nAssistant: *Calls the task tool in parallel to launch two `task` subagents (one per meeting) to prepare agendas*\nAssistant: *Returns final schedules and agendas*\n<commentary>\nTasks are simple individually, but subagents help silo agenda preparation.\nEach subagent only needs to worry about the agenda for one meeting.\n</commentary>\n</example>\n\n<example>\nUser: "I want to order a pizza from Dominos, order a burger from McDonald\'s, and order a salad from Subway."\nAssistant: *Calls tools directly in parallel to order a pizza from Dominos, a burger from McDonald\'s, and a salad from Subway*\n<commentary>\nThe assistant did not use the task tool because the objective is super simple and clear and only requires a few trivial tool calls.\nIt is better to just complete the task directly and NOT use the `task`tool.\n</commentary>\n</example>\n\n### Example usage with custom agents:\n\n<example_agent_descriptions>\n"content-reviewer": use this agent after you are done creating significant content or documents\n"greeting-responder": use this agent when to respond to user greetings with a friendly joke\n"research-analyst": use this agent to conduct thorough research on complex topics\n</example_agent_description>\n\n<example>\nuser: "Please write a function that checks if a number is prime"\nassistant: Sure let me write a function that checks if a number is prime\nassistant: First let me use the Write tool to write a function that checks if a number is prime\nassistant: I\'m going to use the Write tool to write the following code:\n<code>\nfunction isPrime(n) {{\n if (n <= 1) return false\n for (let i = 2; i * i <= n; i++) {{\n if (n % i === 0
) return false\n }}\n return true\n}}\n</code>\n<commentary>\nSince significant content was created and the task was completed, now use the content-reviewer agent to review the work\n</commentary>\nassistant: Now let me use the content-reviewer agent to review the code\nassistant: Uses the Task tool to launch with the content-reviewer agent\n</example>\n\n<example>\nuser: "Can you help me research the environmental impact of different renewable energy sources and create a comprehensive report?"\n<commentary>\nThis is a complex research task that would benefit from using the research-analyst agent to conduct thorough analysis\n</commentary>\nassistant: I\'ll help you research the environmental impact of renewable energy sources. Let me use the research-analyst agent to conduct comprehensive research on this topic.\nassistant: Uses the Task tool to launch with the research-analyst agent, providing detailed instructions about what research to conduct and what format the report should take\n</example>\n\n<example>\nuser: "Hello"\n<commentary>\nSince the user is greeting, use the greeting-responder agent to respond with a friendly joke\n</commentary>\nassistant: "I\'m going to use the Task tool to launch with the greeting-responder agent"\n</example>'
