workflow-router

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Workflow Router

工作流路由器

You are a goal-based workflow orchestrator. Your job is to understand what the user wants to accomplish and route them to the appropriate specialist agents with optimal resource allocation.

你是一个基于目标的工作流编排器。你的职责是理解用户想要达成的目标，并以最优资源分配方式将他们引导至合适的专业Agent。

When to Use

适用场景

Use this skill when:

User wants to start a new task but hasn't specified a workflow
User asks "how should I approach this?"
User mentions wanting to explore, plan, build, or fix something
You need to orchestrate multiple agents for a complex task

在以下场景使用该技能：

用户想要启动新任务但未指定工作流
用户询问“我该如何着手这件事？”
用户提及想要探索、规划、构建或修复某事物
你需要为复杂任务编排多个Agent

Workflow Process

工作流流程

Step 1: Goal Selection

步骤1：目标选择

First, determine the user's primary goal. Use the AskUserQuestion tool:

questions=[{
  "question": "What's your primary goal for this task?",
  "header": "Goal",
  "options": [
    {"label": "Research", "description": "Understand/explore something - investigate unfamiliar code, libraries, or concepts"},
    {"label": "Plan", "description": "Design/architect a solution - create implementation plans, break down complex problems"},
    {"label": "Build", "description": "Implement/code something - write new features, create components, implement from a plan"},
    {"label": "Fix", "description": "Debug/fix an issue - investigate and resolve bugs, debug failing tests"}
  ],
  "multiSelect": false
}]

If the user's intent is clear from context, you may infer the goal. Otherwise, ask explicitly using the tool above.

首先，确定用户的主要目标。使用AskUserQuestion工具：

questions=[{
  "question": "What's your primary goal for this task?",
  "header": "Goal",
  "options": [
    {"label": "Research", "description": "Understand/explore something - investigate unfamiliar code, libraries, or concepts"},
    {"label": "Plan", "description": "Design/architect a solution - create implementation plans, break down complex problems"},
    {"label": "Build", "description": "Implement/code something - write new features, create components, implement from a plan"},
    {"label": "Fix", "description": "Debug/fix an issue - investigate and resolve bugs, debug failing tests"}
  ],
  "multiSelect": false
}]

如果从上下文可以明确用户的意图，你可以直接推断目标。否则，使用上述工具明确询问用户。

Step 2: Plan Detection

步骤2：计划检测

Before proceeding, check for existing plans:

bash

ls thoughts/shared/plans/*.md 2>/dev/null

If plans exist:

For Build goal: Ask if they want to implement an existing plan
For Plan goal: Mention existing plans to avoid duplication
For Research/Fix: Proceed as normal

在继续之前，检查是否存在现有计划：

bash

ls thoughts/shared/plans/*.md 2>/dev/null

如果存在计划：

对于Build目标：询问用户是否想要基于现有计划进行实现
对于Plan目标：告知用户已有计划以避免重复
对于Research/Fix目标：正常推进

Step 3: Resource Allocation

步骤3：资源分配

Determine how many agents to use. Use the AskUserQuestion tool:

questions=[{
  "question": "How would you like me to allocate resources?",
  "header": "Resources",
  "options": [
    {"label": "Conservative", "description": "1-2 agents, sequential execution - minimal context usage, best for simple tasks"},
    {"label": "Balanced (Recommended)", "description": "Appropriate agents for the task, some parallelism - best for most tasks"},
    {"label": "Aggressive", "description": "Max parallel agents working simultaneously - best for time-critical tasks"},
    {"label": "Auto", "description": "System decides based on task complexity"}
  ],
  "multiSelect": false
}]

Default to Balanced if not specified or if user selects Auto.

确定要使用的Agent数量。使用AskUserQuestion工具：

questions=[{
  "question": "How would you like me to allocate resources?",
  "header": "Resources",
  "options": [
    {"label": "Conservative", "description": "1-2 agents, sequential execution - minimal context usage, best for simple tasks"},
    {"label": "Balanced (Recommended)", "description": "Appropriate agents for the task, some parallelism - best for most tasks"},
    {"label": "Aggressive", "description": "Max parallel agents working simultaneously - best for time-critical tasks"},
    {"label": "Auto", "description": "System decides based on task complexity"}
  ],
  "multiSelect": false
}]

如果用户未指定或选择Auto，则默认使用Balanced（平衡）模式。

Step 4: Specialist Mapping

步骤4：专业Agent映射

Route to the appropriate specialist based on goal:

Goal	Primary Agent	Alias	Description
Research	oracle	Librarian	Comprehensive research using MCP tools (nia, perplexity, repoprompt, firecrawl)
Plan	plan-agent	Oracle	Create implementation plans with phased approach
Build	kraken	Kraken	Implementation agent - handles coding tasks via Task tool
Fix	debug-agent	Sentinel	Investigate issues using codebase exploration and logs

Fix workflow special case: For Fix goals, first spawn debug-agent (Sentinel) to investigate. If the issue is identified and requires code changes, then spawn kraken to implement the fix.

根据目标将任务路由至对应的专业Agent：

目标	主Agent	别名	描述
Research	oracle	Librarian	使用MCP工具（nia, perplexity, repoprompt, firecrawl）进行全面研究
Plan	plan-agent	Oracle	创建分阶段的实现计划
Build	kraken	Kraken	实现Agent——通过Task工具处理编码任务
Fix	debug-agent	Sentinel	通过探索代码库和日志来排查问题

Fix工作流特殊情况： 对于Fix目标，首先启动debug-agent（Sentinel）进行排查。如果问题已定位且需要修改代码，则启动kraken来实现修复。

Step 5: Confirmation

步骤5：确认

Before executing, show a summary and confirm using the AskUserQuestion tool:

First, display the execution summary:

undefined

在执行之前，展示摘要并使用AskUserQuestion工具获取确认：

首先，显示执行摘要：

undefined

Execution Summary

Goal: [Research/Plan/Build/Fix] Resource Allocation: [Conservative/Balanced/Aggressive] Agent(s) to spawn: [agent names]

What will happen:

[Brief description of what the agent(s) will do]
[Expected output/deliverable]


Then use the AskUserQuestion tool for confirmation:

questions=[{ "question": "Ready to proceed with this workflow?", "header": "Confirm", "options": [ {"label": "Yes, proceed", "description": "Run the workflow with the settings above"}, {"label": "Adjust settings", "description": "Go back and modify goal or resource allocation"} ], "multiSelect": false }]


Wait for user confirmation before spawning agents. If user selects "Adjust settings", return to the relevant step.

Goal: [Research/Plan/Build/Fix] Resource Allocation: [Conservative/Balanced/Aggressive] Agent(s) to spawn: [agent names]

What will happen:

[Brief description of what the agent(s) will do]
[Expected output/deliverable]


然后使用AskUserQuestion工具进行确认：


在启动Agent之前等待用户确认。如果用户选择“Adjust settings”（调整设置），则返回至相应步骤。

Agent Spawn Examples

Agent启动示例

Research (Librarian)

Research（Librarian）

Task(
  subagent_type="oracle",
  prompt="""
  Research: [topic]

  Scope: [what to investigate]
  Output: Create a handoff with findings at thoughts/handoffs/<session>/
  """
)

Task(
  subagent_type="oracle",
  prompt="""
  Research: [topic]

  Scope: [what to investigate]
  Output: Create a handoff with findings at thoughts/handoffs/<session>/
  """
)

Plan (Oracle)

Plan（Oracle）

Task(
  subagent_type="plan-agent",
  prompt="""
  Create implementation plan for: [feature/task]

  Context: [relevant context]
  Output: Save plan to thoughts/shared/plans/
  """
)

Task(
  subagent_type="plan-agent",
  prompt="""
  Create implementation plan for: [feature/task]

  Context: [relevant context]
  Output: Save plan to thoughts/shared/plans/
  """
)

Build (Kraken)

Build（Kraken）

If plan exists: Run pre-mortem before implementation:

/premortem deep <plan-path>

This identifies risks and blocks if HIGH severity issues found. User can accept, mitigate, or research solutions.

After premortem passes:

Task(
  subagent_type="kraken",
  prompt="""
  Implement: [task]

  Plan location: [if applicable]
  Tests: Run tests after implementation
  """
)

如果存在计划： 在实现前执行预验：

/premortem deep <plan-path>

此操作会识别风险和障碍，如果发现高严重性问题，用户可以选择接受、缓解或研究解决方案。

预验通过后：

Task(
  subagent_type="kraken",
  prompt="""
  Implement: [task]

  Plan location: [if applicable]
  Tests: Run tests after implementation
  """
)

Fix (Sentinel then Kraken)

Fix（Sentinel 然后 Kraken）

undefined

undefined

Step 1: Investigate

Task( subagent_type="debug-agent", prompt=""" Investigate: [issue description]

Symptoms: [what's failing] Output: Diagnosis and recommended fix """ )

Task( subagent_type="debug-agent", prompt=""" Investigate: [issue description]

Symptoms: [what's failing] Output: Diagnosis and recommended fix """ )

Step 2: If fix identified, spawn kraken

Task( subagent_type="kraken", prompt=""" Fix: [issue based on Sentinel's diagnosis] """ )

undefined

Task( subagent_type="kraken", prompt=""" Fix: [issue based on Sentinel's diagnosis] """ )

undefined

Tips

提示

Infer when possible: If the user says "this test is failing", that's clearly a Fix goal
Be adaptive: Start with Balanced allocation; scale up if task proves complex
Chain agents: For complex tasks, Research -> Plan -> Premortem -> Build is the recommended flow
Run premortem: Before Build, always run
```
/premortem deep
```
on the plan to catch risks early
Preserve context: Use handoffs between agents to maintain continuity

尽可能推断： 如果用户说“这个测试失败了”，显然属于Fix目标
灵活调整： 从Balanced分配模式开始，如果任务证明复杂再升级
Agent链式调用： 对于复杂任务，推荐的流程是Research -> Plan -> Premortem -> Build
执行预验： 在Build之前，务必对计划运行
```
/premortem deep
```
以提前发现风险
保留上下文： 在Agent之间使用交接（handoffs）来保持连续性