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workflow-router工作流路由器

Agent Skill

workflow-router 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

7,564

周安装

309

GitHub Stars

3,664

下载量

2,447
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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:workflow-router(工作流路由器)
来源仓库:https://github.com/parcadei/continuous-claude-v3
仓库路径:skills/workflow-router
安装命令:
npx skills add https://github.com/parcadei/continuous-claude-v3 --skill workflow-router
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/parcadei/continuous-claude-v3 --skill workflow-router

简介

用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。

  • 支持基于关键词、任务场景或来源线索进行信息聚合与过滤,提升研究效率。
  • 通过 npx 命令从 GitHub 仓库安装,具体用法需结合原始 README 进一步确认。
  • 安装前建议核实权限范围、维护状态及是否涉及联网、命令执行或文件操作。
  • workflow-router 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Workflow Router

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.

When to Use

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

Workflow Process

Step 1: Goal Selection

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.

Step 2: Plan Detection

Before proceeding, check for existing plans:

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

Step 3: Resource Allocation

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.

Step 4: Specialist Mapping

Route to the appropriate specialist based on goal:

GoalPrimary AgentAliasDescription
ResearchoracleLibrarianComprehensive research using MCP tools (nia, perplexity, repoprompt, firecrawl)
Planplan-agentOracleCreate implementation plans with phased approach
BuildkrakenKrakenImplementation agent - handles coding tasks via Task tool
Fixdebug-agentSentinelInvestigate 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.

Step 5: Confirmation

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

First, display the execution summary:

## 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.

Agent Spawn Examples

Research (Librarian)

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

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

Plan (Oracle)

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

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

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
  """
)

Fix (Sentinel then Kraken)

# Step 1: Investigate
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]
  """
)

Tips

  • 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

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

28.45%
按下载量换算696

OpenCode

25.71%
按下载量换算629

Gemini CLI

17.64%
按下载量换算432

Codex

12.35%
按下载量换算302

Cursor

7.38%
按下载量换算181

Antigravity

3.48%
按下载量换算85

安全审计

Gen Agent Trust Hub

未通过

Socket

通过

Snyk

可疑

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/parcadei/continuous-claude-v3 --skill workflow-router;npx skills add parcadei/continuous-claude-v3 --skill "workflow-router" 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。

来源信息

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