customaize-agent:create-workflow-command
Create a workflow command that orchestrates multi-step execution through sub-agents with file-based task prompts
Best use case
customaize-agent:create-workflow-command is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Create a workflow command that orchestrates multi-step execution through sub-agents with file-based task prompts
Teams using customaize-agent:create-workflow-command should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/create-workflow-command/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How customaize-agent:create-workflow-command Compares
| Feature / Agent | customaize-agent:create-workflow-command | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Create a workflow command that orchestrates multi-step execution through sub-agents with file-based task prompts
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
SKILL.md Source
# 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
```text
Workflow Name: $1
Description: $2
```
## Architecture Overview
Workflow commands solve the **context bloat problem**: instead of embedding detailed step instructions in the main command (polluting orchestrator context), store them in separate task files that sub-agents read on-demand.
```
plugins/<plugin-name>/
├── commands/
│ └── <workflow>.md # Lean orchestrator (~50-100 tokens per step)
├── agents/ # Optional: reusable executor agents
│ └── step-executor.md # Custom agent with specific tools/behavior
└── tasks/ # All task instructions directly here
├── step-1-<name>.md # Full instructions (~500+ tokens each)
├── step-2-<name>.md
├── step-3-<name>.md
└── common-context.md # Shared context across workflows
```
## Key Principles
### 1. Context Isolation
Each sub-agent gets its own isolated context window. The main orchestrator stays lean while sub-agents load detailed instructions from files.
| Component | Context Cost | Purpose |
|-----------|--------------|---------|
| Orchestrator command | ~50-100 tokens/step | Dispatch and coordinate |
| Task file | ~500+ tokens | Detailed step instructions |
| Sub-agent base | ~294 tokens | System prompt overhead |
### 2. Sub-Agent Capabilities
Sub-agents spawned via Task tool:
| Capability | Available | Notes |
|------------|-----------|-------|
| Read tool | ✅ Yes | Can read any file |
| Write tool | ✅ Yes | If not restricted |
| Grep/Glob | ✅ Yes | For code search |
| Skills loading | ❌ No | Skills don't auto-load in sub-agents |
| Spawn sub-agents | ❌ No | Cannot nest Task tool |
| Resume context | ✅ Yes | Via `resume` parameter |
### 3. File Reference Pattern
Use `${CLAUDE_PLUGIN_ROOT}` for portable paths within plugin:
```markdown
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
```bash
# 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:
```markdown
# 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:
```markdown
---
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
| Field | Purpose | Default |
|-------|---------|---------|
| `description` | Brief description of workflow purpose | Required |
| `argument-hint` | Expected arguments description | None |
| `allowed-tools` | Tools the command can use | Inherits from conversation |
| `model` | Specific 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:
```markdown
### 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:
```markdown
### 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:
```markdown
### 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
```markdown
---
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)
```markdown
# 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
| Limitation | Impact | Workaround |
|------------|--------|------------|
| No nested sub-agents | Sub-agents can't spawn Task tool | Keep all orchestration in main command |
| No skill auto-loading | Sub-agents don't trigger skills | Pass explicit file paths or inline context |
| Fresh context per agent | Each dispatch starts empty | Use resume pattern OR pass summaries |
| File read latency | Extra tool call per step | Acceptable 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
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