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create-workflow-command创建工作流命令

Agent Skill

create-workflow-command 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

1,091

周安装

45

GitHub Stars

891

下载量

356
CodexClaudeCursorGemini CLI

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

2

许可证

unknown

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:create-workflow-command(创建工作流命令)
来源仓库:https://github.com/neolabhq/context-engineering-kit
仓库路径:skills/create-workflow-command
安装命令:
npx skills add https://github.com/neolabhq/context-engineering-kit --skill create-workflow-command
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。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/neolabhq/context-engineering-kit --skill create-workflow-command

简介

该技能创建 orchestrator 命令,通过分发子代理执行多步工作流,解决上下文膨胀问题。

  • 适用于需要分解复杂任务、避免主指令过长或提升模块化协作效率的场景。
  • 将详细步骤存储于独立文件,由子代理按需读取,保持主命令简洁高效。
  • 安装方式:GitHub 仓库,使用 npx 命令添加;注意文件读写权限与子代理配置路径。
  • create-workflow-command 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Create Workflow Command

Create a command that orchestrates multi-step workflows by dispatching sub-agents with task-specific instructions stored in separate files.

User Input

Workflow Name: $1
Description: $2

Architecture Overview

Workflow commands solve the context bloat problem: instead of embedding detailed step instructions in the main command (polluting orchestrator context), store them in separate task files that sub-agents read on-demand.

plugins/<plugin-name>/
├── commands/
│   └── <workflow>.md          # Lean orchestrator (~50-100 tokens per step)
├── agents/                     # Optional: reusable executor agents
│   └── step-executor.md       # Custom agent with specific tools/behavior
└── tasks/                      # All task instructions directly here
    ├── step-1-<name>.md       # Full instructions (~500+ tokens each)
    ├── step-2-<name>.md
    ├── step-3-<name>.md
    └── common-context.md      # Shared context across workflows

Key Principles

1. Context Isolation

Each sub-agent gets its own isolated context window. The main orchestrator stays lean while sub-agents load detailed instructions from files.

ComponentContext CostPurpose
Orchestrator command~50-100 tokens/stepDispatch and coordinate
Task file~500+ tokensDetailed step instructions
Sub-agent base~294 tokensSystem prompt overhead

2. Sub-Agent Capabilities

Sub-agents spawned via Task tool:

CapabilityAvailableNotes
Read tool✅ YesCan read any file
Write tool✅ YesIf not restricted
Grep/Glob✅ YesFor code search
Skills loading❌ NoSkills don't auto-load in sub-agents
Spawn sub-agents❌ NoCannot nest Task tool
Resume context✅ YesVia resume parameter

3. File Reference Pattern

Use ${CLAUDE_PLUGIN_ROOT} for portable paths within plugin:

Read ${CLAUDE_PLUGIN_ROOT}/tasks/step-1-workflow-name.md and execute.

Sub-agent will use Read tool to fetch the file content.

Implementation Process

Step 1: Gather Requirements

Ask user (if not provided):

  1. Workflow name: kebab-case identifier (e.g., feature-implementation)
  2. Description: What the workflow accomplishes
  3. Steps: List of discrete steps with:

- Step name - Step goal - Required tools - Expected output

  1. Execution mode: Sequential or parallel steps
  2. Agent type: general-purpose or custom agent

Step 2: Create Directory Structure

# Create tasks directory (if it doesn't exist)
mkdir -p ${CLAUDE_PLUGIN_ROOT}/tasks

# Optional: Create agents directory (if using custom agents)
mkdir -p ${CLAUDE_PLUGIN_ROOT}/agents

Note: All task files (both workflow-specific steps and shared context) are placed directly in tasks/ without subdirectories.

Step 3: Create Task Files

For each step, create a task file with this structure:

# Step N: <Step Name>

## Context
You are executing step N of the <workflow-name> workflow.

## Goal
<Clear, specific goal for this step>

## Input
<What this step receives from previous steps or user>

## Instructions
1. <Specific action>
2. <Specific action>
3. <Specific action>

## Constraints
- <Limitation or boundary>
- <What NOT to do>

## Expected Output
<What to return to orchestrator>

## Success Criteria
- [ ] <Measurable outcome>
- [ ] <Measurable outcome>

Step 4: Create Orchestrator Command

Create the main command file with this pattern:

---
description: <Workflow description>
argument-hint: <Required arguments>
allowed-tools: Task, Read
model: sonnet
---

# <Workflow Name>

## User Input

\`\`\`text
$ARGUMENTS
\`\`\`

## Workflow Execution

### Step 1: <Step Name>

Launch general-purpose agent:
- **Description**: "<3-5 word summary>"
- **Prompt**:
  \`\`\`
  Read ${CLAUDE_PLUGIN_ROOT}/tasks/step-1-<workflow>-<name>.md and execute.

  Context:
  - TARGET: $1
  - MODE: $2
  \`\`\`

**Capture**: <What to extract from result>

### Step 2: <Step Name>

Launch general-purpose agent:
- **Description**: "<3-5 word summary>"
- **Prompt**:
  \`\`\`
  Read ${CLAUDE_PLUGIN_ROOT}/tasks/step-2-<workflow>-<name>.md and execute.

  Context from Step 1:
  - <Key data from previous step>
  \`\`\`

### Step 3: <Step Name>

[Continue pattern...]

## Completion

Summarize workflow results:
1. <What was accomplished>
2. <Key outputs>
3. <Next steps if any>

Frontmatter Options

FieldPurposeDefault
descriptionBrief description of workflow purposeRequired
argument-hintExpected arguments descriptionNone
allowed-toolsTools the command can useInherits from conversation
modelSpecific Claude model (sonnet, opus, haiku)Inherits from conversation

Model selection:

  • haiku - Fast, efficient for simple workflows
  • sonnet - Balanced performance (recommended default)
  • opus - Maximum capability for complex orchestration

Execution Patterns

Pattern A: Sequential Steps (Default)

Each step depends on previous step's output:

### Step 1: Analyze
Launch agent → Get analysis result

### Step 2: Plan (uses Step 1 result)
Launch agent with Step 1 context → Get plan

### Step 3: Execute (uses Step 2 result)
Launch agent with Step 2 context → Complete

Pattern B: Parallel Independent Steps

Steps can run concurrently:

### Analysis Phase (Parallel)

Launch 3 agents simultaneously:
1. Agent 1: Security analysis → Read ${CLAUDE_PLUGIN_ROOT}/tasks/step-1a-security.md
2. Agent 2: Performance analysis → Read ${CLAUDE_PLUGIN_ROOT}/tasks/step-1b-performance.md
3. Agent 3: Code quality analysis → Read ${CLAUDE_PLUGIN_ROOT}/tasks/step-1c-quality.md

**Wait for all**, then consolidate results.

### Synthesis Phase
Launch agent with all analysis results...

Pattern C: Stateful Multi-Step (Resume)

When steps need shared context:

### Step 1: Initialize
Launch agent, **capture agent_id**

### Step 2: Continue (same context)
Resume agent using agent_id:
- **resume**: <agent_id from Step 1>
- **prompt**: "Proceed to phase 2: <additional instructions>"

Example: Feature Implementation Workflow

Orchestrator Command

---
description: Execute feature implementation through research, planning, and coding phases
argument-hint: [feature-description]
allowed-tools: Task, Read, TodoWrite
model: sonnet
---

# Implement Feature

## User Input
\`\`\`text
$ARGUMENTS
\`\`\`

Create TodoWrite with workflow steps.

## Phase 1: Research

Launch general-purpose agent:
- **Description**: "Research feature requirements"
- **Prompt**:
  \`\`\`
  Read ${CLAUDE_PLUGIN_ROOT}/tasks/step-1-feature-impl-research.md

  Feature: $ARGUMENTS
  \`\`\`

**Extract**: Key findings, constraints, existing patterns

## Phase 2: Architecture

Launch general-purpose agent:
- **Description**: "Design feature architecture"
- **Prompt**:
  \`\`\`
  Read ${CLAUDE_PLUGIN_ROOT}/tasks/step-2-feature-impl-architecture.md

  Feature: $ARGUMENTS
  Research findings: <summary from Phase 1>
  \`\`\`

**Extract**: File structure, components, interfaces

## Phase 3: Implementation

Launch developer agent:
- **Description**: "Implement feature code"
- **Prompt**:
  \`\`\`
  Read ${CLAUDE_PLUGIN_ROOT}/tasks/step-3-feature-impl-implement.md

  Architecture: <summary from Phase 2>
  \`\`\`

## Completion

Mark todos complete. Report:
1. Files created/modified
2. Tests added
3. Remaining work

Task File Example (step-1-feature-impl-research.md)

# Step 1: Feature Research

## Context
You are the research phase of a feature implementation workflow.

## Goal
Thoroughly understand the feature requirements and existing codebase context before any implementation begins.

## Instructions

1. **Parse Feature Request**
   - Extract core requirements
   - Identify acceptance criteria
   - Note any constraints mentioned

2. **Codebase Analysis**
   - Search for similar existing features
   - Identify relevant patterns and conventions
   - Find reusable components/utilities

3. **Dependency Check**
   - What existing code will this feature interact with?
   - Are there breaking change risks?
   - What tests exist for related functionality?

4. **Gap Analysis**
   - What's missing from the request?
   - What clarifications might be needed?
   - What edge cases should be considered?

## Constraints
- Do NOT write any implementation code
- Do NOT modify any files
- Focus purely on research and analysis

## Expected Output

Return a structured research summary:

\`\`\`markdown
## Feature Understanding
- Core requirement: <summary>
- Acceptance criteria: <list>

## Codebase Context
- Similar features: <list with file paths>
- Patterns to follow: <list>
- Reusable code: <list with file paths>

## Dependencies
- Files affected: <list>
- Tests to consider: <list>

## Open Questions
- <Question 1>
- <Question 2>

## Recommendation
<Brief recommendation for architecture phase>
\`\`\`

## Success Criteria
- [ ] Feature requirements clearly articulated
- [ ] Relevant existing code identified
- [ ] No implementation attempted
- [ ] Clear handoff to architecture phase

Known Limitations

LimitationImpactWorkaround
No nested sub-agentsSub-agents can't spawn Task toolKeep all orchestration in main command
No skill auto-loadingSub-agents don't trigger skillsPass explicit file paths or inline context
Fresh context per agentEach dispatch starts emptyUse resume pattern OR pass summaries
File read latencyExtra tool call per stepAcceptable trade-off for context savings

Validation Checklist

Before finalizing workflow command:

  • Each step has clear, specific goal
  • Task files are self-contained (sub-agent doesn't need external context)
  • File paths use ${CLAUDE_PLUGIN_ROOT} for portability
  • Context passed between steps is minimal (summaries, not full data)
  • Orchestrator command stays lean (<100 tokens per step dispatch)
  • Error handling defined for step failures
  • Success criteria measurable for each step

Create the Workflow

Based on user input, create:

  1. Directories:

- ${CLAUDE_PLUGIN_ROOT}/tasks/ - All task files directly here - ${CLAUDE_PLUGIN_ROOT}/agents/ - (Optional) Custom agent definitions

  1. Task files: Create in tasks/ directory with naming pattern step-N-<workflow>-<name>.md

- Example: step-1-feature-impl-research.md - Example: step-2-feature-impl-architecture.md - Shared context: common-context.md directly in tasks/

  1. Orchestrator command: Lean dispatch logic in commands/<workflow-name>.md
  2. Custom agents (Optional): If workflow needs specialized agent behavior in agents/
  3. Update plugin.json: Add command to plugin manifest if needed

After creation, suggest testing with /customaize-agent:test-prompt command.

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

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

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

Codex

35.16%
按下载量换算125

Claude

28.62%
按下载量换算102

Cursor

16.92%
按下载量换算60

Gemini CLI

9.51%
按下载量换算34

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

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/neolabhq/context-engineering-kit --skill create-workflow-command 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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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