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Create Workflow Command

  • 868 installs
  • 1.3k repo stars
  • Updated August 3, 2026
  • neolabhq/context-engineering-kit

create-workflow-command is an agent tooling skill that generates reusable workflow commands orchestrating multi-step execution through sub-agents with file-based task prompts stored outside the main command.

About

create-workflow-command is a neolabhq/context-engineering-kit skill for building workflow commands that orchestrate multi-step agent execution. It accepts a workflow name and description, then scaffolds commands that dispatch sub-agents while storing detailed step instructions in separate files to solve context bloat in the orchestrator. Allowed tools include Read, Write, Glob, Grep, and Bash mkdir. Developers reach for create-workflow-command when turning repeatable natural-language procedures into structured, file-backed agent workflows.

  • Generates self-contained workflow command files from a single prompt
  • Enforces context-engineering standards for agent reliability
  • Produces deliverables that integrate directly with Claude Code and Cursor
  • Creates consistent command patterns across multiple agent projects
  • Reduces boilerplate when scaling from one-off prompts to production workflows

Create Workflow Command by the numbers

  • 868 all-time installs (skills.sh)
  • +24 installs in the week ending Aug 4, 2026 (Skillselion tracking)
  • Ranked #319 of 2,715 Automation & Workflows skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/neolabhq/context-engineering-kit --skill create-workflow-command

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Listed on Skillselion
Installs868
repo stars1.3k
Last updatedAugust 3, 2026
Repositoryneolabhq/context-engineering-kit

How do you build multi-step agent workflow commands?

Generate reusable workflow commands that turn natural language instructions into structured, repeatable agent actions.

Who is it for?

Developers designing repeatable multi-step agent workflows who need file-based prompts to limit orchestrator context.

Skip if: One-shot tasks or teams without sub-agent dispatch support in their agent runtime.

When should I use this skill?

A developer wants a workflow command that orchestrates sub-agents with externalized step instructions.

What you get

Workflow command files, sub-agent task prompt files, and mkdir-scaffolded directory structure for orchestration.

  • workflow command file
  • sub-agent task prompt files

Files

SKILL.mdMarkdownGitHub ↗

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

4. Execution mode: Sequential or parallel steps 5. 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

2. 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/

3. Orchestrator command: Lean dispatch logic in commands/<workflow-name>.md

4. Custom agents (Optional): If workflow needs specialized agent behavior in agents/

5. Update plugin.json: Add command to plugin manifest if needed

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

Related skills

How it compares

Pick create-workflow-command when multi-step agent flows need maintainable file-backed prompts instead of one giant inline command.

FAQ

What problem does create-workflow-command solve?

create-workflow-command externalizes detailed step instructions into separate files so the main orchestrator command stays lean and avoids context bloat during multi-step runs.

What inputs does create-workflow-command expect?

create-workflow-command takes a workflow name and description via argument-hint, then generates a command scaffold that wires sub-agent dispatch to file-based task prompts.

Automation & Workflowsagentsautomation

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